Episode 79

SPC#79 - And Don't Call Me Shirley

In Episode 79, we join Bill and guest host Tiffany Wolf as they navigate the flight path of AI with an interview with Alex List of FlyShirley.com. Fly Shirley is a tech startup dedicated to using AI for aviation. While we are in the infancy of this technology as it pertains to aviation, the conversation with Alex is very interesting as we dive into the possibilities, where they are currently at with their product, and what's to come.

Links:

Hope you enjoy the episode and thanks for listening! Visit the SPC website at https://studentpilotcast.com. Please keep the feedback coming. You can use the contact form on the website or send email to bill at student pilot cast dot com. The theme song for our episodes is "To Be an Angel" by the band, "Uncle Seth".

Legal Notice: Remember, any instruction that you hear in this podcast was meant for me and me alone in the situation that we happened to be in at the time.  Please do not try to apply anything you see or hear in this episode or any other episode to your own flying.  If you have questions about any aspect of your flying, please consult a qualified CFI.

Copyright 2008-2024, studentpilotcast.com and Bill Williams

Transcript
Bill:

Hello, SPC followers.

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Welcome back to another episode.

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I've got a little explaining

to do for this one, but I

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think you're going to like it.

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So bear with me a little bit.

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Once I bring you up to speed, we'll get

onto the main attraction for episode

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79

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And that's a very fascinating

discussion with Alex from flyshirley.

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com, an AI startup.

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That's all about aviation.

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So let's get into it.

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All right, so a bit of an explanation

before we dive into it I'll be brief

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because this is gonna be a long episode

anyway But I decided when I published

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episode 78 the last episode in late

September that I needed a bit of a

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break So I decided to take my birthday

month, October, off from the podcast

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while I recharged a little bit We had

some changes happening with the almost

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launched fledgling flightline podcast

that I'll get into in a little bit, but

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I just needed to take a little break.

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So I got some episodes partially

ready and held off on publishing

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supposedly until November.

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As you know, At that same time,

I've been trying to get my CFI

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checkride scheduled for ages, and

I wasn't sure when it would happen.

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But then, last couple of days of

October, I finally got the call.

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I got a checkride scheduled at an

airport about 60 nauticals miles

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away from my home airport for a

couple of weeks in the future.

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So now About the time I was going to

be starting the pet podcast publishing

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again, my focus turned to relearning how

to fly and how to pass a CFI check ride.

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As you can imagine, all my

focus turned towards that.

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And once again, I had to forgo

publishing for a little bit.

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I had a lot of cool stuff

already in the can, but.

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Now didn't have time to finish the edits

and do final publishing, et cetera.

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So I decided to wait another month.

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The good news is I passed my check.

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Right?

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So I'm a brand new CFI.

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The bad news is I ended up taking two

months off from the publishing instead

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of the one that I had originally planned.

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That said, I'm now back and I've

been wanting to get this one out for.

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Quite a while.

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It's really interesting.

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Now, there's one more thing.

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Tiffany and I originally recorded

this for, like I said, the

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Fledgling Flightline podcast.

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So that's what you'll hear

when we're talking to Alex.

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A couple of months ago, though, Tiffany

and I decided to pause the launch of

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that podcast, at least for a while,

as her situation was changing and we

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couldn't, you know, Put the focus on

it that we had hoped we'd be able to.

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We want to do it at some point somehow,

but the good news is I can focus on

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the student pilot cast even more.

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And since we already have a community

of listeners here, I'm glad that this

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interview will get more eyeballs and

more years on it anyway, by releasing

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it as a student pilot cast episode.

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As you'll see from the discussion, It

does have a bit of a student and learning

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orientation anyway, so it fits right in.

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So you're basically up to speed at a very

high level and we're back to publishing

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weekly for the student pilot cast.

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I certainly appreciate everyone's patience

as I recharged and then super charged

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for my check ride and then relaxed

a bit over the Thanksgiving holiday.

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So I hope everyone also had

a good relaxing holiday.

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As always, please reach out

with questions, suggestions,

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ideas, feedback, Everything.

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You can find me via email

at bill at studentpilotcast.

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com or use the contact form on the

website or even via X at, at billwill.

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That's Bravo, India, Lima,

Lima, whiskey, India, Lima.

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So with that said, I hope you enjoy

episode 79, and don't call me Shirley.

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right.

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Welcome back everybody to

the flight line podcast.

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We've got a really

special episode tonight.

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we're sitting here with Alex List,

who's part of the team at FlyShirley.

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And Alex and I met.

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Uh, sort of in happenstance, uh,

while we were looking at one of the

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other vendors at Oshkosh that had to

do with large language models and,

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and what we sometimes refer to as AI.

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And so we got to talking and

said, Hey, you know what, we

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should really get together and

talk about this on the podcast.

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So Alex, welcome to the

flight line podcast.

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Alex: Thank you very much.

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It's good to see you and Tiffany.

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Bill: Excellent.

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tell us a little bit about.

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Alex, and then we'll get to FlyShirley.

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Alex: Sounds great.

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So my background is actually

in apps and technology.

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So in high school, I taught

myself how to program iPhones.

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I had some of the first iPhones

in the app store and ended up

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winning an Apple design award.

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I got into MIT and I decided to study

aerospace because I felt I already

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knew computer science somehow.

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And so I, uh, so I studied

that for three years.

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I ended up dropping out

and making a startup.

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Coming back and switching

to computer science.

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And then I, then I got my private pilot's

license, back, got my master's in kind

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of a combination between aerospace

engineering and computer science.

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And I ended up having the opportunity

to lead flight simulation at a company

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called Beta Technologies up in Vermont.

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an electric protocol takeoff and

horizontal flight airplane company.

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They make some of the, I would say

some of the coolest electric airplanes,

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but also have some of the best sims

that you'd ever see on the planet.

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These amazing full dome, uh, half dome,

you know, wrap around flight sims.

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Really, really sweet.

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I worked on enabling the simulated flight

test and instructor operating stations.

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Helping with the avionics transition.

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I had the opportunity to bring some

of my thesis work into the avionics.

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When you, when you're flying these new

airplanes is a little bit different.

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And, and we ended up building about

eight different VR sims and flights in

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flight domes throughout the country.

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I left when the airplane is entering

production and worked at a leading

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aircraft autonomy company and had

the opportunity to work with some

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really great folks over my career.

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Ended up starting by Shirley in March

after, um, after some, and we can

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get into this a little bit more after

there was a little bit of an accident

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that my friend had, and I wanted to

be able to build something that could

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a difference for aviation safety.

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And so.

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and so we started, I started by building

something that you could fly with in a

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cockpit, and so you could fly with Shirley

while you're, while I was flying my DA42,

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I could ask questions and things like

this, but there are some limitations.

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And so one of my friends actually, uh,

I have a couple of friends at X Plane,

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and they said, Hey, you know, why

don't you try launching for Sims first?

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You know, you wouldn't have

the issue with hallucination.

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This wouldn't be a problem.

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You wouldn't have issues trying to

keep things online versus offline.

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And you would be able to sort of deal

with all these noise issues really easily.

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anyway, we, uh, we launched for flight

sim starting at flight simulator expo.

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And then, um, and then ended up,

uh, and then ended up here and I'm

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really happy to see you guys and,

and talk to you a little bit about.

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this sort of journey and so

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Bill: uh, some of that tech that you're

talking about, but I'm going to hold off.

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Because I want to ask, why aviation?

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What got you into aviation

in the first place?

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You, you said you started with

aerospace at MIT, and then

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you became a private pilot.

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How did that happen, and why?

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Alex: that's actually, that's actually

a really good, that's a great question.

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So I always was interested in space as a

kid, a huge sort of, you know, buff for

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all the sci fi movies runs in the family.

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You know, I wanted to be like a

lot of folks, I wanted to be an

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astronaut, but you do the sort of the

expected value calculation on that.

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And it kind of falls a little bit short.

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And so I thought to myself, what's

the opportunity that you'd have to.

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Sort of the best shot that you

could still kind of, you know,

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fly around and in air or space.

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And of course, the answer to

that is being a private pilot

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or becoming a pilot in general.

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And so, you know, I, I decided to get my

private pilot's license and, um, and it

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was probably one of the best decisions.

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You have the ability to, you know,

you have the superpower, right?

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You could just show up

somewhere, you know,

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Bill: You have, you have a flying carpet,

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Alex: do that.

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You have a

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Bill: A real, honest to

goodness flying carpet.

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It's amazing.

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Alex: It's just the coolest

thing you could possibly do.

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So there's like, you know, you know,

we're blessed to be in the United States.

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And I think just.

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Having this many sort of GA

airports around in this country

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is just such a phenomenal resource

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Tiffany: Yeah,

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Alex: you know, for, of course, all the

municipalities that they're in, but also

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for the individuals who can end up being

pilots and sort of embracing this love of

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flight that I had, you know, my teammates

and at Shirley's that Shirley's share and

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that, you know, of course, all of us here

on the podcast and listening to as well.

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Tiffany: I was looking at your LinkedIn

and I have to say that between you and

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the other two co founders, you guys look

like a bunch of slackers and with this 5.

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0 at MIT from Sam, so it

looks like there's three of

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you guys who founded this.

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Bill: You

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Tiffany: Obviously incredibly intelligent.

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Bill: Yep.

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Tiffany: was this?

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Alex: So, you know, I was

fortunate to meet, uh, Seb.

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Seb, I actually met, he was an intern

of mine while at Beta Technologies.

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He was a, sort of, he had just finished

his freshman year at McGill, and he was

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sort of looking for something to do.

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He grew up in Vermont,

Beta's up in Vermont.

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And Kyle, the CEO of Beta, said, Well,

you should check out this guy, you know.

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You know, you might not, you know, have

a ton of CS experience yet, but, you

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know, he's going to work really hard.

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He's trying, you should

like give him a shot.

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And so, you know, gave Seb a shot and by

three, four years later, I'm a co founder

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with him at my, at my current startup.

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so, you know, I, uh, I left my

job at Merlin labs in March and

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worked on the first prototype of

FlyShirley that you could fly with.

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ended up, you know.

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Getting some of my, some of my

friends and family to help me sort

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of stretch this a little bit farther.

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You know, I was really lucky to meet Sam.

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There's a, you know, for people who

like to start companies and are sort

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of interested in this sort of thing.

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There are these sort of like Tinder for

co founder type of websites that are

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as much of a crapshoot as any sort of

dating app you could possibly imagine.

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In this particular circumstance, you know,

Sam wrote me the nicest message ever.

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He said, well, actually, we went to

the same college, know, like all the

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same sort of things that you, yeah.

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So, you know, all right, we'll

leave it, we'll leave it at that.

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But, you know, he just wrote

out a very respectful, you

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know, very respectful message.

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Of course, his background, he

interestingly was one of the first, he's

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actually, he's, Actually in the army

for another couple of years, at least.

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And, and he was actually one of

the first people to go through the

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VR training sort of program they

had in the army, the initial one

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and for, for helicopter training.

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And so, you know, that's a

really interesting experience.

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He flies the.

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Um, the uh, a plane as a, as a fixed wing

operator there and, you know, his 1st,

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his 1st sort of attachment in the army,

if you will, was to go to MIT and get a

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master's and so, you know, just a really.

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a really good group,

initial group of people.

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And so that's, that's a little

bit how, how we got together.

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I'm actually surprised that I

didn't meet Sam while I was at MIT.

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By all rights, I should have,

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Bill: were there at the same time?

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Alex: things, things that, yeah, we were

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Bill: Okay.

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Alex: time.

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Bill: All right.

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you're all pilots.

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Alex: yeah.

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Hopefully.

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So, yes.

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So, you know, Sam flies

helicopters and the global:

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The, uh, said is a student pilot

and I'm a commercial multi engine

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instrument pilot, know, I'm looking

forward to getting my instructor

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pilots license and learning about some

of those fundamental of instruction.

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Oh, yeah, we love flight.

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Yeah,

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Bill: And did I hear

you say you fly a DA42?

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Is that what you said?

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Alex: that's what I fly.

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Yes, I fly

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Tiffany: Nice.

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Alex: out of Philadelphia

northeast airport.

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That's where my, that's where my family

lives is in sort of the Philadelphia area.

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So I end up going down there.

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I get to fly the 42.

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Actually, 1 of the coolest things that

I've done in that airplane was the at the

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eclipse that kind of ripped through the

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Bill: Yep.

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Yep.

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Right.

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Alex: up there with, uh, My, my,

my partner, me and her ended up

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flying up in there and seeing

this amazing 360 degree sunset.

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And, you know, you know, I was still

looking through these little glasses

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and I was, you know, looked down at the

instruments and then I look back and

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see this amazing sort of white Corona.

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That's

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Tiffany: Wow.

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Oh my

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Alex: and most resplendent way

you've ever seen in your life.

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So I would recommend it not to the point

where you don't listen to, you know,

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your TCAS or anything like that, but you

know, absolutely go, go check it out.

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There was, you know, you'd be in good

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Bill: I, I wasn't in the air for that

eclipse, but I did go to Totality

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in Texas and it was one of the most

incredible things I've ever experienced.

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So I can imagine it, it must've

been incredible in the air too.

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Alex: You see this sort of wall

of darkness kind of flying towards

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Bill: Yes.

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Alex: some, you

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Bill: Yes.

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Alex: You think it's just like just

rain, like the thickest rain you've

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ever seen in your entire life.

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But

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Bill: Yeah.

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Alex: know, it passes you and then

you start to see the sort of the

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light coming around the same way.

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And just sunset in all

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Bill: Everybody made fun of me for

my reaction to it because it made me

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feel so small and so at the same time.

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It was, it was incredible.

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Yes.

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Alex: Like, like within

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Tiffany: Oh, interesting.

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Alex: the heat on.

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Bill: Yeah.

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Alex: Yeah, within moments.

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Bill: Interesting.

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Alex: yeah.

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Bill: Well, I don't know that

I'll be around for the next one

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that happens in North America.

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Um, cause I am kind of

an old guy, but, um,

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Alex: ha

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Tiffany: here we go again.

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Bill: and I still have a medical, I might

have to try it from the cockpit next time.

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that's a great idea.

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Alex: Let's go.

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I'll brave you.

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Tiffany: There we go.

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Alex: what.

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Yeah.

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Bill: Excellent.

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Alex: In any form.

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Bill: Well, thanks for

all that background.

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So, um, one of the things you

mentioned, and you've sent us

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information about Fly Shirley.

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It's clear that, like you said,

you started with, with Sims.

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Tell us, tell us what your approach

was with Sims and then where you're at,

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uh, with the product as it pertains to,

uh, flying in, um, actual airplanes.

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Alex: Yeah.

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No, thanks for that.

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So, Shirley is designed to be

your AI co pilot from Sim to Sky.

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It's set up so that pilots can

just talk to Shirley naturally,

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just like a co pilot friend sitting

next to them in the cockpit.

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So surely provides training in the

SIM to help people prepare for lessons

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and check rides and proficiency.

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so our goal has always also been to

bridge people from SIM And so in the long

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term, we're working towards being able

to have surely apply back in the cockpit.

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so, you know, our approach starting with

the SIM has been to sort of home SIM

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flight users, people who actually just.

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You know, Flight Simulator released

a metric, 15 million users Microsoft,

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uh, at Flight Sim Expo, they made this

new metric book at 15 million users,

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Microsoft Flight Simulator, of this

amazing sort of trend of getting more

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and more people involved, interested in

flight through this sort of sim community.

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And so, you know, we've started

with a co pilot that just.

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Really easily connects to We're

starting with explain because we're

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friends with the explain guys.

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all you need to do is you open a web

browser and then you go to flyshirley.

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com and then you hit start call and.

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Immediately, Shirley's talking to you

and sort of says, sort of airplane

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teammates up, mic check when ready,

and then you get connect to explain.

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You don't have to install any

plugin or anything like that.

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As long as you just explain 12 and

then it just immediately connects

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and has a window seat into your sin.

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so we just start with this sort of,

you know, this a I kind of copilot.

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Shirley's your copilot.

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You talk.

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It's really immediately replies.

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You end up having this kind of nice

conversation, no matter where you're at.

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Surely.

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an idea of where you are and give you

info about where you're flying to.

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So we sort of have three

different sort of modes.

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We're starting here with this sort of.

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Home flights in.

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And so folks there, some people just

want us, you know, try out different

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airplanes, cruise around different areas.

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There's all sorts of reasons I'd be

able to sort of home flight sitting.

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And then there's sort of a, we've

introduced a sort of challenge

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feature as well, that, you

know, we can make challenges.

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Other people can build challenges as well.

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So the first one is this Aaliyah 250

flight training type of challenge where.

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You know, explain ships with the

model of the alia to 15 beetle mode.

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And so with that challenge, essentially,

surely is stepping you through, you

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know, the controls check is stepping

you through this sort of initial.

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How do you hover?

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How do you have control in that sort

of mode and then how do you transition

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out and sort of transition back in and

so surely kind of walks you through

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this and that sort of automated fashion

challenges are really set up for other

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people to be able to kind of build

fun, little interactive capabilities.

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And we have the sort of for people who use

chat or whatever we have already sort of.

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You know, example, example, prompts

that you would just follow and be able

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to create these things and things like

skull challenges that possible, sort

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of this, you know, you can have landing

challenges, different sorts and explore

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different areas that you're interested in.

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also just launched on Friday.

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We just launched a sort of the first

version of our private pilot curriculum.

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so that's really the sort of

the first step into training.

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And private pilot, uh, curriculum is

really interesting that we end up being

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able to teach people about some level

of, know, taxiing, you know, from the

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fundamentals of, you know, what do you do?

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What does it feel like to

actually take a lesson?

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But to also let people be

prepared for their lessons.

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So let's say you just went out and did

sort of in terms of at a point with

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your instructor, and now, you know,

you're going to go make sure you got

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it by next week and you're going to go

either your instructor is either going

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to test you at the beginning of the

lesson and then have you do something

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else or they'll test you at the lesson.

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And if you don't do it, they're

going to make you do it again.

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And so maybe you'll go and prepare for

that lesson and be able to make sure

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you really nail it when you get back.

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And one of the things that.

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:

We provide with surely is sort of

feedback while you're doing the

372

:

maneuver, but we also keep the sort

of a data log of you doing that

373

:

are able to sort of chart it out.

374

:

Surely is able to talk to you about

sort of the, you know, the sort of the

375

:

flight data and sort of your results.

376

:

You have sort of a indication of

what would be to the ACS standards.

377

:

So some people would really like to be

able to prepare for their, for their

378

:

sort of check ride, because it's pretty

expensive and it's pretty high stress,

379

:

you don't want to, you know, mess up.

380

:

And so, you know, to varying

levels, depending on the fidelity

381

:

of somebody's sim and their setup

and all these different things, you

382

:

know, we can provide value based

on our private pilot curriculum.

383

:

And so that's live right now.

384

:

And then we're also sort of working to

bridge our way into different levels

385

:

of kind of commercial environments.

386

:

have a sort of a pilot program with.

387

:

With actually beta starting September,

where we're going to be providing.

388

:

That's sort of, you know, training, sort

of familiarization to the employees of the

389

:

company so that they can, you know, when

they have VR seats throughout the company.

390

:

And so when an employee comes by, they

can just sort of sit down in the seat and

391

:

be able to try it out, be able to like,

how do I actually fly this airplane?

392

:

I kind of forget I had it on my

first day as a lesson in but I

393

:

really just want to, like, see what

it's like in order to fly again.

394

:

I went, you know.

395

:

And it's really fun and kind of

like interactive and and can be

396

:

pretty inspiring for the employees.

397

:

looking at commercial

opportunities at various levels.

398

:

For instance, if somebody has a, a

aviation advanced training device that.

399

:

You know, the, one of the really

interesting trends, I think, is that

400

:

those are starting to be reduced in price.

401

:

They're now also, you know, you

know, there's also VR type AATDs,

402

:

you know, loft dynamics is a company

that is certified, uh, FAA now

403

:

for one of their, for an Airbus.

404

:

And so one of the cool things is that as

instructors are really in high demand,

405

:

just like pilots are really in high

demand, surely can provide training that

406

:

prepares people for their instruction.

407

:

and one of the things that we're

looking to do is be able to provide

408

:

sort of both surely providing

instruction, but also having the sort

409

:

of channel to allow sort of remote

instructors for people to check in.

410

:

This is sort of especially interesting

for commercial operators, like, you

411

:

know, companies at the same scale as.

412

:

JetBlue or American airlines, United,

et cetera, where you have to spend

413

:

multiple weeks on site when you're

trying to get a new tech rating.

414

:

And so if you were able to spend some

time at home with your family, not

415

:

have to, you know, from the eyes of the

operators have to do the spend of being

416

:

at a hotel per diem and all this other

stuff running around the flights, et

417

:

cetera, you know, displacing revenue

fares, know, then, you know, you'd

418

:

be able to prepare, show up prepared.

419

:

Have check ins with instructors remotely

as you're preparing at home and then sort

420

:

of, you know, show up for the 1 week where

you need to have the full flight simulator

421

:

and be able to have your 20 hours.

422

:

And then, you know, you're good to go.

423

:

But, you know, this is sort of things that

we're looking at and sort of, you know,

424

:

on the track towards getting be able to

bring Shirley back into the cockpit where

425

:

actually you begin by sort of taking.

426

:

Some of the learnings and, you

know, working with some of, you

427

:

know, the, the, the, um, some of the

folks that are amenable to saying,

428

:

yeah, like I support the mission.

429

:

Like, I'd love to be able to make flight.

430

:

Safer, you know, you know, I'm in for,

uh, I'm in for sort of stuff like that.

431

:

Then we're able to make some of these

features that surely has in terms of

432

:

interactability, conversationality

available on, on an iPhone so that

433

:

pilots can talk to Shirley while

they're flying and that can provide.

434

:

A lot of sort of overhead, especially

in the GA context to begin with

435

:

where, you know, task saturation,

et cetera, is really hard.

436

:

And sometimes like if you're flying

in instrument conditions and then

437

:

something breaks and now you need this

number, you can't remember the thing.

438

:

And it's just, it just ends

up being a mess where you can

439

:

just ask for the information.

440

:

And this ends up being kind of a kind of

thing, but we're kind of working our way

441

:

back to there, which was where we started.

442

:

And I think along the way, we're

providing a really revolutionary

443

:

training product that.

444

:

a lot of value for people.

445

:

Surely folks have tried out at flyshare.

446

:

com, but it's, and there's a free

trial for that, but it's, it's a really

447

:

engaging sort of system and doesn't,

think quite a good job at being able

448

:

to provide a level of training that

helps people prepare for check rides

449

:

and help them with proficiency too.

450

:

Tiffany: Can you do a, could you set up.

451

:

Bill: into it.

452

:

Yeah.

453

:

Alex: Right.

454

:

So one of the things that we're

working towards, so we, then

455

:

there's two parts of that.

456

:

One of them is sort of the, the.

457

:

Oral examination part of that.

458

:

And no, that part is actually pretty,

pretty straightforward and pretty easy to

459

:

do because, you know, there's some aspect

of a question bank, surely has been,

460

:

you've been talking to Shirley, Shirley

has some ideas of things that you're,

461

:

are your weak points over, over time.

462

:

And so you can kind of have

a conversation and be sort of

463

:

grilled in the service, similar way

that you'd be grilled in person.

464

:

And, and then there are those

maneuvers aspects of it.

465

:

And the maneuvers aspects of it is

what's really neat about the ACS is

466

:

that it really lays out like the precise

parameters, you know, plus or minus

467

:

50 feet, you know, of course, they

say things in the ACS, like you can

468

:

temporarily exceed that,

you know, these thresholds.

469

:

But if you consistently exceed

them, and that's a, that's a fail.

470

:

So there's like, there's some

soft barriers, and that's

471

:

actually to be totally, totally.

472

:

On this, one of the really cool

things about using this sort of new AI

473

:

technology is that it has a lot more of a

holistic view on how things are working.

474

:

And so when you provide this sort

of graph that shows how tolerances

475

:

are exceeded temporarily, et cetera,

then you really do get kind of like

476

:

hear the whole story about, yeah,

this is if you're going to focus and

477

:

you had time to focus on something.

478

:

This is what you should focus on.

479

:

But overall, you might like

depending on the examiner, then

480

:

you probably would speak by.

481

:

And so, you know, there's stuff like that.

482

:

And, you know, there's so absolutely.

483

:

That's 1 of the things that

we're looking to provide.

484

:

I think 1 of the major sources of value

on top of helping people to prepare.

485

:

For their particular lessons

and and aspects like that.

486

:

Of course, there's different depending

on the equipment that they have.

487

:

And I think,

488

:

Tiffany: Yeah.

489

:

Alex: maybe we'll get into

this a little bit more.

490

:

There's different things that

are probably best suited to

491

:

help their training at home.

492

:

You know, a lot of people who are

pilots have iPads, probably the

493

:

majority of them by now or or iPhones.

494

:

And so there's sort of, you know,

equipment amenable to that, you

495

:

know, the intersection of people

who have amazing flight sims that

496

:

have monitors like wrapping around

or VR headsets with like world edge

497

:

leading kind of gaming computers.

498

:

That's a much smaller subset of folks,

but, you know, there's, there's these

499

:

sort of interesting opportunities where.

500

:

You start to be able to expand and sort

of the trends in the industry are such

501

:

that you start to be able to see that

really good representative Sims are sort

502

:

of making it out in the customer's hands.

503

:

Microsoft Flight Simulator gets better

and better, know, as does sort of

504

:

the number of computers that can run

something like X Plane and, you know,

505

:

There's sort of VR headsets get really

a lot cheaper and a lot more accessible.

506

:

You know, there's other aspects

related to, of course, related to

507

:

AI and also certified sims becoming

more affordable and things like that.

508

:

I think are really

interesting trends right now.

509

:

Yeah, thanks.

510

:

Bill: those are all sort of, those are

all sort of on your, I guess your roadmap

511

:

target list to investigate how Shirley

specifically can enhance that experience.

512

:

Yeah.

513

:

Yeah.

514

:

Yeah.

515

:

Alex: so you look at some, some folks,

even some streamers, this person named

516

:

Swiss001, who made a video about Shirley.

517

:

It's pretty funny.

518

:

could link it or something, but

the, the, The thing that he says

519

:

is that he got to start by, you

know, learning with infinite flight.

520

:

And so he got interested in being

able to fly because he had this

521

:

iPad app that showed him how to fly.

522

:

you know, they're sort of, they have

a, they have a data interface for sure.

523

:

They could very easily have a window

seat into that sort of experience.

524

:

don't, you know, their planes,

they don't have, they don't have

525

:

sort of a very interactive sort

of FMS or something like that.

526

:

But they do have sort of like a

navigation system and things like that.

527

:

So there's different levels and it's

sort of like also Microsoft lights.

528

:

And they've been around the Xbox.

529

:

You know, people can be able to fly

using a remote, but or like a game pad.

530

:

But, you know, they can also attach sort

of yolks and things like that to it.

531

:

you know, you can look at

the folks that have sort of a

532

:

sort of a single monitor or.

533

:

MacBook Pros now can all run X Plane

12 like really well because they have

534

:

these amazing processors on them.

535

:

And, you know, even with this either on

the, on the laptop or with the monitor,

536

:

that makes it a really, really quite

reasonable IFR platform for, for training.

537

:

if you want to be able to do something

where you have representative

538

:

maneuvering, then you either need to

get really fancy with the way you sort

539

:

of map, you know, keys on your yoke

for looking left or looking right, or

540

:

you need to have multiple monitors.

541

:

But then you can start to use something

like explain, which has a really

542

:

impressive flight model, even for

slow flight in order to be able to

543

:

see kind of realistically touchdowns,

takeoffs and be able to some sort

544

:

of stalls and things like that.

545

:

And so, you know, there's just, there's

just are a total variety of different

546

:

platforms where, you know, uh, where the

application of surely makes some sense

547

:

where, you know, surely can provide

helpless sort of instrument procedures,

548

:

give you, give you the numbers, help you

set up for the approaches, et cetera, sort

549

:

of judge how you did, where did you break

out, you know, where did you knock off?

550

:

Like things like that.

551

:

And, and, you know, um, and we're, and

we're also looking at how to engage.

552

:

With, you know, how to bring

flight instructors, of course,

553

:

to are such an important aspect.

554

:

We really see surely as a, as a tool

to help people prepare for those

555

:

lessons, especially since there is

such a pilot shortage, you know,

556

:

3000 just in the United States by

:

557

:

Tiffany: Yeah, huge.

558

:

Alex: that.

559

:

They're only getting worse.

560

:

Tiffany: Okay, I have a

quick layman question here.

561

:

So if I had a flight simulator right

now, which I do not, what kind of

562

:

guidance does it come with already?

563

:

Or is, all of a sudden, Fly

Shirley like this holy cow moment?

564

:

You know, my nephew, he's working on

his private right now at Cal Baptist.

565

:

So he takes his checkride in September.

566

:

Um, but, like, let's say that he

gets a flight simulator and he

567

:

jumps on it and he's not a pilot.

568

:

Is there any sort of, um,

tutorial or information?

569

:

Like, how do people learn how to fly

on a flight simulator besides just

570

:

game theory and trial and error?

571

:

Alex: you know, we don't, we don't

exist within a vacuum for sure.

572

:

You know, there's, there's actually

a lot of precedent for both, both

573

:

apps that people can add on for doing

training on their, on their sims.

574

:

And also, of course, the, there's a

whole cohort of people who have been

575

:

doing sort of training content for sims.

576

:

There's just so many like amazing

creators that do this sort of thing.

577

:

So.

578

:

Tiffany: But those would

live on YouTube or?

579

:

Alex: yeah.

580

:

And so actually a lot of people to

be interested in doing Sims things

581

:

because they were somehow kind of cross

marketed on YouTube and had sort of

582

:

a video that shows up and it's like,

Oh, here's this really cool person

583

:

doing like, you know, beetle VR, which

is this amazingly accessible sort of

584

:

You know, the fighter sort of like

but it's really easy to get going.

585

:

Or somebody sees an X Plane demo

where somebody is like, you know,

586

:

really being super concentrated,

flipping switches on, you know, seven,

587

:

three, seven, or something like that.

588

:

And people want to get involved with that.

589

:

And so, you know, what's

interesting is that for sure we

590

:

don't exist within a vacuum, so.

591

:

There are, you know, there have

been historically companies that can

592

:

provide a sort of standards based,

very specific kind of add on that

593

:

sets you up in a particular maneuver

and then looks to see your altitude

594

:

and sort of like really specifically

has these triggers and is just very,

595

:

very precise and gives you sort of.

596

:

Like a percentage like score based

on whether like how much and how

597

:

long you were within tolerances.

598

:

And if you're exactly at 100 percent the

entire time, then, you know, then the

599

:

best, but, you know, so, you know, there

was a whole generation prior of people

600

:

who have been trying to build sort of, you

know, tools to help people with training.

601

:

I think it's been hard to call those sort

of teammates because they're not really.

602

:

You know, interactive or copilots because,

you know, there are, there have been

603

:

sort of historically there's a, a tool

called Linda for the explain explain 11

604

:

and 12, which is sort of like a copilot

that's sort of for the zebo mod, which

605

:

is the popular kind of mod for a 737 that

adds a lot more interactivity and a lot

606

:

of really cool things and explain, but,

you know, what Linda does is be able to

607

:

sort of You know, you can use basic voice

recognition that sort of matches commands

608

:

like Alexa would in 2024, at least, and

be able to basically, you know, flip

609

:

switches for you and things like that.

610

:

You know, the, the previous company

I was talking about was sort of the.

611

:

Sort of, sort of kind of laid out

sort of, um, parameters is something

612

:

called, um, take play interactive.

613

:

Even like Sporty's sells

that sort of thing.

614

:

You know, there are really kind of

innovative companies that also sell You

615

:

know, Sporty's is a good example of that.

616

:

For instance, they.

617

:

You know, they are working with infinite

flight to try to provide lessons to

618

:

certain degrees in infinite flight,

like they have their own sort of

619

:

explained scenarios sort of bundle.

620

:

They, of course, have all their training.

621

:

I did my instrument sort of ground

school with them, and they also

622

:

sell Microsoft Flight Simulator

apparel for what it's worth.

623

:

But the, the, the interesting thing

about some of these opportunities,

624

:

I would say, in these companies.

625

:

Is that, you know, they

are not as interactive.

626

:

I mean, fundamentally what's, what's

been the new kind of breakthrough

627

:

with all this AI is that now you

can just have natural language.

628

:

Be able to map into the whole space of

possibilities for what you're going to do.

629

:

And so right now, surely, for

instance, you could just, know, for

630

:

the home flights and market, you can

ask Shirley to put down the flats

631

:

to like bring up the gear to turn

off the lights and things like that.

632

:

Like, you know, all these sort of,

sort of, you know, fundamental things.

633

:

And just by using natural language

and you can sort of describe things,

634

:

you can say, do this and that, and

that, and all those things happen.

635

:

Yeah.

636

:

Versus, you know, the issue with

sort of speech recognition up until

637

:

this point is that you just literally

are translating speech into words,

638

:

Tiffany: Right,

639

:

Alex: not sort of like an understanding

layer, whereas as people, we just sort

640

:

of like hear a bunch of stuff, and then

we have like an idea of what already

641

:

they wanted and sort of like, you know,

we walk into a coffee shop, and you

642

:

could probably mumble some things and

get a coffee, and, you know, that's

643

:

maybe not the sort of deal, just sort

of a basic sort of speech recognition.

644

:

So it's sort of the new,

sort of like the new.

645

:

Um, kind of, uh, standard is to

kind of combine speech recognition

646

:

plus some sort of intelligence.

647

:

Tiffany: right.

648

:

Alex: And that's absolutely what

we're doing with Shirley and have

649

:

sort of a, uh, a leg up on that.

650

:

Yeah.

651

:

Bill: Cool.

652

:

Tiffany: That's, this is awesome.

653

:

I'm loving it.

654

:

I, sorry Bill, I, I ended up getting A

complete sinus infection for two weeks

655

:

after my instrument, which I passed,

but I was just terrified of that one.

656

:

And, you know, as you're talking,

it's like, man, something like

657

:

this would have been so helpful.

658

:

Just to sit with somebody else by yourself

that you know is not a real person

659

:

that you have to face is going to go.

660

:

God, that chick's an idiot.

661

:

So, uh,

662

:

Alex: Yeah.

663

:

The

664

:

Tiffany: thing

665

:

Alex: the instrument that

can be brutal because

666

:

Tiffany: else.

667

:

Alex: have any random symbol on anything

and it's just like, Oh God, I don't, never

668

:

Tiffany: Yeah,

669

:

Alex: the DME arc and all, okay.

670

:

Yeah.

671

:

Totally agree.

672

:

Tiffany: I don't know if we want to

transition to this, but I am so curious.

673

:

Uh, you had made a comment

as to why you started this.

674

:

What really brought that idea on?

675

:

Um, I'd love to hear that story.

676

:

Alex: Yeah.

677

:

So.

678

:

Yeah, it was actually a kind of a, a

tragic, it was a tragic event, really.

679

:

I mean, I, a friend of mine

crashed his cozy and ended

680

:

up passing away through that.

681

:

And you know, when you, when

something like that happened, you

682

:

just sort of get kind of shaken out

of whatever you're doing currently.

683

:

For me, it was sort of, I was

running a flight sim team at,

684

:

at, Um, and Merlin was a great

aviation autonomy company in Boston,

685

:

I sort of saw that there could

be an opportunity to make

686

:

aviation even somewhat safer.

687

:

And, you know, I don't know, sometimes

when you feel really powerless, you

688

:

just try to figure out something you can

689

:

Tiffany: Right.

690

:

Alex: to help in some way.

691

:

Right.

692

:

And so I thought, like, maybe there's

some sort of a way to apply this new

693

:

technology and and be able to see if.

694

:

Get it make safer and while still

appreciating aspects of flight

695

:

being really worthwhile and fun

and sort of, you know, kind of

696

:

kind of wondrous in a lot of ways.

697

:

And I think that's 1 of the things that

that flying through the eclipse made me

698

:

remember was was that, you know, you know,

Yeah, flying is just incredibly beautiful.

699

:

We notice it every a lot of a lot

of afternoons and evenings when you

700

:

find in the sunset or something.

701

:

And so, you know, starting by trying

to see, even just from a very direct

702

:

way, does this actually improve fine?

703

:

Is there an opportunity to actually make?

704

:

safer and so things that I noticed

immediately for this from a GA context

705

:

were when there were issues that required

digging through a POH could be, you

706

:

know, 1000 pages long in the case of

a DA 42, you know, things that were

707

:

like, related to numbers that you had

to keep on recalling that, you know.

708

:

You know, might not be able to do if

your hands are actually on the controls,

709

:

or if you're on a pilot, it's maybe

unreliable, or if you're in the soup and

710

:

you don't want to like move your head into

weird directions, of opportunities where

711

:

folks in particular don't necessarily

have a teammate a copilot, right?

712

:

If you're flying up a buddy, or you got a

friend, or you can do a lot of this stuff,

713

:

and that's like, that's pretty great, but,

you know, having an opportunity to have.

714

:

You know, something you talk to about that

the flight help you kind of think things

715

:

through ended up being a pretty useful

thing, at least from my perspective,

716

:

and it'd be pretty be pretty helpful.

717

:

But you have to make sure that it's safe.

718

:

There's no exceptions.

719

:

Like, you have to make sure that.

720

:

It's not making stuff up.

721

:

It's not acting wild that it can

hear you, that it runs on your phone

722

:

without melting your phone or making

it like immediately drain and die

723

:

from battery or something like that.

724

:

And so, you know, starting with sims.

725

:

And working your way back to flight seemed

like the most responsible way to doing

726

:

that, because, you know, you'd be able

to have the advantage of having a huge,

727

:

a huge cadre of people in the sort of

sim land to be able to try out the things

728

:

that you're building in service of being

able to make something work in flight.

729

:

you know, you'd be able to see whether

those you'd be able to see really quickly.

730

:

People ask, you know, I've learned that

people sort of celebrate that surely can

731

:

talk about sports and things like that.

732

:

And

733

:

Bill: Yeah.

734

:

Alex: know, I see lots

of fun stuff, you know.

735

:

So I learned from Shirley about

football formations that like are,

736

:

Tiffany: that's funny.

737

:

Alex: and it's true, you know, Shirley

knows about all sorts of stuff because,

738

:

know, there's a enormous sort of

intelligence model behind it and,

739

:

and so, of course, like, you know,

even Shirley can tell you about the

740

:

best restaurants near the particular

airport that you're flying over.

741

:

Don't expect necessarily that

Shirley off the bat would be

742

:

able to do that on your phone.

743

:

But, you know, because it

has to run offline in your

744

:

pocket, um, on your dashboard.

745

:

But, you know, we're kind of building up

towards being able to provide things that

746

:

are safe and also still conversational

747

:

Bill: Yeah.

748

:

Alex: it's when, when you're able to

have that context, it's able to hear

749

:

hopefully, or, you know, ideally also be

connected into some message to the panel.

750

:

So there's a lot of

things to be figured out.

751

:

Along along that way.

752

:

However, I think the sort of the value

of having something or certain or

753

:

surely or something that you talk to

while you're flying is is absolutely

754

:

there, but it takes a lot of work.

755

:

You got to get it right.

756

:

Bill: Yeah.

757

:

Right.

758

:

Alex: to

759

:

Bill: takes.

760

:

Alex: way up.

761

:

Bill: Um, not only practice um,

learning on the model and the,

762

:

um, intelligence models part, but

it's going to take learning and

763

:

practice from the pilots as well.

764

:

So if you don't mind, um, I'm going to

branch off into a couple of different

765

:

areas and I'm going to start with

the product itself and the, the vast

766

:

opportunity tonight for me to geek out

with you is there, I want to do it on the,

767

:

on the Aviator and educator side, but I'm

going to hold off on that for a second.

768

:

I want to geek out on the actual

product a little bit, if you don't mind.

769

:

So I'm going to ask you a series of

questions that take us down that road.

770

:

Um, first of all, um, I know

this is an overloaded term.

771

:

You're using a large language model.

772

:

You're using, uh, you're

using an intelligence model.

773

:

Um, do you call it AI or do you

stay away from that overloaded term?

774

:

Alex: That's a good that's a

that's a reasonable question.

775

:

I think it is, okay, so I think

AI has become the suitcase

776

:

Bill: Yep.

777

:

Alex: defines the category of things

that use large language models, you

778

:

know, there's a whole kind of, there's

a whole cadre of people that go

779

:

into all sorts of rabbit holes about

artificial intelligence, and then they're

780

:

starting to worry about, you know,

plotting robots and things like that,

781

:

that don't make a lot of sense to me.

782

:

But.

783

:

Okay.

784

:

You know, starting and I think,

you know what I'm talking

785

:

Bill: Yeah.

786

:

Alex: there's, but there's absolutely

something that makes surely a,

787

:

I mean, you can talk to Shirley

about anything that you want and,

788

:

you know, there's totally the.

789

:

you know, surely we'll try to

bring you back into the light.

790

:

That's that's really, truly just kind

of wants to fly with you and maybe not

791

:

that you can see some of the videos

that creators make and they try to push

792

:

Charlotte in a different direction.

793

:

The trouble is like, maybe you want

to fly because that could make you

794

:

feel better and, and trying to kind

of get away from like something.

795

:

But, um, so, know, um, that's kind

of my philosophical point on that,

796

:

you know, And we're not, you know,

797

:

Bill: You're not against it.

798

:

You're not against using the

term, but you're also not

799

:

defining the product as just AI.

800

:

Is that fair?

801

:

Alex: Right.

802

:

It surely is your, yeah.

803

:

I mean, we say it's on our poster.

804

:

I mean, surely it's your

AI co pilot from Sim to

805

:

Bill: Okay.

806

:

All right.

807

:

Alex: so, you know, You know,

we're providing a service

808

:

where surely it can be your co

809

:

Bill: Perfect.

810

:

Well,

811

:

Alex: say something like

it's, you know, it's Shirley.

812

:

Bill: this is the definitive

test on if it's AI.

813

:

Do you use Lisp anywhere

in your, in your product?

814

:

Alex: So,

815

:

Bill: I couldn't resist.

816

:

Like I said, I'm an old guy.

817

:

So,

818

:

Alex: written,

819

:

I have written programming languages

and compilers and I programmed

820

:

in a language called Haskell

821

:

Bill: yes.

822

:

Yeah.

823

:

Yeah.

824

:

Alex: nope, we're not, we're not using

825

:

Bill: That, that was a joke.

826

:

I did program in list points, but

it was, but it was in college.

827

:

So that was a long time ago.

828

:

Alex: We're trying to be a successful

829

:

Bill: Yeah.

830

:

Right.

831

:

Right.

832

:

Alex: So

833

:

Bill: All right.

834

:

I couldn't resist.

835

:

So a serious question though,

how much, how much of your model

836

:

is running on the edge and how

much is, um, bound to the cloud?

837

:

And how are you, how

are you navigating that?

838

:

I mean, it's a, it's a tough balance.

839

:

Alex: Yeah.

840

:

So some of the things that are

really interesting about that.

841

:

So right now, you know, the quickest way

to start a company is to, is to use all

842

:

cloud services in this space for sure.

843

:

Right now, you know, what we're,

what we're doing is we are sort

844

:

of setting ourselves up to be able

to progressively run things more.

845

:

Offline and sort of what we're beginning

with that is to build a system that,

846

:

know, kind of encourages surely to be a

little bit more judicious about replying.

847

:

You know, 1 of the interesting things

about these sort of large models, you look

848

:

at either, you know, if you go to tattoo,

you go to claw or something like that.

849

:

you ask a question, it's always

going to reply to something.

850

:

And if you say, let's simulate a

conversation and you say, okay, thanks.

851

:

And it says, you know, see ya.

852

:

And you say bye.

853

:

And then it says And then you say, okay.

854

:

And it says, all right, let

me know if you have a state.

855

:

And so like, you know,

that can be sort of a mess.

856

:

And

857

:

Bill: It's like saying goodbye to

your significant other in high school.

858

:

Tiffany: You hang up.

859

:

Bill: Takes all night.

860

:

No, you hang up.

861

:

No, you hang up.

862

:

Alex: Shirley.

863

:

No, you hang up, Shirley.

864

:

Enjoy your flight.

865

:

I am.

866

:

Yeah.

867

:

Great.

868

:

And so, you know, that's, that's

something that, you know, you watch

869

:

them, some videos, you know, there's a.

870

:

Wonderful channel, virtual aviation

aviator, uh, Frank's providing a

871

:

ton of sort of feedback to us and

just, you know, watching his videos.

872

:

Of course, you learn that things that can

be a little bit challenging, like surely

873

:

being over ambitious about replying.

874

:

And so, you know, the 1st,

kind of the 1st sort of.

875

:

Segment for building things that go more

towards the edge are sort of models that

876

:

sort of tell us whether or not she needs

to reply or not, and things like that.

877

:

And so, and when and things like that.

878

:

And so, you know, start with that.

879

:

And then, you know, of course, the

model, which is going to run on on the

880

:

iPhone is going to run entirely offline.

881

:

So so that's really good.

882

:

But I think what's What's neat is

the, the amount of progress that these

883

:

sort of sort of hosted cloud models

have been making is just phenomenal.

884

:

I mean, right now you can almost, uh,

you know, right now, surely can totally

885

:

comprehend these sort of data graphs that

we're, that we're providing and there's

886

:

sort of charts and things like that.

887

:

And, you know, all sorts of

things you find in the AFD that.

888

:

Just by looking at them, you know,

there could be some sort of evidence.

889

:

So, you know, there's lots of real

benefits to using things that exist on,

890

:

on the cloud, as well as they have really

well defined sort of, you know, they are

891

:

respecting the rights of, you know, users,

et cetera, related to privacy and not,

892

:

not necessarily training on their data.

893

:

So we could kind of do it in a very

judicious way where, you know, um, you

894

:

know, where we're, where we are, of

course, we're collecting some of the

895

:

text of the conversations, but before we.

896

:

Do anything with it, you

know, we're we're, yeah.

897

:

Anonymizing it

898

:

Bill: Yeah.

899

:

Alex: and you know, sort of hitting

it with the past to make sure

900

:

there's nothing, wild in there.

901

:

If we kind of encourage users not

to share social security numbers

902

:

and things like that, Shirley, but

you know, just 'cause it did then

903

:

sort of hit it, hit it with that and

we'll, we'll also, we're still early.

904

:

They both figure, figure out a way

of letting people sort of opt out.

905

:

But I think

906

:

Bill: Right.

907

:

Alex: is something that people

will hopefully opt, to opt into.

908

:

'cause we're looking

to be able to provide.

909

:

Sort of training, they were

training, but also surely in flight

910

:

Bill: Yeah, yeah, yeah.

911

:

Alex: to do that is by being able to

use some of these conversations and make

912

:

something that's really small behave a lot

913

:

Bill: Right.

914

:

I mean, these are all kind of typical

challenges that you have around AI and,

915

:

and large language model learning, right?

916

:

Um, so has latency proven to be

somewhat of a, uh, an issue that

917

:

you're dealing with in your product?

918

:

Or are you finding that it's not a, it's

as big a challenge as maybe it would seem?

919

:

Alex: latency has been so it's

a little bit longer when an

920

:

image is in the conversation.

921

:

You know, then it can start

to feel like, you know, you're

922

:

waiting for a second or something

923

:

Bill: Mm hmm.

924

:

Alex: but our current latency is something

along the line of is less than a second.

925

:

It's like, you know,

600, 800 milliseconds.

926

:

it ends up being pretty fast.

927

:

In fact, you know, one of the, one

of the issues and the reason why

928

:

we're focusing on building something

that tells Shirley when to not reply

929

:

Bill: hmm.

930

:

Alex: is, is that latency is so low.

931

:

And so, you know, it ends up being a

932

:

Bill: Yeah,

933

:

Alex: very conversational

sort of interaction.

934

:

In fact, the videos that I sent her,

935

:

Bill: yeah.

936

:

Alex: on, on doctor, there was

no time warping in them and,

937

:

and, or anything like that.

938

:

And so.

939

:

You know, I think people are very, you

know, very pleased with the latency.

940

:

But, you know, there are, there

are issues where it's a little too

941

:

low and so, you know, so, you know,

interjecting at the wrong times, you

942

:

know, things interrupting or things

that shouldn't be happening like that.

943

:

And so we're, we're focusing on, you

know, fixing those issues without.

944

:

Making latency too much, although

those might increase the latency

945

:

temporarily while we sort of

figure out how to do that better.

946

:

So this sort of thing is kind of

bread and butter, but you know, it's,

947

:

it's an important aspect of making

a copilot that actually feels like a

948

:

copilot as opposed to somebody who's

the high school, as you say, the high

949

:

school kind of lover saying goodbye at

every time you're having an exchange.

950

:

Tiffany: When you're planning

On making the version for,

951

:

uh, actually being in flight.

952

:

We'll, we'll surely be

listening to the radio as well.

953

:

Will that be the helper that says,

Hey, I think they called your,

954

:

called you and you didn't reply.

955

:

How's that working?

956

:

Alex: So, you know, you could see it

with some of the existing companies.

957

:

In fact, that's, you know, there

are some very good examples of

958

:

companies that are providing that

you can talk to via bluetooth you're

959

:

while you're flying and they can

listen to you while you're flying.

960

:

The challenge is if you also

want to listen to the intercom,

961

:

so you have to start to have

adapters and things like that.

962

:

And as a software company, you don't

want to get into really the business of

963

:

building adapters or things like that.

964

:

You want to use sort of off the shelf

adapters and And so, you know, there

965

:

are some sort of hiccups to doing that.

966

:

However, you know, I've talked

to some avionics makers.

967

:

very interested in being able to provide

high quality transcriptions of things that

968

:

are happening, you know, over the radio.

969

:

And so one of the hopes that we

have is also through our process of.

970

:

to develop surely that we can provide

something maybe to some avionics makers

971

:

that would allow them to better do the

2 stage sort of process of 1st speech

972

:

to text and then sort of like a kind

of a rough, like an overview pass and

973

:

editorial pass of, you know, turning

that don't make sense in certain

974

:

places and the things that make sense.

975

:

so, you know, if we could sort of provide

that along the sort of along the way,

976

:

I'll provide a lot of value to people

being able to just sort of see whether or

977

:

not something was for you or maybe being

able to incorporate a, a directive into

978

:

your FMS directly or something like that.

979

:

So there could be a lot of value there

980

:

Bill: Yeah, that first step is to

digitize it, um, and then you can start

981

:

analyzing it, but I guess taking that

first step is where you're at right now.

982

:

Alex: right.

983

:

Bill: so how, how does the, uh,

intelligence model, uh, behind

984

:

Shirley specifics about the POH for

your airplane, for, for example?

985

:

how does it, how do you teach Shirley?

986

:

or how will you in the future, um, so that

it's getting the right version of the POH.

987

:

You can't just get this

generically off the internet.

988

:

It has to be for your

serial number, right?

989

:

It has to be for any number of things.

990

:

And I've got a follow up question

on other data as well that it needs.

991

:

So go ahead.

992

:

Alex: absolutely.

993

:

No, that's that's great.

994

:

So if we're talking about the version.

995

:

Of so if you're working with like a

flight school and you're trying to give

996

:

representative training to you know,

the students at the flight school,

997

:

or if you're working with providing a

version of an app that then pilots fly

998

:

with, you have to get the right numbers

just sort of, you know, make something

999

:

up that, you know, I heard on the

:

00:52:45,239 --> 00:52:48,039

Bill: It can't be a chat

GPT type answer, right?

:

00:52:48,069 --> 00:52:49,269

That's, that's what I'm getting at.

:

00:52:49,339 --> 00:52:49,859

Alex: right.

:

00:52:49,859 --> 00:52:50,759

Yeah, exactly.

:

00:52:50,899 --> 00:52:51,689

Exactly.

:

00:52:51,689 --> 00:52:51,909

Right.

:

00:52:52,269 --> 00:52:55,139

Even though those sorts of

answers end up being quite

:

00:52:55,189 --> 00:52:56,679

good at sort of a generic case,

:

00:52:56,789 --> 00:52:57,169

Bill: Yes.

:

00:52:57,409 --> 00:53:00,219

Alex: down like we do, and surely

we're just like, oh, you're flying

:

00:53:00,219 --> 00:53:03,019

a 172, you're like, okay, 172.

:

00:53:03,369 --> 00:53:05,629

Okay, well, it'll be about this, right?

:

00:53:05,969 --> 00:53:10,309

So the process that we'll do

is to have a place where people

:

00:53:10,309 --> 00:53:12,679

can ingest their own checklist,

:

00:53:12,929 --> 00:53:13,409

Bill: Perfect.

:

00:53:13,969 --> 00:53:14,959

Alex: sort of the POH.

:

00:53:15,049 --> 00:53:19,219

We'll have a system that allows somebody

just to drop the PDF, of, you know, do

:

00:53:19,219 --> 00:53:20,859

a first pass, sort of digitizing that.

:

00:53:21,649 --> 00:53:22,769

something, clean it up for them.

:

00:53:22,949 --> 00:53:25,879

You're like, here's the sort of

information that will appear.

:

00:53:25,879 --> 00:53:28,109

If you ask questions, it'll be from here.

:

00:53:28,739 --> 00:53:31,189

there's a lot of processes that you

can follow in order to make sure that

:

00:53:31,189 --> 00:53:33,859

you're getting the right of data.

:

00:53:33,979 --> 00:53:39,659

So one of those is, you know, tell the

system to not actually give them, give

:

00:53:39,659 --> 00:53:43,579

a number because it can just make up a

number instead, it'll give sort of the.

:

00:53:43,929 --> 00:53:50,189

Sort of index the place inside, like the

section number where that number is found.

:

00:53:50,604 --> 00:53:54,624

And you sort of like, you know, label

that number inside of the POH somewhere.

:

00:53:54,984 --> 00:53:58,464

And so you just, it outputs the

index and then you, before you speak

:

00:53:58,464 --> 00:54:02,044

anything, you go and you grab that

information from the actual book.

:

00:54:02,424 --> 00:54:06,414

And then, so you can kind of

make sure that things are, you

:

00:54:06,414 --> 00:54:08,154

know, working appropriately.

:

00:54:08,154 --> 00:54:14,404

And so this is the absolute stuff that

needs to be done prior to shipping in the

:

00:54:14,854 --> 00:54:15,144

Bill: Yep.

:

00:54:15,374 --> 00:54:15,704

Yep.

:

00:54:15,774 --> 00:54:18,324

Alex: precisely, but also very

important to flight schools.

:

00:54:18,719 --> 00:54:22,489

Before that ends up, you know,

know, shipping out for them, but for

:

00:54:22,489 --> 00:54:26,599

sure, it's very important, you know,

before getting into the cockpit,

:

00:54:26,959 --> 00:54:30,659

one of the things that will also be

implementing is, you know, feedback.

:

00:54:30,659 --> 00:54:35,319

So somebody has a problem with the

number, they're surprised by something

:

00:54:35,799 --> 00:54:40,109

is important to be able to capture that

and be able to be able to essentially.

:

00:54:41,134 --> 00:54:44,494

Incorporate that and say, okay, maybe we

should take a look at how this performed.

:

00:54:45,574 --> 00:54:47,894

you know, feedback in sort of human

:

00:54:48,094 --> 00:54:48,394

Bill: Yeah.

:

00:54:48,394 --> 00:54:49,944

And maybe

:

00:54:50,034 --> 00:54:50,364

Alex: good,

:

00:54:50,534 --> 00:54:55,014

Bill: a safe word, um, when

she's leading you astray, right?

:

00:54:55,024 --> 00:54:56,774

Like, okay, leave me alone for a while.

:

00:54:59,194 --> 00:55:00,774

Alex: The safe word in flyshirley.

:

00:55:01,084 --> 00:55:04,394

com right now is by all

means, definitely mute.

:

00:55:04,774 --> 00:55:05,314

Bill: Oh, okay.

:

00:55:05,384 --> 00:55:05,844

Perfect.

:

00:55:06,124 --> 00:55:06,904

Alex: is the safe word here.

:

00:55:08,944 --> 00:55:09,484

Bill: Excellent.

:

00:55:09,774 --> 00:55:10,054

Okay.

:

00:55:10,054 --> 00:55:15,339

So my related question then is what

about, What about future integration?

:

00:55:15,349 --> 00:55:19,469

Maybe you have it now, but I'm guessing

future integration with other real time

:

00:55:19,469 --> 00:55:26,629

data that might prove handy to assimilate

into answers and so on, like ADS B data,

:

00:55:27,019 --> 00:55:33,359

GPS data, um, data that's coming from

ForeFlight or, you know, things like that.

:

00:55:34,369 --> 00:55:36,049

Kind of, how are you

taking that into account?

:

00:55:38,349 --> 00:55:38,809

Alex: Right.

:

00:55:38,819 --> 00:55:43,679

And so we're starting by using this

really convenient interface that explained

:

00:55:43,679 --> 00:55:45,299

just launched called the web socket

:

00:55:45,669 --> 00:55:45,909

Bill: Mm hmm.

:

00:55:45,909 --> 00:55:46,819

Mm

:

00:55:46,899 --> 00:55:48,889

Alex: not have to install a

plugin in order to be able

:

00:55:48,889 --> 00:55:50,049

to have data go to Shirley.

:

00:55:50,699 --> 00:55:52,439

And so that's been really very convenient.

:

00:55:53,239 --> 00:55:56,609

We're looking at releasing

an app version of Shirley.

:

00:55:56,609 --> 00:56:00,099

You know, there are other, there

are other sort of platforms that

:

00:56:00,099 --> 00:56:01,549

provide these sort of data streams.

:

00:56:01,559 --> 00:56:05,619

So ADS B is a good example, but

you can have a data stream from

:

00:56:05,629 --> 00:56:07,059

infinite flight, which is the iPad

:

00:56:07,199 --> 00:56:07,559

Bill: hmm.

:

00:56:07,859 --> 00:56:08,169

Alex: in.

:

00:56:09,239 --> 00:56:14,069

Sort of one of the leaders there, you

know, you can incorporate surely that way.

:

00:56:14,069 --> 00:56:20,929

Of course, in the cockpit, you can have a

have the GPS from the sky onto your phone.

:

00:56:20,929 --> 00:56:23,449

But of course, you and

the altimeter actually.

:

00:56:23,449 --> 00:56:27,619

Now there's also altimeters

built into into phones.

:

00:56:27,739 --> 00:56:29,999

Believe it or not, there's

barometric sensors.

:

00:56:30,934 --> 00:56:34,234

But yes, the ADS B that comes

in has a lot more reliable data.

:

00:56:34,234 --> 00:56:34,914

You should use that.

:

00:56:35,244 --> 00:56:37,884

One of the things that we've been

focusing on as well, and one of the

:

00:56:37,904 --> 00:56:42,864

reasons why we are sort of doing

this sort of data process is that, so

:

00:56:42,874 --> 00:56:46,334

that surely will pay more attention

to the particular aviation context.

:

00:56:46,334 --> 00:56:50,794

And so one of the things that we've

noticed is that existing really big sort

:

00:56:50,794 --> 00:56:54,774

of language models are not very good at

paying attention to the state of flight.

:

00:56:55,124 --> 00:56:59,979

And so even though you might have

information related to, of your altitude

:

00:56:59,979 --> 00:57:05,469

and your descent rate and, you know, your

bank angle and things like this, you know,

:

00:57:05,839 --> 00:57:11,209

the system might not fully be appreciating

the fact that you're about to land or

:

00:57:11,209 --> 00:57:15,529

you already have landed and instead

relying more on the story to think about.

:

00:57:15,879 --> 00:57:16,209

Bill: Mm hmm.

:

00:57:16,374 --> 00:57:17,204

Alex: you've landed or not.

:

00:57:17,424 --> 00:57:22,054

And so part of that is that these

sort of models like to reason,

:

00:57:22,524 --> 00:57:25,574

sometimes you reason best by doing

this kind of chain of thought thing.

:

00:57:25,674 --> 00:57:29,114

It's like, you know, you could tell

it this, you could say something

:

00:57:29,114 --> 00:57:34,294

like, okay, surely using the

information, the information that

:

00:57:34,294 --> 00:57:39,124

you see related to altitude and

rate of descent, what would you say?

:

00:57:39,154 --> 00:57:41,404

We're in the herd phase of flight.

:

00:57:41,404 --> 00:57:42,984

And then it could say

something along the lines of.

:

00:57:43,414 --> 00:57:45,074

Descent rate is 500 feet per minute.

:

00:57:45,214 --> 00:57:47,614

You know, altitude is 500 feet AGL.

:

00:57:48,044 --> 00:57:48,834

We're about to land.

:

00:57:49,894 --> 00:57:54,714

And, you know, what is really important

is to be able to skip those steps and just

:

00:57:54,714 --> 00:57:56,124

for sure, to be able to understand that

:

00:57:56,259 --> 00:57:56,679

Bill: Yeah.

:

00:57:56,694 --> 00:57:57,284

Alex: about to land.

:

00:57:57,359 --> 00:57:57,599

Bill: Just

:

00:57:57,834 --> 00:58:00,474

Alex: And so bigger and

better and badder models

:

00:58:00,529 --> 00:58:01,619

Bill: Yeah, right.

:

00:58:01,634 --> 00:58:06,694

Alex: able to appreciate those factors,

but also by tuning the models using

:

00:58:06,694 --> 00:58:09,274

that sort of information, you're

able to skip those steps and how

:

00:58:09,359 --> 00:58:09,659

Bill: Yeah.

:

00:58:09,854 --> 00:58:10,914

Alex: attention to the particulars.

:

00:58:11,089 --> 00:58:11,929

Bill: we've, we've got,

:

00:58:12,034 --> 00:58:13,184

Alex: opportunities to do this.

:

00:58:14,019 --> 00:58:14,639

Bill: sorry, go ahead.

:

00:58:16,359 --> 00:58:16,689

Yeah.

:

00:58:16,704 --> 00:58:19,894

Alex: Well, there's other opportunities

also to do things called multimodal

:

00:58:19,954 --> 00:58:23,884

models for, you know, essentially

1 channel is the flight data,

:

00:58:23,919 --> 00:58:24,359

Bill: Mm hmm.

:

00:58:24,484 --> 00:58:26,364

Alex: then the other

channels are the speech.

:

00:58:26,734 --> 00:58:30,154

And, you know, you could have

two different channels feeding

:

00:58:30,154 --> 00:58:31,464

the model so that it all points.

:

00:58:31,464 --> 00:58:35,654

It has some concept of, you know, your

state of flight that it's generating

:

00:58:36,144 --> 00:58:38,224

and also some concept of the story and

:

00:58:38,319 --> 00:58:38,759

Bill: Right.

:

00:58:38,929 --> 00:58:40,749

And that's kind of what I had in my mind.

:

00:58:40,774 --> 00:58:42,024

Alex: it into text land too.

:

00:58:42,049 --> 00:58:42,439

Bill: Right.

:

00:58:42,449 --> 00:58:44,939

And that's sort of what I had in

my mind, because we have the, we

:

00:58:44,939 --> 00:58:48,209

have access to these relatively

inexpensive adhars and things like

:

00:58:48,209 --> 00:58:50,119

that, like in the century, right?

:

00:58:50,529 --> 00:58:55,249

So it, that's kind of, is that

kind of part of your roadmap is

:

00:58:55,249 --> 00:58:57,049

to have that multimodal approach.

:

00:58:58,904 --> 00:59:02,184

Alex: and that's 1 of the cool

reasons for starting with Sims 2

:

00:59:02,284 --> 00:59:03,414

is because they have all that same

:

00:59:03,639 --> 00:59:03,999

Bill: Got it.

:

00:59:04,129 --> 00:59:05,959

Alex: You're just getting

it streamed from the flight

:

00:59:05,989 --> 00:59:06,559

Bill: Exactly.

:

00:59:06,659 --> 00:59:09,939

Alex: could absolutely trade to pay

attention to this thing, especially

:

00:59:09,939 --> 00:59:12,659

for a smaller model, which would

have a lot more trouble paying

:

00:59:12,659 --> 00:59:16,349

attention to the correct things

without tons of prompting, et cetera.

:

00:59:16,699 --> 00:59:20,709

And so being able to provide that

sort of these sort of pairs and being

:

00:59:20,709 --> 00:59:23,539

able to train these certain models to

pay attention to their phase of life.

:

00:59:23,599 --> 00:59:24,959

That's a, that's a huge

:

00:59:25,089 --> 00:59:25,979

Bill: It's very interesting.

:

00:59:25,989 --> 00:59:26,849

And you mentioned,

:

00:59:26,849 --> 00:59:27,219

Alex: question.

:

00:59:27,289 --> 00:59:29,859

Bill: you mentioned these massive

models that, you know, they're going to

:

00:59:29,859 --> 00:59:31,759

get supermodels and things like that.

:

00:59:33,109 --> 00:59:35,959

not the way I thought about

those supermodels in high school.

:

00:59:35,959 --> 00:59:36,419

It's different.

:

00:59:36,819 --> 00:59:41,069

But, um, so I thought

you'd like that, Tiffany.

:

00:59:41,069 --> 00:59:43,159

Okay.

:

00:59:43,159 --> 00:59:49,039

Um, so, so my question then is,

I think you're iOS only, right?

:

00:59:49,479 --> 00:59:49,889

Today?

:

00:59:51,279 --> 00:59:52,889

Alex: So right now we're X Plane

:

00:59:53,089 --> 00:59:54,429

Bill: Uh, explain only.

:

00:59:54,499 --> 00:59:54,849

Okay.

:

00:59:55,259 --> 00:59:56,359

Alex: and so we're, so we're

:

00:59:56,464 --> 00:59:57,204

Bill: Running in the browser.

:

00:59:57,204 --> 00:59:57,444

Okay.

:

00:59:57,444 --> 00:59:57,804

Thank you.

:

00:59:57,804 --> 00:59:58,164

Thank you.

:

00:59:59,704 --> 01:00:04,234

so you're probably thinking about how this

will, um, run in the cockpit and so on.

:

01:00:04,484 --> 01:00:09,894

And so I'm wondering how important

the, the differences that you're seeing

:

01:00:09,894 --> 01:00:17,774

between, you know, the A chips in, in

a, in an iPhone versus now, you know,

:

01:00:17,774 --> 01:00:20,164

most of the iPads are getting M chips.

:

01:00:20,484 --> 01:00:25,354

How important is that to you to be

able to do this edge processing?

:

01:00:26,194 --> 01:00:30,004

as you go forward, is that going

to be a big deal for you like

:

01:00:30,074 --> 01:00:35,514

you're you'll be able to fork

your or or change your application

:

01:00:35,524 --> 01:00:37,014

based on the power that it has.

:

01:00:37,014 --> 01:00:40,694

If it's running on an iPad that has

an M four in it, it's going to be

:

01:00:40,694 --> 01:00:43,844

able to do different things than

if it's running on a phone with

:

01:00:43,844 --> 01:00:45,974

an alpha chip with an H up, right?

:

01:00:46,449 --> 01:00:46,819

Alex: Right.

:

01:00:46,849 --> 01:00:49,359

No, I think that's, I think

it's massively, I think

:

01:00:49,359 --> 01:00:50,229

it's massively important.

:

01:00:50,229 --> 01:00:54,879

In fact, this is only the first year

where you might have a mobile phone,

:

01:00:54,889 --> 01:00:59,649

which is powerful enough in order to

be able to run an AI model on it at

:

01:00:59,894 --> 01:01:00,444

Bill: Right.

:

01:01:00,449 --> 01:01:04,699

Alex: And so, you know, the iPhone

pros that exist right now can run AI

:

01:01:04,889 --> 01:01:07,489

models that, you know, my iPad here.

:

01:01:08,294 --> 01:01:10,714

Can can run, you know, the,

the, there's two aspects.

:

01:01:10,714 --> 01:01:13,344

One of them has been just sort of

making models a lot more efficient

:

01:01:13,604 --> 01:01:14,514

Bill: Mm hmm.

:

01:01:14,524 --> 01:01:16,064

Alex: packing more

punch into these models.

:

01:01:16,074 --> 01:01:20,314

So a really good one is one of the

smaller sort of these Facebook created

:

01:01:20,314 --> 01:01:24,504

a medic rated as models called the llama

series of models that are open source.

:

01:01:24,534 --> 01:01:28,094

And so you can essentially, you

know, start to think about bringing

:

01:01:28,094 --> 01:01:30,214

some of those things to mobile and.

:

01:01:30,574 --> 01:01:34,574

You know, the, the opportunity

there is, is massive.

:

01:01:34,634 --> 01:01:37,484

So you can run some of these

models already on iPads.

:

01:01:37,664 --> 01:01:41,764

The of historical ones

are really not that smart.

:

01:01:42,254 --> 01:01:46,964

It kind of and confabulate is really the

kind of the term of art related to that.

:

01:01:47,444 --> 01:01:51,664

And then the ones that you can

now run on the iPhone will have

:

01:01:51,664 --> 01:01:54,859

to be sort of tuned by us and with

the sort of data that we have.

:

01:01:55,299 --> 01:01:58,389

That we collect in order to

be smart for the task, be able

:

01:01:58,389 --> 01:01:59,689

to be relevant for the task.

:

01:01:59,839 --> 01:02:02,309

And, you know, the idea is

to be able to upgrade when

:

01:02:02,309 --> 01:02:03,409

somebody has internet connection,

:

01:02:03,574 --> 01:02:04,434

Bill: Right, right.

:

01:02:04,479 --> 01:02:05,669

Alex: is really the fundamental.

:

01:02:06,059 --> 01:02:09,439

And there's different ways of looking

at how to get internet connection.

:

01:02:09,739 --> 01:02:09,919

And

:

01:02:10,184 --> 01:02:11,754

Bill: And presumably it.

:

01:02:12,019 --> 01:02:12,449

Alex: around,

:

01:02:12,559 --> 01:02:15,769

Bill: send learning data as well,

once they have a connection.

:

01:02:16,339 --> 01:02:19,839

Um, I'm guessing, so it's

not only going to enhance the

:

01:02:20,099 --> 01:02:20,939

Alex: to, it's important.

:

01:02:21,129 --> 01:02:21,479

Bill: Go ahead.

:

01:02:21,739 --> 01:02:22,809

Sorry, we got a little lag.

:

01:02:23,484 --> 01:02:25,174

Alex: It's important to have feedback.

:

01:02:25,304 --> 01:02:25,734

It's important to have.

:

01:02:25,984 --> 01:02:26,824

No, that's all right.

:

01:02:27,264 --> 01:02:30,413

It's important to have feedback

on whether or not what somebody

:

01:02:30,614 --> 01:02:32,814

experienced was was good or not.

:

01:02:33,484 --> 01:02:37,704

And so, you know, of course, you

don't want to be exfiltrating

:

01:02:38,824 --> 01:02:40,574

all sorts of data while you're in

:

01:02:40,788 --> 01:02:41,179

Bill: Right.

:

01:02:41,284 --> 01:02:44,614

Alex: know, in fact, that's a

lot of what the SIM community

:

01:02:44,614 --> 01:02:45,929

is for, is to be able to Yeah.

:

01:02:46,229 --> 01:02:50,599

Be able to, to be able to try out some

of these things and, you know, be able

:

01:02:50,599 --> 01:02:52,249

to ensure that these things are safe.

:

01:02:52,249 --> 01:02:56,199

And so I think when I think about flight

data, I'm a lot more kind of, know,

:

01:02:56,209 --> 01:03:00,729

a little bit more hesitant to think

about kind of like kind of sucking

:

01:03:00,729 --> 01:03:04,509

that data off the phone, especially if

it's all running on somebody's phone

:

01:03:04,509 --> 01:03:05,969

and without having to use anything on

:

01:03:06,159 --> 01:03:06,519

Bill: Yeah.

:

01:03:06,529 --> 01:03:07,609

Alex: on the cloud at all.

:

01:03:07,609 --> 01:03:10,969

And, you know, but it is important to

have some sort of feedback mechanism.

:

01:03:10,969 --> 01:03:15,429

So that really has to be tread

very kind of lightly, you know.

:

01:03:15,909 --> 01:03:18,619

You know, I ultimately think about how

to provide these sort of technologies

:

01:03:18,619 --> 01:03:22,089

to, you know, airlines, you know,

pilots unions, nobody wants to be able

:

01:03:22,089 --> 01:03:25,929

to have that, like, listening to them

and their livelihood is on the line.

:

01:03:25,959 --> 01:03:27,769

It just, you know, it's

:

01:03:27,899 --> 01:03:29,779

Bill: Yeah, you guys,

you guys have a lot of

:

01:03:29,879 --> 01:03:30,109

Alex: So,

:

01:03:30,489 --> 01:03:33,369

Bill: CS questions ahead of

you to answer, don't you?

:

01:03:33,369 --> 01:03:36,629

Heh heh heh heh.

:

01:03:36,829 --> 01:03:37,429

Alex: really fun

:

01:03:37,569 --> 01:03:37,929

Bill: Yeah.

:

01:03:38,089 --> 01:03:38,489

Alex: like.

:

01:03:38,949 --> 01:03:44,229

A combination somehow now, as a, as

a grown up now, I get to say that I'm

:

01:03:44,229 --> 01:03:49,259

combining a lot of interest for the

aviation with computer science you

:

01:03:49,269 --> 01:03:52,159

know, if there's other people out there

that are see this as an interesting

:

01:03:52,159 --> 01:03:53,479

opportunity, they should reach out,

:

01:03:53,774 --> 01:03:54,064

Bill: We're,

:

01:03:54,659 --> 01:03:55,579

Alex: if they're on these

:

01:03:55,663 --> 01:03:58,394

Bill: we're really in front of

that hockey stick curve, aren't we?

:

01:03:58,394 --> 01:04:00,674

I mean, we're just in the

infancy of all of this.

:

01:04:02,649 --> 01:04:05,739

Alex: I think that's what makes it

such a fun time to be building things.

:

01:04:05,788 --> 01:04:09,969

And, you know, our favorite thing is to

be able to work with customers directly.

:

01:04:10,219 --> 01:04:13,729

And so, No, we have our discord

channel where it's really

:

01:04:13,949 --> 01:04:15,719

exciting to see people chime in.

:

01:04:15,729 --> 01:04:18,609

It's airplane dot team slash

discord if you want to get on

:

01:04:18,764 --> 01:04:19,134

Bill: All right.

:

01:04:19,259 --> 01:04:25,249

Alex: but the, the people who join, you

know, we end up interacting and, and, and,

:

01:04:25,659 --> 01:04:28,519

you know, sometimes they're willing to hop

on a phone call and give us some feedback.

:

01:04:28,699 --> 01:04:32,409

Sometimes they're posting YouTube

videos about things and, you know, that

:

01:04:32,409 --> 01:04:35,524

they experienced a Shirley, you know,

flights through New York or, you know,

:

01:04:35,674 --> 01:04:39,184

Different experiences were surely or

kind of funny videos for, you know,

:

01:04:39,184 --> 01:04:43,064

sinfluencers, which I think is an awesome

subcategory of the internet influencers.

:

01:04:43,454 --> 01:04:43,894

It's amazing.

:

01:04:44,294 --> 01:04:46,974

And so, so we learned so much from that.

:

01:04:46,974 --> 01:04:50,854

And I think there's just the enthusiasm

in this space to see people really

:

01:04:50,854 --> 01:04:53,744

enjoying using their sins and

seeing what's possible in sense.

:

01:04:53,774 --> 01:04:56,784

I mean, there's a lot of really

interesting companies that are, that

:

01:04:56,784 --> 01:05:03,919

are shipping things for For, for Sims

now, you know, you have like the ATC

:

01:05:03,919 --> 01:05:09,489

land and you have sort of, you know,

same tensions and beyond ATC, P2ATC,

:

01:05:09,489 --> 01:05:12,589

which are using all this AI stuff to

be able to enable really good ATC.

:

01:05:12,589 --> 01:05:14,839

You know, it's, it's.

:

01:05:15,609 --> 01:05:19,079

amazing time to be kind of building

and also being a flight simmer.

:

01:05:19,549 --> 01:05:23,399

And, and so, yeah, it just

couldn't be, couldn't be any more

:

01:05:23,399 --> 01:05:24,659

fun if I could think about it.

:

01:05:27,634 --> 01:05:27,964

Bill: All right.

:

01:05:27,964 --> 01:05:32,484

Well, I, I've, um, exhausted the,

the geek out portion on the product.

:

01:05:32,484 --> 01:05:35,984

So I'm going to, um, I'm going to give

Tiffany a chance to ask some of her

:

01:05:35,984 --> 01:05:37,864

pent up questions that I know she's got.

:

01:05:38,244 --> 01:05:41,284

And then I want to really

kind of geek out on the, uh,

:

01:05:41,314 --> 01:05:43,694

aviation learning side of this.

:

01:05:43,694 --> 01:05:45,194

I've got some questions about that too.

:

01:05:45,194 --> 01:05:46,194

So go ahead,

:

01:05:46,435 --> 01:05:48,120

Tiffany: I think all my

questions were answered.

:

01:05:48,619 --> 01:05:49,349

Bill: Oh, good.

:

01:05:49,538 --> 01:05:49,949

All right.

:

01:05:51,049 --> 01:05:51,399

All right.

:

01:05:51,399 --> 01:05:54,139

Well, um, got a few then.

:

01:05:54,259 --> 01:06:00,189

Um, we've talked a little bit

about how, uh, Shirley could be

:

01:06:00,189 --> 01:06:01,869

used in the training environment.

:

01:06:02,269 --> 01:06:07,609

I would love to hear your thoughts go a

little bit deeper into how Shirley would

:

01:06:07,619 --> 01:06:14,529

integrate, uh, and I mean this in a non

technical way, but integrate with a human

:

01:06:14,529 --> 01:06:16,244

CFI to augment the training environment.

:

01:06:16,564 --> 01:06:21,694

Uh, and enhance what they're doing with

a, with a student or with a, a client

:

01:06:21,704 --> 01:06:23,614

who's doing some advanced training,

:

01:06:25,909 --> 01:06:27,419

Alex: Yeah, that's a great question.

:

01:06:28,239 --> 01:06:33,288

so we see, just to be clear again and

reiterate, like, we see Shirley as being

:

01:06:33,288 --> 01:06:35,649

a supplement to professional instruction.

:

01:06:36,029 --> 01:06:42,719

You know, there's a portion of, uh,

practice that surely can provide a lot of

:

01:06:42,729 --> 01:06:47,769

value and it's actually pretty good, but,

you know, there are so many conceptual

:

01:06:47,779 --> 01:06:50,899

things that only a really a human can

:

01:06:50,954 --> 01:06:51,224

Bill: Yeah.

:

01:06:51,299 --> 01:06:51,659

Alex: can see.

:

01:06:51,659 --> 01:06:55,038

And plus, there'll be things that

surely does miss and, and, and.

:

01:06:55,339 --> 01:06:59,809

There'll be opportunities to

to enhance sort of, you know,

:

01:07:00,239 --> 01:07:02,119

some of the some of the style.

:

01:07:02,119 --> 01:07:07,479

And if the, you know, are also unknown

unknowns related to some aspects of

:

01:07:07,479 --> 01:07:11,059

this of this training, but, you know,

what is really valuable about it is

:

01:07:11,059 --> 01:07:14,709

being able to show up prepared for

your lesson and to be able to do fine.

:

01:07:14,709 --> 01:07:15,379

You know, you're.

:

01:07:15,809 --> 01:07:19,038

You know, you might have missed a week

with your instructor due to weather

:

01:07:19,038 --> 01:07:23,079

or somebody got And now you're like

looking at potentially needing to

:

01:07:23,079 --> 01:07:27,099

repeat a lesson or you just went out

and did some training with an instructor

:

01:07:27,099 --> 01:07:28,449

and you had these deficiencies.

:

01:07:28,449 --> 01:07:32,788

You need sort of this retraining or,

you know, in a, you know, you started

:

01:07:32,788 --> 01:07:38,269

with your PPL, you had these maneuvers,

you know, you were a little bit, you're

:

01:07:38,299 --> 01:07:39,959

kind of bad at terms about a point.

:

01:07:40,279 --> 01:07:43,519

And now you're going to go, you know,

you got your IFR, you're really like

:

01:07:43,519 --> 01:07:45,199

book smart, you got your IFR real easy.

:

01:07:45,674 --> 01:07:47,534

And now you're back in commercial land.

:

01:07:47,534 --> 01:07:51,124

You got, it's on pylons and you're

just like, Oh, goodness gracious.

:

01:07:51,514 --> 01:07:53,114

And you're struggling.

:

01:07:53,114 --> 01:07:59,214

And so, you know, maybe for somebody who

is having an integrated sort of training

:

01:07:59,214 --> 01:08:03,954

program that includes Shirley, then they

could have some sort of knowledge that.

:

01:08:04,349 --> 01:08:09,538

Yes, actually, in PPL time, you were

pretty deficient these sort of areas.

:

01:08:09,609 --> 01:08:12,729

In fact, you might want to actually

put some extra, extra energy into

:

01:08:12,729 --> 01:08:16,349

them before you go out and start

working on these eights on pylons

:

01:08:16,349 --> 01:08:17,828

or between your instrument or,

:

01:08:17,944 --> 01:08:18,234

Bill: Mm.

:

01:08:18,249 --> 01:08:20,379

Alex: know, after you get your

instrument, make out an airplane

:

01:08:20,379 --> 01:08:21,908

or do it or do it in the sim.

:

01:08:22,238 --> 01:08:25,859

And so some level of integration

that you would want to have, you

:

01:08:25,859 --> 01:08:31,658

know, maybe between your, your

four flight pilot sort of logbook.

:

01:08:31,658 --> 01:08:32,339

You know, there's.

:

01:08:32,594 --> 01:08:35,734

Some people who take the

logs real seriously inside

:

01:08:35,734 --> 01:08:37,064

of the electronic log books.

:

01:08:37,274 --> 01:08:42,544

Some people don't take them quite as

seriously as, as the opportunity with

:

01:08:42,554 --> 01:08:46,064

the actual paper log book, because

there's a, there's a flight track and

:

01:08:46,064 --> 01:08:47,448

things like that associated with it.

:

01:08:47,868 --> 01:08:48,828

Electronic logbook.

:

01:08:48,828 --> 01:08:53,698

Sometimes you feel like it might maybe

not be, uh, might not be as but for,

:

01:08:54,049 --> 01:08:57,288

uh, if that data is there, then it

would be really good to be able to grab

:

01:08:57,493 --> 01:08:57,734

Bill: hmm.

:

01:08:57,738 --> 01:09:00,589

Alex: able to provide that to Shirley

as part of your sort of private pilot

:

01:09:00,589 --> 01:09:04,669

sort of preparation and have, you

know, your pilot notes related to,

:

01:09:04,959 --> 01:09:08,269

you know, what did you feel like you

did right and did wrong and what areas

:

01:09:08,269 --> 01:09:10,529

that surely believe that you might

need a little bit of more practice on.

:

01:09:10,849 --> 01:09:13,959

Include those in sort of a logbook that's

integrated between your real flying and

:

01:09:13,959 --> 01:09:18,609

your virtual flying and be able to help

people become a lot more prepared and then

:

01:09:18,658 --> 01:09:22,118

to have, you know, instructors be able

to kind of be able to try this stuff out.

:

01:09:22,118 --> 01:09:26,038

Maybe they already used it themselves,

or maybe they have heard about it and

:

01:09:26,038 --> 01:09:29,448

just think it's maybe worthwhile just

to have, you know, if you're tired at

:

01:09:29,448 --> 01:09:32,828

the end of the day, or like, and you

and what your setup is, if you have like

:

01:09:32,828 --> 01:09:35,979

a yoke and You know, you're a laptop

and now you have to like go to your

:

01:09:35,979 --> 01:09:38,099

desk in order to like plug, plug it in.

:

01:09:38,099 --> 01:09:39,318

It's like, you're kind of tired.

:

01:09:39,639 --> 01:09:41,669

It'd be nice to have

somebody like provide or

:

01:09:41,943 --> 01:09:42,384

Bill: Mm hmm.

:

01:09:42,389 --> 01:09:46,809

Alex: a little bit of extra to get

you, to get you over that sort of line.

:

01:09:46,809 --> 01:09:50,009

And so you sort of show up and

Shirley's like, like, let's go,

:

01:09:50,009 --> 01:09:51,426

you're ready to do blah, blah, blah.

:

01:09:51,426 --> 01:09:56,089

And you're like, all right, like, I'm, I'm

just there enough to be able to practice

:

01:09:56,294 --> 01:09:56,724

Bill: Yeah.

:

01:09:56,724 --> 01:09:58,844

Mm hmm.

:

01:09:58,939 --> 01:10:02,029

Alex: like at 125 percent as usual.

:

01:10:02,409 --> 01:10:06,969

And so with that in mind, there are

different sort of styles of training and

:

01:10:07,669 --> 01:10:09,409

different styles of learning and teaching.

:

01:10:09,409 --> 01:10:13,369

And I think one of the one of the

interesting things with Shirley is that

:

01:10:13,659 --> 01:10:15,068

what people don't know is that they can.

:

01:10:15,524 --> 01:10:18,984

You know, if they're not enjoying,

or if it's not working for them in a

:

01:10:18,984 --> 01:10:22,924

particular way, you can actually just

tell Shirley to do it differently.

:

01:10:22,984 --> 01:10:26,254

And Shirley will actually

do something differently.

:

01:10:26,924 --> 01:10:30,634

You can just ask for a different

sort of approach to working with you.

:

01:10:30,634 --> 01:10:34,124

So, you know, there is some

opportunity of Shirley's is getting

:

01:10:34,124 --> 01:10:38,064

that last word in too much to be

like, Hey, can you just like not do

:

01:10:38,084 --> 01:10:38,364

Bill: Just

:

01:10:38,404 --> 01:10:40,974

Alex: or mute so that,

Oh, we're not doing this.

:

01:10:41,174 --> 01:10:43,014

Bill: from the old

Saturday Night Live days.

:

01:10:43,474 --> 01:10:48,994

You could, you could have her

respond appropriately to Simodana.

:

01:10:48,994 --> 01:10:50,314

Simodana.

:

01:10:51,264 --> 01:10:51,674

Alex: Yeah.

:

01:10:52,074 --> 01:10:52,354

Bill: All right.

:

01:10:52,939 --> 01:10:54,029

Alex: Yeah, you

:

01:10:54,084 --> 01:10:55,204

Bill: so do you see,

:

01:10:55,249 --> 01:10:55,429

Alex: And

:

01:10:55,594 --> 01:10:57,164

Bill: do you, resist.

:

01:10:57,174 --> 01:11:00,594

You might be a little too young for that,

Alex, but you might not remember that.

:

01:11:01,024 --> 01:11:03,434

Um, but do you, do you see,

:

01:11:03,489 --> 01:11:03,849

Alex: No,

:

01:11:03,943 --> 01:11:04,614

Bill: what's that?

:

01:11:06,179 --> 01:11:06,739

Alex: said me.

:

01:11:06,739 --> 01:11:07,039

Not too

:

01:11:07,094 --> 01:11:08,534

Bill: Oh, yeah, yeah, yeah.

:

01:11:08,534 --> 01:11:13,564

Um, do you see maybe a future where

there could be a, almost a three way

:

01:11:13,564 --> 01:11:16,234

collaboration between a professional CFI?

:

01:11:17,039 --> 01:11:17,239

Alex: Yes.

:

01:11:17,519 --> 01:11:23,589

Bill: the learner and surely where

there's feedback going both ways, um,

:

01:11:23,859 --> 01:11:30,568

kind of from what the learner may have

done on their own in solo practice, kind

:

01:11:30,568 --> 01:11:35,109

of some of that feedback, making it to

the CFI to help the CFI understand where

:

01:11:35,109 --> 01:11:37,179

to put emphasis and things like that.

:

01:11:37,389 --> 01:11:39,149

Do you see that kind of

in the future as well?

:

01:11:40,919 --> 01:11:41,339

Alex: Right.

:

01:11:41,369 --> 01:11:45,929

So in fact, I at Oshkosh this year,

I met a company called Noble Flights,

:

01:11:45,959 --> 01:11:51,369

and they make these really cool sort of

SR 22 SR sort of home flight sins that

:

01:11:51,369 --> 01:11:53,839

are advanced aviation training devices.

:

01:11:53,859 --> 01:11:54,699

So if you own

:

01:11:54,709 --> 01:11:55,229

Bill: Really?

:

01:11:56,099 --> 01:11:58,729

Alex: you could actually have it

in your house and be able to have

:

01:11:58,779 --> 01:12:00,879

sort of instrument proficiency.

:

01:12:00,909 --> 01:12:04,369

You know, you have a, they

have like a, it's like a 20

:

01:12:04,369 --> 01:12:06,799

to 40 to 50, 000 piece of kit.

:

01:12:07,059 --> 01:12:07,469

Bill: Yeah.

:

01:12:07,839 --> 01:12:08,609

Alex: you know, it's, it's an

:

01:12:08,959 --> 01:12:11,399

Bill: Well, they're also flying

a million dollar airplane.

:

01:12:11,589 --> 01:12:12,129

So,

:

01:12:12,210 --> 01:12:12,500

Tiffany: Yeah.

:

01:12:13,169 --> 01:12:13,609

Alex: yeah, yeah.

:

01:12:13,609 --> 01:12:14,669

Those are pretty expensive too.

:

01:12:14,879 --> 01:12:16,849

But, you know, one of the

interesting things that they are

:

01:12:16,849 --> 01:12:20,629

thinking about is how to provide

some level of remote instruction.

:

01:12:20,659 --> 01:12:21,219

Bill: Oh yeah.

:

01:12:21,459 --> 01:12:23,769

Alex: so there is a really

big, big opportunity.

:

01:12:23,799 --> 01:12:25,989

In fact, there are some companies

right now that already provide.

:

01:12:26,434 --> 01:12:29,414

You know, there's one flight sim

coach that provides remote instruction

:

01:12:29,864 --> 01:12:31,594

between that I don't endorse.

:

01:12:31,594 --> 01:12:35,034

I don't, I'm not personally familiar

with them, but you know, it's, it is

:

01:12:35,034 --> 01:12:39,354

a company that where you, uh, and I

don't not endorse it for the record.

:

01:12:39,434 --> 01:12:39,544

It

:

01:12:39,579 --> 01:12:40,339

Bill: Yeah, yeah, right.

:

01:12:40,364 --> 01:12:40,714

Alex: company.

:

01:12:40,714 --> 01:12:41,624

That's out there that provides

:

01:12:41,799 --> 01:12:43,209

Bill: You don't know enough about it.

:

01:12:43,279 --> 01:12:44,759

So yes, I got it.

:

01:12:44,774 --> 01:12:48,974

Alex: know enough about it, but like the,

um, but it's really, it's a really cool

:

01:12:48,974 --> 01:12:52,674

concept where you have an instructor who's

able to join you in a simulation session.

:

01:12:53,044 --> 01:12:57,584

Now if you combine that, a few things

you combine in here, you combine a, a

:

01:12:58,674 --> 01:13:03,774

A AI sort of, uh, you provide, surely

provide some level of instruction and then

:

01:13:03,774 --> 01:13:06,924

you have the ability to kind of connect

in an instructor to be able to provide

:

01:13:07,164 --> 01:13:10,734

sort of the verification of how somebody

is actually doing in their progress.

:

01:13:11,034 --> 01:13:13,374

And you sort of have a really neat

combination, the sort of thing that

:

01:13:13,374 --> 01:13:15,744

we were talking about in the kind

of commercial spectrum, which would

:

01:13:15,744 --> 01:13:18,644

be really useful for them, but

also something that could provide

:

01:13:18,644 --> 01:13:19,874

sort of a combination, you know.

:

01:13:20,104 --> 01:13:22,764

You don't necessarily get home

and you don't necessarily have

:

01:13:22,764 --> 01:13:23,984

something scheduled with somebody.

:

01:13:24,274 --> 01:13:25,044

We want to practice.

:

01:13:25,044 --> 01:13:27,804

And so surely is really good because

you don't really, you can just

:

01:13:27,804 --> 01:13:29,224

sort of show up and truly is ready.

:

01:13:29,584 --> 01:13:33,054

And then, you know, there's a

opportunity, of course, to be able

:

01:13:33,054 --> 01:13:34,724

to provide that sort of connection.

:

01:13:34,724 --> 01:13:38,374

And so a lot of our technology that

is able a lot of our technology

:

01:13:38,374 --> 01:13:42,294

that provides the sort of connection

with Shirley and the individualist

:

01:13:42,434 --> 01:13:45,814

technology that could be able to

provide that sort of session between.

:

01:13:46,164 --> 01:13:47,564

An individual and another individual.

:

01:13:47,624 --> 01:13:49,654

And that's something we're really

excited to be able to do, because,

:

01:13:49,984 --> 01:13:54,764

you know, not and not just in, you

know, and to varying degrees as well.

:

01:13:54,794 --> 01:13:58,874

So you'd be able to have

theoretically at at its extreme.

:

01:13:59,344 --> 01:14:03,284

You think about to a logical conclusion,

you have a VR headset that somebody

:

01:14:03,294 --> 01:14:04,634

you're sitting inside the airplane.

:

01:14:04,704 --> 01:14:06,414

You're able to interact

with all the controls.

:

01:14:06,514 --> 01:14:09,474

You have an instructor to

actually sit next to you in sort

:

01:14:09,474 --> 01:14:10,864

of this virtual space inside of.

:

01:14:11,244 --> 01:14:14,193

Your airplane and be able to sort of see

you as you're doing these sort of things.

:

01:14:14,193 --> 01:14:17,924

I think this would be this is sort of the

logical conclusion where things can go.

:

01:14:17,984 --> 01:14:20,084

You send the VR headset to somebody.

:

01:14:20,474 --> 01:14:23,214

Surely you can help get them prepared

to be familiar with this airplane.

:

01:14:23,214 --> 01:14:25,814

You have an instructor join them

next to them inside of the cockpit.

:

01:14:26,229 --> 01:14:28,549

And be able to verify that they

know how to operate this vehicle.

:

01:14:29,289 --> 01:14:34,149

And so this is absolutely where this sort

of our kind of our part of our ground game

:

01:14:34,159 --> 01:14:39,009

vision of how we bring sort of advanced

training and make it a lot more accessible

:

01:14:39,009 --> 01:14:43,939

and representative to all sorts of flight

between maneuvers to sort of flight

:

01:14:43,949 --> 01:14:48,659

training device style, sort of instrument

training and et cetera, et cetera.

:

01:14:48,659 --> 01:14:48,999

And.

:

01:14:49,318 --> 01:14:55,889

And looking, and looking to do that as

part of supply, surely, So that's a,

:

01:14:55,889 --> 01:14:57,269

that's a great and relevant question.

:

01:14:58,699 --> 01:14:58,999

Bill: Cool.

:

01:15:01,689 --> 01:15:12,059

Um, so, um, as it pertains to teaching,

uh, one of the, one of the things that

:

01:15:12,059 --> 01:15:21,559

keeps coming up in my mind is that,

um, this is super ambitious, right?

:

01:15:21,969 --> 01:15:27,004

So where we met, Um, there's a,

there's another company, you know,

:

01:15:27,014 --> 01:15:30,894

doing a co pilot, um, sort of approach

and we're actually going to be,

:

01:15:31,089 --> 01:15:31,489

Alex: yeah,

:

01:15:31,584 --> 01:15:34,714

Bill: Goose, we're going to actually be

talking to them in a couple of weeks,

:

01:15:35,164 --> 01:15:41,274

um, for, for the same reasons, this is

all very interesting, um, what they're

:

01:15:41,274 --> 01:15:48,964

doing is, is much more, um, would say

focused on a very specific use case of

:

01:15:49,884 --> 01:15:54,894

your co pilot in the cockpit, whereas

you're taking the approach of being sort

:

01:15:54,894 --> 01:16:01,099

of, you know, A lot of different things

to a pilot, to a simmer, to a pilot,

:

01:16:01,099 --> 01:16:03,659

to a learner, to somebody who's flying.

:

01:16:04,589 --> 01:16:06,009

It's very, very ambitious.

:

01:16:06,389 --> 01:16:13,509

Um, how do you, do you balance what you're

doing with what you can deliver right now?

:

01:16:13,519 --> 01:16:14,769

How, how's that going?

:

01:16:14,779 --> 01:16:17,469

And, and how are you walking that line?

:

01:16:19,929 --> 01:16:22,769

Alex: I think that's an insightful

question for two reasons.

:

01:16:22,859 --> 01:16:30,509

One of them is that a, it's realistic

to be able to only, it's, it's

:

01:16:30,509 --> 01:16:34,568

realistic to say, Hey, you're looking

at doing this entire scope of things,

:

01:16:34,568 --> 01:16:35,909

what can you actually cut off?

:

01:16:35,939 --> 01:16:38,699

But I think there's another sort

of conceptual reason why that's an

:

01:16:38,699 --> 01:16:41,979

insightful question is that it's

actually challenging if you're a.

:

01:16:42,344 --> 01:16:44,114

Individual hearing about what we're doing.

:

01:16:44,114 --> 01:16:46,234

It could be challenging to

think, okay, how does this fit

:

01:16:46,234 --> 01:16:47,354

into my life in particular?

:

01:16:47,799 --> 01:16:48,339

Bill: Um, yeah.

:

01:16:48,754 --> 01:16:53,044

Alex: you know, I think, yeah,

and so I think there's, there's,

:

01:16:53,874 --> 01:16:55,514

there's a few different ways.

:

01:16:55,514 --> 01:16:57,754

And I'll try to get back to the question.

:

01:16:57,754 --> 01:17:03,964

Also, of, you know, how are we

balancing it long term as well?

:

01:17:04,334 --> 01:17:10,894

And so the to the former question,

the, the thing that we provide

:

01:17:10,894 --> 01:17:15,004

right now is a copilot that

connects into your flights in.

:

01:17:15,004 --> 01:17:15,074

Okay.

:

01:17:15,484 --> 01:17:20,014

And can, you can either fly with

and sort of an open sort of setting.

:

01:17:20,014 --> 01:17:21,264

It's not just a deadhead.

:

01:17:21,314 --> 01:17:22,784

It flips switches.

:

01:17:22,784 --> 01:17:24,144

It interacts with the SIM for you.

:

01:17:24,144 --> 01:17:24,984

It can be sort of a.

:

01:17:25,414 --> 01:17:27,964

Kind of a co pilot, it's your buddy,

:

01:17:28,489 --> 01:17:29,119

Bill: co pilot.

:

01:17:29,289 --> 01:17:29,648

Yeah.

:

01:17:29,784 --> 01:17:29,904

Alex: pretty

:

01:17:29,999 --> 01:17:30,289

Bill: Right.

:

01:17:30,289 --> 01:17:32,669

Yeah.

:

01:17:32,714 --> 01:17:36,674

Alex: And the other aspect that

we're working on right now is

:

01:17:36,714 --> 01:17:38,764

through our challenges system.

:

01:17:38,914 --> 01:17:41,664

And so we have this sort of

concept that we're building

:

01:17:41,664 --> 01:17:43,164

off of, which is challenges.

:

01:17:43,484 --> 01:17:48,714

Challenges have enabled us to build

sort of fun experiences from the Aaliyah

:

01:17:48,864 --> 01:17:53,914

sort of training challenge to also our

entire kind of training curriculum.

:

01:17:54,354 --> 01:17:58,724

And so what we're providing and what

we're hoping to get feedback on in part

:

01:17:58,724 --> 01:18:03,584

through conversations like this is to

have pilots try out this sort of private

:

01:18:03,584 --> 01:18:07,244

pilot curriculum and see if it's meeting

their needs and be able to get feedback.

:

01:18:07,794 --> 01:18:19,519

And so, you know, it, it, it would be fair

to say right now that surely is, In early

:

01:18:19,519 --> 01:18:24,559

adopters product, so it is absolutely

fair to say that, you know, you try.

:

01:18:24,559 --> 01:18:25,859

Surely it works.

:

01:18:25,898 --> 01:18:31,339

The product works, but there are

that you can provide feedback on.

:

01:18:31,339 --> 01:18:34,879

And then within a day or two,

we go and we build it you

:

01:18:34,898 --> 01:18:36,459

provide that sort of feedback.

:

01:18:36,459 --> 01:18:38,539

And you have this sort of

iteration process, you know,

:

01:18:38,549 --> 01:18:40,959

th:

:

01:18:41,299 --> 01:18:43,629

Hopefully in a few months will

be through that sort of process

:

01:18:43,629 --> 01:18:44,898

with the private pilot curriculum.

:

01:18:45,654 --> 01:18:48,124

Just like we're starting to get

through that process related

:

01:18:48,124 --> 01:18:49,294

to some of the co pilot stuff

:

01:18:49,489 --> 01:18:49,759

Bill: Yeah.

:

01:18:50,014 --> 01:18:50,494

Alex: right now.

:

01:18:50,604 --> 01:18:52,064

And, you know, we'll continue to do that.

:

01:18:52,374 --> 01:18:59,144

You know, we're working with a company

that has a few hundred And so we'll be

:

01:18:59,454 --> 01:19:05,104

getting feedback with them using our

product to see how they fly with Shirley.

:

01:19:05,114 --> 01:19:06,764

A lot of those people are

becoming pilots as well.

:

01:19:07,784 --> 01:19:11,184

we're working to develop this

product as a startup company.

:

01:19:11,644 --> 01:19:15,504

There are your major

prerogative is to grow.

:

01:19:15,959 --> 01:19:16,489

Bill: Yes.

:

01:19:16,514 --> 01:19:20,273

Alex: so you kind of are like this

little silkworm, you're like trying

:

01:19:20,273 --> 01:19:22,074

to find light and you're like

:

01:19:22,429 --> 01:19:22,669

Bill: Yeah.

:

01:19:22,874 --> 01:19:27,004

Alex: kind of put energy into what

works and like, maybe don't worry too

:

01:19:27,004 --> 01:19:31,193

much about what's, you know, about

things that are not really working

:

01:19:31,193 --> 01:19:32,564

and it's kind of like you water the

:

01:19:32,749 --> 01:19:33,068

Bill: Or the,

:

01:19:33,114 --> 01:19:34,344

Alex: growing as opposed to the

:

01:19:34,818 --> 01:19:37,379

Bill: yeah, you got to figure

out a way to make revenue, right?

:

01:19:37,443 --> 01:19:37,874

Alex: garden.

:

01:19:37,874 --> 01:19:38,084

That

:

01:19:38,199 --> 01:19:39,719

Bill: That's not always that clear.

:

01:19:39,979 --> 01:19:43,109

It's not always that clear when you're

doing something conceptual like this.

:

01:19:43,109 --> 01:19:45,409

It's like, okay, well, where

does the revenue come from?

:

01:19:45,409 --> 01:19:47,539

It's, it's not that easy

of a question to answer.

:

01:19:49,544 --> 01:19:53,924

Alex: And so what we ended up

doing is we, we really closely

:

01:19:53,924 --> 01:19:54,804

with the customers that we have.

:

01:19:55,154 --> 01:19:59,144

And so we ended up having these really

close customer relationships where we

:

01:19:59,144 --> 01:20:00,294

find out things that are important.

:

01:20:00,294 --> 01:20:02,894

We watched the videos that they're

posting, if they're streamers.

:

01:20:03,539 --> 01:20:06,219

know, and then we end up figuring

out how to make their lives better.

:

01:20:06,549 --> 01:20:08,409

Fundamentally trying to build

something that people want.

:

01:20:08,639 --> 01:20:16,269

I think it is still very insightful to

be able to say that there are, there are

:

01:20:16,299 --> 01:20:21,089

a huge number of things that this, that

this could be, and there are a huge number

:

01:20:21,089 --> 01:20:22,309

of things that we're building towards.

:

01:20:22,349 --> 01:20:24,919

I think we're in an excellent

position to be able to start with

:

01:20:24,919 --> 01:20:29,209

these really of large group of

enthusiastic home flight sim users,

:

01:20:29,209 --> 01:20:31,539

help them bridge from sim to sky.

:

01:20:32,029 --> 01:20:32,479

And.

:

01:20:32,879 --> 01:20:35,459

Be able to provide training and

integrate with other sort of training

:

01:20:35,689 --> 01:20:39,148

platforms and curriculum to help them

be kind of having a one stop shop that

:

01:20:39,148 --> 01:20:40,369

could help them get into the cockpit.

:

01:20:40,369 --> 01:20:43,299

And with the idea that people who

trained with Shirley would want to

:

01:20:43,299 --> 01:20:46,699

fly with Shirley and the actual,

an actual airplane because they

:

01:20:46,699 --> 01:20:47,809

would have had this experience.

:

01:20:48,259 --> 01:20:51,759

And so I think, I think there

is a path from sin to sky that

:

01:20:51,979 --> 01:20:53,009

makes sense for a company.

:

01:20:53,009 --> 01:20:55,349

It was sort of the data pipelines

and things like this that.

:

01:20:55,759 --> 01:20:58,398

It's set up really nicely to

make this all sort of possible.

:

01:20:58,729 --> 01:21:02,635

Yeah, but if you're a customer today,

the question is, you know, if you

:

01:21:02,635 --> 01:21:06,869

have, if you have explained August

th,:

:

01:21:07,284 --> 01:21:12,334

You are interested in flying with Shirley,

and you're interested in training,

:

01:21:12,714 --> 01:21:13,904

and it's a great time to get involved.

:

01:21:14,044 --> 01:21:17,584

You know, it's a great time to

join the discord and interact.

:

01:21:17,584 --> 01:21:20,234

And as we sort of build this out,

and we're excited to have more

:

01:21:20,234 --> 01:21:24,554

people to to work with and learn

what to learn more about what, you

:

01:21:24,554 --> 01:21:27,674

know, what customers want and sort

of build something directly on that.

:

01:21:28,004 --> 01:21:28,294

Yeah.

:

01:21:28,329 --> 01:21:28,699

Bill: Okay.

:

01:21:28,989 --> 01:21:30,659

So I'm going to ask a really, um,

:

01:21:32,979 --> 01:21:38,859

selfish, selfish question, but maybe

this will extrapolate to, um, uh,

:

01:21:39,219 --> 01:21:42,009

to many of your future customers.

:

01:21:42,429 --> 01:21:43,209

Um, I think it will.

:

01:21:43,984 --> 01:21:44,984

I'm kind of an everyman.

:

01:21:45,794 --> 01:21:46,384

So

:

01:21:49,394 --> 01:21:54,794

when, when you and I first started

talking about how Fly with Shirley

:

01:21:54,794 --> 01:22:00,924

could be used in a training environment,

my, my brain started going to all

:

01:22:00,924 --> 01:22:06,484

sorts of places that would help me

specifically and maybe to other people.

:

01:22:06,484 --> 01:22:16,709

Like I said, um, when I'm studying,

for a rating for, test for, you know,

:

01:22:16,709 --> 01:22:24,459

for a check ride, an oral, whatever,

or maybe I'm just, you know, doing some

:

01:22:24,489 --> 01:22:30,309

instrument, um, you know, some approaches

and I start to ask myself some questions.

:

01:22:31,279 --> 01:22:36,318

I'll spend the next hour to two

hours diving into the aim and

:

01:22:36,318 --> 01:22:40,979

into the, the FARs and trying

to find answers to my questions.

:

01:22:41,329 --> 01:22:45,644

So the first thing that popped

into my mind is I would love to

:

01:22:45,644 --> 01:22:50,674

have a resource that's so aviation

specific like this that I could ask

:

01:22:50,744 --> 01:22:54,104

questions or have a conversation.

:

01:22:55,193 --> 01:23:03,304

Is something like, um, off the

top of my head, um, what, what

:

01:23:03,304 --> 01:23:08,594

does a, uh, what does a vertical

descent point look like on a chart?

:

01:23:09,364 --> 01:23:16,074

And it can show me, or it might be,

you know, you explain the differences

:

01:23:16,074 --> 01:23:17,724

between these two approaches?

:

01:23:18,594 --> 01:23:25,854

Or, um, remind me what the three different

types, maybe it's four, I don't know,

:

01:23:26,204 --> 01:23:31,894

the three different types of night, uh,

are, I, I'm trying, I'm trying to think

:

01:23:31,894 --> 01:23:34,414

of examples, that's probably not the

best example, because that's pretty easy

:

01:23:34,414 --> 01:23:38,494

to look up, but I'm trying to think of

examples where you would want to get

:

01:23:38,494 --> 01:23:42,544

specific with Shirley on things that

you're not going to get from an internet,

:

01:23:42,614 --> 01:23:44,814

internet search, because what you're

going to get from an internet, internet.

:

01:23:45,084 --> 01:23:48,464

An internet search is a bunch of

different opinions, maybe a podcast,

:

01:23:48,494 --> 01:23:51,474

maybe a YouTube video that's on the

subject, you know, that sort of thing.

:

01:23:52,394 --> 01:23:56,574

But I might want Shirley to help

guide me in the research I would have

:

01:23:56,574 --> 01:23:59,104

done anyway and help me do it faster.

:

01:23:59,484 --> 01:24:03,624

So in other words, it, it pulls

together the answer, but then

:

01:24:03,624 --> 01:24:08,204

points to the resources so

that I can quickly go the FAR.

:

01:24:09,624 --> 01:24:13,794

you know, that specific section and

see in the AIM, the chart that they

:

01:24:13,794 --> 01:24:14,824

have, you know, that sort of thing.

:

01:24:14,824 --> 01:24:16,684

I hope I'm getting across what I'm asking.

:

01:24:16,994 --> 01:24:18,974

Is, is that something

you're thinking about?

:

01:24:21,454 --> 01:24:21,864

Alex: Right.

:

01:24:22,014 --> 01:24:22,734

And so, cool.

:

01:24:23,709 --> 01:24:28,179

I think there are absolutely aspects

of that that we're thinking about, you

:

01:24:28,179 --> 01:24:32,039

know, when you start to think about how

Shirley can provide a virtual check ride.

:

01:24:32,273 --> 01:24:32,664

Bill: Mm hmm.

:

01:24:32,824 --> 01:24:36,574

Alex: there are questions you'd want

to be able to ask related to that.

:

01:24:36,734 --> 01:24:37,254

Bill: Yes.

:

01:24:37,554 --> 01:24:38,984

Alex: And then if the D.

:

01:24:38,984 --> 01:24:39,294

P.

:

01:24:39,304 --> 01:24:41,084

says, well, I actually don't

really know the answer.

:

01:24:41,414 --> 01:24:45,624

You tell me that that doesn't really

sort of scratch the itch that you're

:

01:24:45,864 --> 01:24:46,284

Bill: Right.

:

01:24:46,523 --> 01:24:47,074

Alex: about here.

:

01:24:47,564 --> 01:24:55,344

What I what I will say is that, you

know, plan to back up and surely with all

:

01:24:56,114 --> 01:24:58,523

all the references from, you know, the.

:

01:24:58,929 --> 01:25:02,139

You know, the, the far, of course,

the firing and all these sort of

:

01:25:02,284 --> 01:25:02,594

Bill: Yeah.

:

01:25:02,739 --> 01:25:04,629

Alex: the handbooks, all

the flying handbooks, the P.

:

01:25:04,629 --> 01:25:04,749

O.

:

01:25:04,749 --> 01:25:04,909

H.

:

01:25:04,909 --> 01:25:05,568

is, et cetera.

:

01:25:06,039 --> 01:25:09,169

There are, there are sort of like.

:

01:25:10,504 --> 01:25:15,064

where you have sort of like FAA

legal department decision papers

:

01:25:15,094 --> 01:25:15,544

Bill: Yes.

:

01:25:15,654 --> 01:25:16,374

Alex: you know, what

:

01:25:16,724 --> 01:25:18,874

Bill: The legal opinions and stuff.

:

01:25:18,874 --> 01:25:19,224

Yeah.

:

01:25:19,394 --> 01:25:24,454

Alex: who's, just like you get into

that absolute wild land of, you know,

:

01:25:24,454 --> 01:25:27,074

questions that I think are really good

questions or the sort of questions

:

01:25:27,074 --> 01:25:29,419

that I used to, Get crickets to and I'd

:

01:25:29,574 --> 01:25:29,894

Bill: Yep.

:

01:25:29,999 --> 01:25:33,659

Alex: on our sort of discussion

forum be like, ah, who cares?

:

01:25:33,659 --> 01:25:37,129

Like, why are you like, you know,

or this is like such a specific

:

01:25:37,139 --> 01:25:41,479

IFR question related to, you know,

philosophers does not, you know,

:

01:25:41,479 --> 01:25:43,199

these are the sort of like very.

:

01:25:43,609 --> 01:25:46,859

Kind of insightful questions that

need to be kind of built through,

:

01:25:47,044 --> 01:25:48,984

Bill: I've got some logging questions

:

01:25:49,029 --> 01:25:49,148

Alex: the,

:

01:25:49,284 --> 01:25:50,074

Bill: right now.

:

01:25:50,094 --> 01:25:55,504

Here I am, um, I've been a private pilot

for 15 years or something like that.

:

01:25:55,554 --> 01:25:59,824

And here I am at the commercial

level and about to finish my CFI.

:

01:26:00,584 --> 01:26:05,064

I was looking at my logbook the other

day, about ready to enter some stuff.

:

01:26:05,364 --> 01:26:09,724

And I'm hitting situations where

I'm going, I don't actually

:

01:26:09,724 --> 01:26:11,154

know the proper way to log this.

:

01:26:11,599 --> 01:26:17,409

Like, it's not your typical, like, I've

got a safety pilot situation or, uh, I,

:

01:26:17,459 --> 01:26:22,049

I won't go into details, but my point

is I would love to have a resource

:

01:26:22,349 --> 01:26:26,349

because I even know that most of my

instructors that I know are probably

:

01:26:26,349 --> 01:26:27,889

going to go, yeah, I don't know.

:

01:26:28,699 --> 01:26:31,239

it would be amazing to have a

resource that would help you.

:

01:26:31,799 --> 01:26:35,129

discover the answer for yourself

by walking you along a path.

:

01:26:35,139 --> 01:26:35,669

Well, I don't know.

:

01:26:35,669 --> 01:26:36,279

Good question.

:

01:26:36,279 --> 01:26:37,479

Let's look at this.

:

01:26:37,479 --> 01:26:38,309

Well, what about this?

:

01:26:38,309 --> 01:26:42,419

And you know, it's, it would just be

incredible to have a resource like that.

:

01:26:43,039 --> 01:26:43,419

You know?

:

01:26:44,969 --> 01:26:48,989

Alex: I think that there are, I

think that this could be in the

:

01:26:49,139 --> 01:26:54,709

good wheelhouse for companies

that are providing sort of ground

:

01:26:54,749 --> 01:26:55,809

Bill: Yeah, that's true.

:

01:26:56,159 --> 01:26:56,929

Alex: materials,

:

01:26:57,009 --> 01:26:57,279

Bill: point.

:

01:26:57,279 --> 01:27:00,859

Yeah.

:

01:27:01,609 --> 01:27:04,619

Alex: able to give some sort of

insights related to some of these

:

01:27:04,619 --> 01:27:08,689

questions, you know, I think with

the thing with the format of Shirley

:

01:27:08,699 --> 01:27:12,394

currently, you know, And as much as

we were just talking about how we were

:

01:27:12,394 --> 01:27:13,904

intending surely to be everything to

:

01:27:14,189 --> 01:27:14,489

Bill: Right.

:

01:27:14,489 --> 01:27:14,709

Right.

:

01:27:14,719 --> 01:27:17,959

You've got to, you've got to

put a limit somewhere, right?

:

01:27:18,820 --> 01:27:19,110

Tiffany: Yeah.

:

01:27:19,564 --> 01:27:22,904

Alex: we're, we're bridging from SIM

to sky, but we're looking to basically

:

01:27:22,914 --> 01:27:24,904

be the co pilot sort of setting.

:

01:27:24,924 --> 01:27:28,474

So surely is your co pilot friend

sitting next to you in the cockpit who

:

01:27:28,754 --> 01:27:33,954

can also provide some level of training

and instruction, not necessarily going

:

01:27:33,954 --> 01:27:40,764

to like write up that has references to

things, although like I will say that,

:

01:27:41,044 --> 01:27:45,374

you know, We'll come back to you and be

able to get and get your feedback on that.

:

01:27:45,474 --> 01:27:46,394

And, and, and.

:

01:27:46,779 --> 01:27:48,459

In some time, let's say, you

:

01:27:48,599 --> 01:27:48,779

Bill: Yeah.

:

01:27:48,779 --> 01:27:49,059

Yeah.

:

01:27:49,389 --> 01:27:54,019

Alex: let's say you are, you're,

you're, you're saying probably resonates

:

01:27:54,019 --> 01:27:57,579

with what a lot of other students

experience, which is, you know, really

:

01:27:57,579 --> 01:28:00,279

stumper questions that are super hard.

:

01:28:00,549 --> 01:28:00,669

You

:

01:28:00,809 --> 01:28:01,179

Bill: Yeah.

:

01:28:01,209 --> 01:28:04,989

Alex: fact, I've met some people who are

working on these sort of written based

:

01:28:05,419 --> 01:28:09,044

sort of like, you type it out, your

question, and then it's like providing.

:

01:28:09,259 --> 01:28:09,919

Bill: Oh yeah.

:

01:28:10,789 --> 01:28:11,449

Alex: of feedback.

:

01:28:11,449 --> 01:28:14,469

I met somebody like that

at, actually at, at Oshkosh.

:

01:28:14,469 --> 01:28:16,689

I wish I had his card

at the top of my mind.

:

01:28:17,579 --> 01:28:19,579

again, another person that

I haven't tried there.

:

01:28:19,729 --> 01:28:23,489

I mean, I barely tried their stuff

and, you know, it seems cool.

:

01:28:23,489 --> 01:28:26,159

We should check it out

type of deal, but the.

:

01:28:26,554 --> 01:28:33,284

The, the, the solution there, I

think, is, um, is a kind of thing that

:

01:28:33,294 --> 01:28:37,354

spits out text that's permanent, that

has references, and is a very bulk

:

01:28:37,374 --> 01:28:38,034

Bill: Interesting.

:

01:28:38,034 --> 01:28:38,334

Yeah.

:

01:28:38,384 --> 01:28:38,614

Alex: do

:

01:28:38,624 --> 01:28:38,934

Bill: Yeah.

:

01:28:38,943 --> 01:28:43,234

Alex: be part of a one stop, and that's

a, and that is an event, that is a place

:

01:28:43,234 --> 01:28:44,854

where AI can take a lot of advantage.

:

01:28:45,169 --> 01:28:48,579

You know, what we'd like to be able

to do is be able to talk to you about

:

01:28:48,579 --> 01:28:51,679

those sort of things, pull in the

relevant information so that while

:

01:28:51,679 --> 01:28:54,519

you're kind of having this discourse,

that could be an important thing or

:

01:28:54,519 --> 01:28:57,709

take a note for you to be able to

look that sort of thing up because you

:

01:28:57,709 --> 01:29:00,679

might be flying an approach and you're

like, my goodness, what the heck is

:

01:29:00,784 --> 01:29:01,154

Bill: Yep.

:

01:29:01,549 --> 01:29:01,859

Alex: And,

:

01:29:01,884 --> 01:29:02,193

Bill: Yep.

:

01:29:02,499 --> 01:29:04,129

Alex: you know, you want

to remember that later.

:

01:29:04,469 --> 01:29:07,509

And so you'll be able to have that as

sort of a flight note that then ends

:

01:29:07,509 --> 01:29:09,239

up in your, you know, inside of your

:

01:29:09,634 --> 01:29:09,974

Bill: Yeah.

:

01:29:10,004 --> 01:29:10,204

Yeah.

:

01:29:10,204 --> 01:29:10,874

Great idea.

:

01:29:11,059 --> 01:29:11,329

Alex: items

:

01:29:11,384 --> 01:29:11,984

Bill: Great idea.

:

01:29:11,984 --> 01:29:13,724

Yeah.

:

01:29:13,739 --> 01:29:17,249

Alex: think it's really cool to be able

to think about Shirley as being part of

:

01:29:17,249 --> 01:29:22,599

a one stop shop related to some level

of ground, like ground instruction.

:

01:29:22,849 --> 01:29:25,318

You have a ground

instruction integrated with.

:

01:29:25,959 --> 01:29:30,239

A, um, you know, you have ground

destruction, really integrated with

:

01:29:30,519 --> 01:29:34,629

private pilot maneuvers, integrated

with private pilot sort of checks

:

01:29:34,979 --> 01:29:36,379

your check ride preparation.

:

01:29:36,719 --> 01:29:39,679

And so, you know, I think it is

conceivable that we could get

:

01:29:39,679 --> 01:29:43,369

into building a whole learning

management system that provides a

:

01:29:43,604 --> 01:29:43,924

Bill: Yeah.

:

01:29:44,154 --> 01:29:46,824

Alex: This sort of text based

thing, but we're not doing

:

01:29:46,884 --> 01:29:47,284

Bill: Right.

:

01:29:47,284 --> 01:29:47,504

Right.

:

01:29:47,504 --> 01:29:47,724

Right.

:

01:29:47,724 --> 01:29:48,034

Right.

:

01:29:48,504 --> 01:29:50,934

Alex: you know, I think,

that needs to be seen.

:

01:29:50,934 --> 01:29:53,814

So I will be the exception to

say that we're not saying that

:

01:29:53,814 --> 01:29:54,454

we're everything to everybody,

:

01:29:54,693 --> 01:29:55,144

Bill: Awesome.

:

01:29:55,234 --> 01:29:55,684

Alex: that's my

:

01:29:56,034 --> 01:29:58,504

Bill: Look, we came full,

we came full circle on that.

:

01:29:58,604 --> 01:29:59,134

Look at that.

:

01:30:00,324 --> 01:30:00,914

Alex: That's right.

:

01:30:00,974 --> 01:30:01,394

Yeah.

:

01:30:01,945 --> 01:30:03,925

Tiffany: Did you say when,

what year you started this?

:

01:30:04,350 --> 01:30:04,670

Was it?

:

01:30:04,700 --> 01:30:07,960

I see March 24 on your LinkedIn.

:

01:30:10,034 --> 01:30:10,464

Alex: Yes.

:

01:30:10,504 --> 01:30:11,424

March,:

:

01:30:11,604 --> 01:30:12,464

Bill: It's brand new.

:

01:30:12,534 --> 01:30:14,874

They're, they're at their

first MVP basically.

:

01:30:14,874 --> 01:30:16,424

Well, a little past it now, but.

:

01:30:17,684 --> 01:30:20,514

Alex: So flights in Mexico

was our was our MVP.

:

01:30:20,534 --> 01:30:21,754

That was in July.

:

01:30:22,644 --> 01:30:28,434

so at the beginning of July, um,

and so, yeah, we've just been

:

01:30:28,630 --> 01:30:28,930

Tiffany: Wow.

:

01:30:29,134 --> 01:30:29,943

Alex: a couple months now.

:

01:30:29,943 --> 01:30:32,154

And so, yeah, anyway,

:

01:30:32,844 --> 01:30:33,234

Bill: Excellent.

:

01:30:33,254 --> 01:30:33,624

Well,

:

01:30:33,714 --> 01:30:34,224

Alex: exciting.

:

01:30:34,354 --> 01:30:35,454

Bill: it is very

:

01:30:35,670 --> 01:30:35,860

Tiffany: it's

:

01:30:36,023 --> 01:30:40,369

Bill: and it's, it's, It's hard to

comprehend sometimes where all of this

:

01:30:40,379 --> 01:30:46,099

can go, uh, but we certainly appreciate

your time helping bend our brains a little

:

01:30:46,099 --> 01:30:50,439

bit around, around the possibilities.

:

01:30:50,869 --> 01:30:54,469

And because I know you've been thinking

about this a lot more than we have.

:

01:30:54,699 --> 01:30:56,729

So we do

:

01:30:56,950 --> 01:30:58,140

Tiffany: well, and I

:

01:30:58,304 --> 01:30:58,634

Alex: been my

:

01:30:59,034 --> 01:31:00,818

Bill: time.

:

01:31:01,530 --> 01:31:02,270

Tiffany: I could be wrong.

:

01:31:02,270 --> 01:31:06,040

I know we at least used to hang out

with the, the ForeFlight guys or they

:

01:31:06,040 --> 01:31:10,770

were kind of in that circle and it was

this tiny little startup and like no

:

01:31:10,770 --> 01:31:14,570

one's ever going to let you use your

phone in the closet and look at it now.

:

01:31:15,019 --> 01:31:15,479

Bill: And look at

:

01:31:15,550 --> 01:31:17,110

Tiffany: this is, it's

really exciting to see this.

:

01:31:17,719 --> 01:31:20,089

Bill: Well, and they're, and they're

starting to use, I mean, it's a

:

01:31:20,089 --> 01:31:24,818

totally different thing, but they're

starting to use big data as well.

:

01:31:25,239 --> 01:31:29,479

Um, you know, they're, they're

pulling data from those adhars

:

01:31:29,489 --> 01:31:37,259

in the centuries to be able to do

automatic pyreps on turbulence.

:

01:31:37,429 --> 01:31:41,429

You know, and so they're using,

they're using models to filter out,

:

01:31:43,144 --> 01:31:49,074

operations so that they can see

where, um, turbulence is happening.

:

01:31:49,084 --> 01:31:52,344

They know the airplane, you

know, they know the type, they

:

01:31:52,344 --> 01:31:53,664

know the weight of the airplane.

:

01:31:53,914 --> 01:31:55,244

They know exactly where it's at.

:

01:31:55,254 --> 01:31:57,104

They know what altitude it's at.

:

01:31:57,544 --> 01:31:58,974

They know what direction it's heading.

:

01:32:01,064 --> 01:32:05,454

they're filtering out normal

movement, normal airplane movement.

:

01:32:05,484 --> 01:32:09,714

And what they're left with is That

was turbulence, and that, this

:

01:32:09,724 --> 01:32:11,324

is the level of that turbulence.

:

01:32:11,324 --> 01:32:12,984

That's, that's pretty incredible stuff.

:

01:32:12,984 --> 01:32:15,914

I mean, it's totally different than

what you're doing, but the idea of being

:

01:32:15,914 --> 01:32:21,214

able to take, um, large amounts of data

from a lot of different places and,

:

01:32:21,334 --> 01:32:26,793

and give real time insights to users

of the application, it's really amazing

:

01:32:26,793 --> 01:32:30,814

what, what we're going to be able to do

over the next, you know, 10, 15 years.

:

01:32:33,104 --> 01:32:34,654

Alex: I'm going to say

that there are so many.

:

01:32:35,089 --> 01:32:39,539

You know, the, these companies that

started in the last generation of

:

01:32:39,539 --> 01:32:43,789

product, whereas essentially, you know,

we have these new iPhones and iPads,

:

01:32:44,109 --> 01:32:49,568

how can we bring charts to them and then

also make pilots lives a lot better?

:

01:32:49,898 --> 01:32:51,389

Those things have gotten so good.

:

01:32:51,568 --> 01:32:51,639

I

:

01:32:51,674 --> 01:32:52,004

Bill: Yep.

:

01:32:52,009 --> 01:32:55,059

Alex: look at ForeFlight, it's just

an amazing piece of technology.

:

01:32:55,059 --> 01:32:57,359

It has all the data

possible on an entire world.

:

01:32:57,729 --> 01:33:01,089

And now what's really neat about

this sort of technological transition

:

01:33:01,629 --> 01:33:04,429

is that there are all these

really cool companies that exist.

:

01:33:05,289 --> 01:33:07,039

let's sort of look about

this next generation.

:

01:33:07,039 --> 01:33:08,809

So you have, you know,

if you have goose is a

:

01:33:08,934 --> 01:33:09,354

Bill: Mm hmm.

:

01:33:09,549 --> 01:33:09,939

Alex: of that.

:

01:33:10,219 --> 01:33:12,159

You have sort of the same intentions.

:

01:33:12,959 --> 01:33:16,209

be on to see, you know, you have,

you know, you have surely in this

:

01:33:16,209 --> 01:33:18,318

sort of category of being able to

provide training and eventually be

:

01:33:18,318 --> 01:33:19,489

able to get back into a cockpit.

:

01:33:19,509 --> 01:33:20,898

Something that's pretty conversational.

:

01:33:21,289 --> 01:33:22,089

You have companies like.

:

01:33:22,469 --> 01:33:26,609

You know, loft dynamics, which are

making sort of, you know, VR certified

:

01:33:26,609 --> 01:33:30,299

Sims or maybe 30, like divide by 20, the

:

01:33:30,580 --> 01:33:30,590

Tiffany: A

:

01:33:30,724 --> 01:33:31,204

Bill: right.

:

01:33:32,169 --> 01:33:32,679

Alex: Sims.

:

01:33:33,169 --> 01:33:35,029

And, you know, it's

just an incredible time.

:

01:33:35,029 --> 01:33:41,839

I would say to be a, a pilot,

a simmer, a flight school, just

:

01:33:42,019 --> 01:33:42,889

so many things are gonna be a

:

01:33:42,910 --> 01:33:43,430

Tiffany: startup?

:

01:33:44,139 --> 01:33:44,529

Alex: and,

:

01:33:44,684 --> 01:33:45,273

Bill: A startup

:

01:33:45,509 --> 01:33:45,759

Alex: and a

:

01:33:45,964 --> 01:33:47,394

Bill: let let's face it though.

:

01:33:47,414 --> 01:33:49,804

It's always a great time to be a pilot.

:

01:33:51,130 --> 01:33:51,480

Tiffany: It's true.

:

01:33:51,789 --> 01:33:53,318

Alex: It's always a

good time to be a pilot.

:

01:33:53,999 --> 01:33:54,369

Yeah,

:

01:33:54,514 --> 01:33:55,443

Bill: couldn't resist.

:

01:33:57,004 --> 01:33:57,604

Excellent.

:

01:33:57,644 --> 01:33:58,544

Oh, this is, this

:

01:33:58,568 --> 01:33:59,159

Alex: good to have.

:

01:33:59,254 --> 01:34:02,434

Bill: has been really fun and

really, really enlightening.

:

01:34:02,434 --> 01:34:04,894

So Alex, wonderful time.

:

01:34:05,084 --> 01:34:05,884

We appreciate it.

:

01:34:05,894 --> 01:34:07,104

We've held you long enough.

:

01:34:07,454 --> 01:34:08,584

Um, so we'll let you go.

:

01:34:08,603 --> 01:34:12,724

Anything that we forgot to ask or

didn't ask that we should have.

:

01:34:12,934 --> 01:34:14,094

You want to make sure we cover

:

01:34:14,889 --> 01:34:19,529

Alex: it just, well, it just

encouraged folks that they can,

:

01:34:19,589 --> 01:34:23,359

you know, follow along with what

we're up to over at airplane.

:

01:34:23,639 --> 01:34:25,818

team slash discord or slash blog.

:

01:34:25,818 --> 01:34:28,939

If they're curious, you

know, we, we love pilots.

:

01:34:28,939 --> 01:34:29,509

We love Simmers.

:

01:34:30,349 --> 01:34:35,443

talking to our customers, you know,

it's, it's, It's real important

:

01:34:35,454 --> 01:34:42,014

to us that pilots and aviators and

instructors continue to We want to

:

01:34:42,023 --> 01:34:43,594

see more people becoming pilots.

:

01:34:43,664 --> 01:34:45,384

We really care about this entire industry.

:

01:34:45,384 --> 01:34:49,544

I love flying and, you know, just

want to wish everybody to fly safe.

:

01:34:49,704 --> 01:34:52,004

It's been really good talking

to you, Bill and Tiffany.

:

01:34:52,344 --> 01:34:52,834

Bill: beautiful.

:

01:34:52,934 --> 01:34:53,115

Tiffany: awesome.

:

01:34:53,885 --> 01:34:54,915

Thank you so much, Alex.

:

01:34:54,915 --> 01:34:55,575

This was great.

:

01:34:55,985 --> 01:34:58,085

We look forward to seeing

you at Oshkosh next year.

:

01:34:58,665 --> 01:34:59,585

Are you going to have a booth?

:

01:34:59,924 --> 01:35:00,514

Alex: Likewise.

:

01:35:01,784 --> 01:35:04,894

I think we'd like to probably figure

out something like that the next

:

01:35:05,084 --> 01:35:05,334

Bill: Yeah.

:

01:35:05,504 --> 01:35:05,904

Excellent.

:

01:35:06,174 --> 01:35:07,364

Alex: it's probably

going to be a good time.

:

01:35:07,725 --> 01:35:07,915

Tiffany: I think so.

:

01:35:09,839 --> 01:35:10,469

Bill: Well, thanks again.

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About the Podcast

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The Student Pilot Cast
Learning to fly...in front of the world. A Podcast about flight training.

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About your host

Profile picture for Bill Williams

Bill Williams

Bill is a papa, a pilot, a geek, a diver, a sailor, a motorcycle rider, and a podcaster. He brings a long if sometimes interrupted history with both aviation and podcasting, along with passion for both to his podcasts. Currently working on his CFI, Bill is dedicated to advancing his skills and sharing his love of flying with others.

Bill hosts the popular Student Pilot Cast where he shares his flight training with the world, bringing the listener into the cockpit and more frighteningly, into his head, to share in the triumphs and the defeats of perpetually learning the art and science of flying.

More recently Bill is also co-hosting the Flight Line Podcast with Tiffany Wolf as they reunite after having been co-hosts on the reborn Pilotcast podcast in the earlier days of aviation podcasting.