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fully connected episode of the

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Practical AI podcast. This

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is a fully connected episode where we

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keep you connected with everything

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that's happening in the AI community,

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all the interesting and crazy news

0:58

out there, and hopefully a few

1:00

things that will help you level

1:02

up your machine learning game. My

1:04

name is Daniel Wightnack. I am

1:06

the founder and CEO at Prediction

1:08

Guard, and I'm joined as always

1:11

by my co-host Chris Benson, who

1:13

is a principal AI research engineer

1:15

at Lockheed Martin. How are you doing, Chris?

1:17

I'm doing great today, Daniel. How are you

1:19

doing? I am

1:22

doing well mentally,

1:24

a little bit less physically.

1:26

I ran a half

1:28

marathon yesterday, which was really

1:31

exciting, and the first sort

1:34

of running type event that

1:36

I've done personally. And

1:38

I have to say, my training was

1:41

going good for a while. I would

1:43

say the last couple months was not

1:45

going as well. And so let's

1:48

just say that I'm in a good amount of

1:50

pain today, but self-inflicted,

1:52

I guess. It is. I'm

1:55

sorry. I sympathize. I have done a

1:57

couple of half marathons, but it has been a while

1:59

since I've done it. I've done them and

2:01

I know that at the end of those I was

2:03

indefinitely You sound much better than

2:05

I did afterwards. I gotta tell you well, I've been

2:07

in bed most of the day Since

2:10

you and I can see each other but listeners

2:12

can't I will I will report that you look

2:14

very well for someone who just I have marathon.

2:16

I I look terrible at the time. I am

2:19

sitting in a chair not moving. So Yeah,

2:22

that's key. Excellent Well, I guess

2:24

someday it will be doing half

2:26

marathons and there'll be things like

2:29

robots running along beside us Maybe

2:31

powered by artificial general intelligence and you

2:34

know, they'll have their own I'm presuming

2:36

We don't have to compete against the

2:38

robots I'm I'm hoping because you

2:41

know, I I don't think I would

2:43

do very well or maybe I'll just

2:45

have some sort of automated or augmented

2:49

Knees or legs put in and I

2:51

can cyborg the Marathon,

2:53

you know, they've long had Meniscus

2:56

is the is the cushioning in your

2:58

knees. They've long had meniscus transplants,

3:00

but maybe they'll have like robotic

3:02

You know intelligent meniscus and like

3:05

it springs you up, you

3:07

know I'm a off or something like that

3:09

Nobody you'll have that edge and they'll have

3:11

to detect it then, you know the competition,

3:13

you know for everything being equal Who

3:16

knows where we're going on that but

3:18

you know, yeah speaking of autonomous systems

3:21

And you know in the spirit of

3:23

robots and stuff. I thought

3:25

I would kick us off by talking about The

3:29

I've been keeping track of kind of an ongoing

3:31

news story, but it popped up in the last

3:33

week or so Which is the

3:36

x62 a Vista, which is

3:39

it's a project that the Air Force has

3:42

been leading with a number of companies and

3:45

For full disclosure Lockheed Martin my employer

3:48

is involved though I personally have absolutely

3:50

nothing to do with this and

3:52

my information is only what's available publicly So

3:55

I just wanted to give my my

3:57

disclosure there before we got into but I've been following

3:59

the news stories on this because it

4:01

is super cool. It is an F-16

4:04

Fighting Falcon fighter plane,

4:07

which are, they've been around for a long time.

4:09

They're actually 50 years old this year, but

4:12

it's gone through multiple ownership. Lockheed Martin is

4:14

the owner of the F-16 now. And

4:17

it's kind of one of those for NATO

4:19

countries, kind of standard baseline

4:22

fighter planes. The

4:24

reason it's an X-62A versus

4:26

an F-16 in this case

4:29

is it has been enabled

4:32

with a fully autonomous AI autopilot

4:34

that's not only designed to fly

4:36

the plane, but flies the plane

4:38

in combat. And they have been

4:40

doing simulated tests for the past,

4:42

roughly the past year. I don't

4:44

have all the dates in front

4:47

of me and stuff. But

4:49

this last week it made a new splash because

4:52

in addition to the usual

4:54

human test pilot, which sits in the

4:56

cockpit but does nothing, they have manual

4:59

controls to override the AI. But on

5:01

all the tests, they have not needed the

5:03

test pilot to do anything because the AI

5:05

autopilot is so darn good. And this past

5:08

week, the Secretary of the United States Air

5:10

Force also flew in the

5:13

cockpit. It has two seats and flew in the front

5:15

seat with the test pilot in the back seat. Neither

5:18

human touching any controls while

5:20

they did a simulated combat

5:23

scenario in the sky with

5:25

other airplanes flying against,

5:27

you know, in a human controlled

5:29

airplane, human controlled airplanes against

5:31

other test pilots flying combat

5:34

scenarios. And rumor,

5:36

according to what the news reports

5:38

are, everything has just gone flawlessly.

5:41

It performs exceptionally well.

5:43

And it's just, you

5:45

know, it's one of those moments in time

5:47

where you realize this stuff, it's, you know,

5:49

we, we talk about models and often our

5:51

models are, you know, just in the cloud

5:54

and we're using them on apps and things

5:56

like that. But this is a type where

5:58

you have a model that It is in the

6:01

lingo out on the edge. It

6:03

is controlling an advanced piece of

6:05

machinery to a very high degree

6:07

of performance. We

6:10

kind of had the moment with Tesla cars doing

6:12

full auto, but now we're talking about

6:14

some of the most sophisticated

6:17

aircraft in the world, not

6:19

just little drones, but big

6:21

full-on fighter planes being

6:23

flown as well as any human or better

6:25

than any human fighter pilot in the world.

6:28

What do you think of that? I've talked to him for a

6:30

while, but I'd rather take him with

6:32

just the moment. It's really interesting in a

6:35

number of ways. I was thinking back to,

6:37

I guess it was last

6:40

month when I was in Boston and I

6:43

got to stop by the MIT

6:45

Media Lab for an event. They

6:47

had a panel with some various

6:49

luminaries. One of the panels was

6:51

an investor panel. They

6:54

were all talking. Some of the

6:56

questions were, of course, related to various

6:59

things about AI. It was an AI-focused

7:01

event, but I was struck by one

7:03

of the comments about this

7:06

next wave of innovation in AI.

7:09

The panelist was basically saying

7:11

that the days of just

7:13

being an innovator in AI as a model

7:17

builder, as a

7:19

foundation model builder, are in

7:22

some ways over. What's

7:24

really interesting now is embedding

7:27

AI everywhere in the physical

7:30

world. At the

7:32

edge, here's an example of that

7:34

happening in an airplane, of course,

7:36

but there's certainly other things happening

7:39

in the civilian space as well with

7:41

AI assistance in the retail

7:44

environment. Also, of course,

7:46

in cars and that sort of

7:48

thing. Retail

7:50

environments or manufacturing environments,

7:53

agriculture, machinery,

7:56

all of these sorts of things where AI is

7:58

going to be involved. embedded in all

8:00

of these physical spaces. That

8:02

brought up that in my mind as I

8:05

was thinking back to that event. But then

8:07

also thinking here, I

8:09

know you've made some comments

8:11

before being a pilot yourself,

8:13

just a civilian aircraft pilot

8:16

about the AI systems that

8:18

already exist, for example, for

8:21

commercial airliners and

8:23

other systems that actually can even

8:25

now do better in many

8:28

ways than human pilots. But

8:30

then there's always that, I guess,

8:32

fear on people's parts where it's

8:34

acceptable for a human to make

8:37

a mistake in such a scenario

8:39

because they could potentially be punished. Of

8:41

course, in air flight, maybe they wouldn't

8:44

survive if they made a mistake, which

8:46

would be really unfortunate. But

8:48

for a machine to make a mistake in

8:50

such a scenario is sort of unforgivable because

8:52

the machine shouldn't make a mistake. So

8:54

there's kind of this double standard that's

8:56

happening. Do you see that shifting or

8:58

changing at all with some of these

9:01

recent developments? I think it'll take longer

9:03

in the commercial airspace. And just to

9:05

address one quick thing, to the best

9:07

of my knowledge at this moment, there

9:09

are no AI systems authorized by the

9:11

FAA in the United States to fly

9:13

commercial airliners. But there's a lot of

9:15

interest in testing about those kinds of

9:17

systems that are out there. There's even,

9:19

I may be wrong about this, but

9:21

I believe it was MIT that has a

9:23

system that is designed for

9:26

that. It's not been deployed in production. It's

9:29

kind of an open system for

9:31

airliner navigation and such. But

9:33

there's a lot of work in this area. And certainly on

9:35

the military side, there's lots

9:37

and lots of constraints. So I don't

9:40

wanna represent it as like, oh, you

9:42

can do whatever you want. There's tons

9:44

and tons of gateways you

9:46

have to earn your way through in the testing.

9:49

But there is definitely a full

9:52

on interest in military circles

9:54

and defense circles about

9:57

using AI in just about

9:59

every conceivable. use case that you might

10:01

want to come up with on the ground in the air under

10:03

sea in space, you name it everything and

10:06

That's without getting sidetracked I spend a lot

10:09

of time in those scenarios in my day

10:11

job away from the podcast But

10:14

many things in the military

10:16

world are classified and you can't really talk about on

10:18

one of the really cool things about The

10:21

x62 a program is it's being done in the

10:23

light of day It's a

10:25

news story every time something news happens and you can go

10:27

and and search it and

10:29

find all sorts of Information

10:31

about it. It's interesting over

10:33

time if you over the last

10:35

few years I am

10:37

one of those people because I've seen

10:40

this a lot as a

10:42

pilot and as just a Non-pilot

10:44

I will trust myself to AI

10:46

autopilots and trust my family's lives

10:48

if it were to come to that Because

10:50

they're so darn good that I've seen them

10:52

back as far back as a

10:54

DARPA event that was public on YouTube in 2020

10:58

It was a simulator But the AI pilot

11:00

beat one of the best fighter pilot instructors

11:02

in the world an Air Force instructor Yeah

11:04

the equivalent of what people would know is

11:07

top gun in the Navy and just Amolish

11:09

the poor guy and that

11:11

was four years ago now and over four

11:13

years ago And so we've come you know,

11:15

that's the prehistoric times in AI, you know

11:17

in the way we think of AI So

11:20

I really do Think that

11:22

we're we're crossing some thresholds now

11:25

and really the thing that will hold us

11:27

back is the public becoming comfortable

11:30

enough to really You know embrace

11:32

the technology as that and I think one

11:34

of the before I draw

11:36

to an end and I'm not picking

11:38

on Boeing But the Boeing, you know

11:40

problems with the 737 max, which is

11:43

not an AI system They are automated

11:45

systems, but they're not AI systems Has

11:48

really shaken the public's trust

11:50

in automation in aircraft and

11:52

airliners And so there's

11:54

that will slow things down but

11:56

you know someday when we do

11:58

have FAA approved systems and the airliners

12:01

that we're all flying every day,

12:03

I think that we will be orders

12:05

of magnitude safer than we are with even

12:07

seasoned airline pilots today. I'm so sorry as

12:10

a pilot to say that to you pilots

12:12

out there. I don't mean that. I have

12:14

many good friends who are

12:16

in that occupation, but that's just the way AI

12:18

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12:32

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12:35

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12:37

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14:35

Chris, one of the things that I was

14:37

thinking about when you were bringing up this

14:39

story about the X-62

14:42

autonomous testing was

14:44

one of the comments you talked

14:46

about was the sort of regulations

14:48

and guardrails around the testing that

14:50

it's also happening in open. There's

14:53

regulations, especially in the airspace

14:55

about testing these vehicles and

14:57

that sort of thing. I

15:00

was remembering back I had a conversation

15:02

with breakfast

15:04

with a group that just

15:07

came out here to Purdue

15:09

University where I'm located. The

15:11

company is called Wind Racers and

15:14

they have sort of

15:16

commercial autonomous drones that

15:18

are really kind of mid-sized

15:21

drones that do like

15:24

mail remote or

15:26

rural mail routes or something like that. If

15:28

they send mail in the UK, they have

15:31

drones that take mail out to all

15:33

of these different islands in the UK

15:35

that need mail deliveries and that sort

15:37

of thing. But then also there's the

15:40

chance to use these for disaster

15:42

relief or humanitarian aid and

15:45

that sort of thing. I know

15:47

one of the things that they talked about

15:49

was just the struggle in finding ways to

15:53

test autonomous drones,

15:55

especially in the airspace,

15:58

to actually make some significant progress in

16:01

the R&D and testing and all that,

16:03

you actually have to be able to

16:05

take flights over significant distances and that

16:07

sort of thing. And here

16:10

you see, you know, these tests happening

16:12

on the military side. I know there's

16:14

differences kind of civilian

16:16

and government with the ability to

16:19

test things and availability of airspace

16:21

and all of that, but how

16:23

do you, as a pilot, maybe

16:25

you're maybe more familiar with some

16:27

of these regulations than

16:29

the rest of us are, how

16:31

do you see this technology being

16:34

able to develop over time with

16:38

such restrictions around testing and how

16:40

could that be eased up in

16:42

a reasonable way without

16:44

undue, you know, issues

16:47

and danger and that sort of thing.

16:49

Cause obviously if you have drones flying

16:51

over populated areas, that is

16:53

definitely an issue. But

16:56

at some point there's going to have to be

16:58

a drone fly over a populated area.

17:00

Indeed. And so, and to start off with,

17:02

I certainly am not an expert in that.

17:04

I have some very loose familiarity with the

17:07

process. Military, they have their own

17:10

dedicated air spaces. There's military airspace

17:12

and especially, it's all

17:14

over, but especially out West, places like Edwards

17:16

Air Force Base and a number of others

17:19

where you have literally, you know, hundreds of

17:21

square miles that you

17:23

can do testing in. And obviously there's

17:25

a long history of that already since

17:27

the dawn of flight. The FAA is

17:29

very aware, you know, of

17:32

the need to innovate on this. And so

17:34

they basically, you have to apply

17:36

for what you're trying to do and

17:38

show them that you've done

17:40

due diligence from the engineering safety, you know,

17:42

all the concerns about that. And

17:45

basically I follow a lot of aviation

17:47

news. So I've kind of read about a number of

17:49

these programs that have come into being,

17:51

and then they give you a little bit of

17:53

a leash and you can kind of, you have

17:55

to kind of earn your way through a number

17:58

of gateways, you know, where you're going. you

18:00

where you successfully do something in very

18:02

small scale, very small scope, and increase

18:04

your way into it. But it seems

18:06

to me that that is happening more

18:08

and more. And in some cases, if

18:10

there is a military utility

18:13

to doing that, then there

18:15

can be coordination also with

18:17

military and taking advantage of

18:19

military airspace to have more

18:21

room, things like that. So it

18:24

seems though, though, obviously, government

18:27

agencies are not the speediest

18:29

things, typically, that there are

18:31

opportunities for even private businesses

18:33

and stuff to get some support

18:36

in that way. They know it's coming. Yeah,

18:39

this is probably something

18:41

we could refer people back

18:43

to our previous episode

18:45

with Jake and others.

18:48

It's unlikely that we'll be seeing

18:51

the skies filled with weaponized

18:53

autonomous drones doing whatever they want.

18:55

There's a lot of

18:58

hopefully responsible people thinking about

19:00

these things. But the

19:03

main interesting piece here is

19:05

both on the commercial side

19:07

and on the military side,

19:09

the ability to increase safety

19:12

and decrease people, human

19:14

pilots being in dangerous

19:16

situations, I think it

19:18

seems to be the focus of a lot

19:21

of this. Now, you

19:23

know, there's probably all of those out there

19:25

that can imagine all sorts of scenarios of

19:28

misuse and all of those sorts of things.

19:30

But there's also in our

19:32

previous conversations with people, at least

19:34

I have some hope

19:36

that there's some reasonable

19:38

people and thoughtful people that

19:41

are part of these programs.

19:43

Yeah, just at risk of sounding

19:45

like an apologist, I point out to

19:47

people there are a lot of safeguards

19:50

to that point. I work in

19:52

defense. I come home. I

19:54

Mostly work from home, but I have my

19:56

family and my dog and everybody else who's

19:59

doing this whether. In the military or

20:01

whether they're civilian supporting that they have

20:03

their family and their kids and all

20:05

that. So on the notion that there's

20:07

like the dark military minds behind the

20:09

closed doors are in my experience of

20:11

fiction we all you know when we

20:13

get on the phone or even for

20:15

your business thing, we're talking about the

20:17

same things that everybody else talks about,

20:19

you know, the weekend and what? You

20:21

know, if my dog wasn't feeling well

20:24

and my kid with stay home from

20:26

school or whatever and so I'm very

20:28

encouraged and that way or it's normal.

20:30

People running these are and they have different

20:32

motivations obviously are depending on where the rat

20:34

and what organization there with but it's one

20:36

of their things that I get worried about

20:39

with a I going forward but that's not

20:41

one of of. Yeah, I'm might

20:43

refer people back to our episode

20:45

leading the charge on a I

20:47

A National Security with a General

20:50

Jackson a Ham. Really good episode

20:52

to yeah retired Us Air Force

20:54

So if you want to get

20:56

a sense of someone on the

20:58

was sort of leading the charge

21:01

on the inside for a good

21:03

long time then I would recommend

21:05

that episode from being a civilian

21:07

myself who is good to have

21:09

a chat with him. Yeah General

21:11

Shanahan is. Who's now retired is

21:14

both are. That was a recent episode

21:16

as we record this and was also

21:18

the original hard charger for a I

21:20

in the military an hour and is

21:22

in a A uniquely he still considered

21:24

even though he's retired to be one

21:26

of the top experts and influencers. Have

21:28

a hope people check that out. Yeah,

21:30

well. I don't know if this was

21:32

widespread news, but I thought it would

21:34

be a cool thing to highlight for

21:36

people. You. Know you're talking about

21:38

kind of this further testing and

21:41

I'm sure some of that testing

21:43

on the autonomous vehicle side involves.

21:45

Standards. And best practices and

21:48

frameworks. All of that's necessary

21:50

to really advance. A technology

21:52

from are in the to produce

21:54

type and otherwise and I think

21:57

that we're seeing also some of

21:59

that. On the. Enterprise.

22:02

Ai generative, Ai side of

22:04

things. So this last couple

22:07

weeks I was. Informed

22:09

about this project which is

22:11

now a project at the

22:13

Linux Foundation. In the project

22:15

is called the Open Platform

22:17

for Enterprise A I just

22:19

abbreviated to O P A

22:21

which seems like an unfortunate

22:23

and awkward acronym. The homicide

22:25

Her I don't I was

22:27

trying to think like, how

22:29

do I it via over

22:31

here Either that or know

22:33

that. See you avoiding the

22:35

obvious A high school. A

22:39

of doing it. The. I've been bought

22:41

the greatest of acronyms, but ah yeah,

22:43

the Linux Foundation has this ai and

22:46

data foundation, so if you're not familiar

22:48

with the Linux foundation, you can look

22:50

it up. But. This.

22:52

Enterprise Open platform for

22:54

enterprise Ai. Is. A

22:56

very collaborative initiative it seems

22:59

and just some of the

23:01

companies involved are kind of

23:03

was them out. Not all

23:05

of them but just to

23:07

give you a sense includes

23:09

Intel and any scale cloud

23:11

era data stacks, Domino Data

23:13

Lab hugging face many yo.

23:15

Zola, X A bunch of

23:17

different. Companies. That probably

23:20

your familiar with, certainly

23:22

ones that we've talked

23:24

about on this show

23:26

and. There's. A few

23:28

interesting elements of this.

23:31

Open platform for. Enterprise.

23:34

A I but the

23:36

general goal I think

23:38

is to enable and

23:41

facilitate. Or the way that

23:43

they frame it as aims to facilitate

23:45

and enable the development of flexible. Scale.

23:48

Of Bullets and Ai systems.

23:51

That. Harness the best open

23:53

source innovation from across the

23:55

ecosystem. And. That's kind

23:57

of vague in terms of the.

24:00

The where they're going with this, but

24:02

I think if you look sort of

24:04

a little bit deeper I think there's

24:06

some really interesting things of where this

24:08

could lead one as they recognize certain.

24:11

Common. And developing.

24:14

Archetypes. Or I'm. Main.

24:16

Use cases where people are using

24:18

two hundred of a I, for

24:21

example, the rag work flow retrieval,

24:23

augmented generation work flow and they're

24:25

kind of take that rag work

24:28

flow and are creating blueprints for

24:30

the various pieces that are involved

24:32

in a an industry standard kind

24:35

of advance. Rag work for not

24:37

just stay naive rag work flow

24:39

that you might play around with

24:42

on your laptop or something that

24:44

could be deployed in the Enterprise.

24:46

And so they have some blueprints or

24:48

kind of architecture type of things. I

24:50

think they'll be more of that that

24:53

will be developed and then those architectures

24:55

or blueprints have certain components within them.

24:57

For. Example: Ah, retrieve or system

24:59

and abetting model or guard

25:02

rails for models or fine

25:04

tuning systems are a vector

25:06

database and then if you

25:08

follow the link to the

25:10

get hub related to the

25:12

o p a project appear

25:14

project whatever you wanna call

25:16

it. I notice some really

25:18

interesting kind of a few

25:21

categories of some things that

25:23

aren't quite complete there yet

25:25

but that they're building and

25:27

public. And those are

25:29

both examples of implementing these

25:31

sort of reference implementations of

25:33

industry standard ways of going

25:35

about doing certain things so

25:37

like Sat with your dogs,

25:39

cogeneration assistance the you can

25:41

plug into. Visual. Studio Code

25:44

Document Summary Visual: A question

25:46

and answer. Am those reference

25:48

implementations include open source ways of

25:51

doing these different things in a

25:53

kind of industry standard way. Another

25:55

one, as they have, it seems

25:58

like they're developing a. These

26:00

of micro open micro services that

26:02

could be plugged and to do

26:05

various of these components. and then

26:07

finally I said of evaluations. So

26:09

they have a repo valuation benchmark

26:12

and scorecard. Targeting. Performance on

26:14

throughput and latency accuracy Unpopular evaluation

26:16

harnesses for safety hallucination Other things

26:18

like that, so there seems to

26:21

all of that put together. I

26:23

know there was a little bit

26:25

rambling, but it seems like they're

26:27

kind of focus here on these

26:29

blueprints. Reference. Implementations of

26:32

things represented in those blueprints,

26:34

and then industry kind of

26:37

enterprise level evaluations for performance

26:39

and issues within these systems,

26:42

that sort of thing, So

26:44

this definitely seems encouraging. To.

26:47

See a lot of collaboration on this and

26:49

see the support from the Linux Foundation. Yeah.

26:51

I mean with the Linux Foundation being

26:54

in a one of the most reputable

26:56

open source organizations in the world certainly

26:58

the top few, it's really important that

27:01

finishes like this come into being in.

27:03

The reason is that in the business

27:05

world I know you and your company

27:07

and I certainly is. I'm talking to

27:10

people in different companies, everyone out there

27:12

is trying to find their own way

27:14

and to implementing. Jenner they I solutions

27:16

and how do you put it together?

27:19

had you architect it? I have my

27:21

own thoughts. Around that and and I

27:23

know the company I work at has

27:25

its own thoughts around that and I

27:27

end up talking to people of different

27:29

organizations and they're struggling with many of

27:31

the same problems, but they come to

27:33

their own solutions you know of based

27:35

on however their team wants to approach

27:37

it and as we know from other

27:40

in a before Gen Vi and even

27:42

before A I came along, it's an

27:44

early point in every growth. You know

27:46

development of every are you know whether

27:48

in software, anything else, where you have

27:50

everyone kind of going off. and doing

27:52

their own thing but they realize that that

27:54

itself or while it might solve the immediate

27:56

it's they need it creates a whole new

27:58

set of problems as the after grow and

28:00

integrate with other organizations. So seeing

28:03

what the open platform for enterprise AI

28:05

has to offer, it looks

28:07

very promising. And I would, I

28:09

would encourage organizations out there to

28:12

take a look at it and whether

28:14

you adopt it or not, maybe it

28:16

helps frame how you're choosing to solve

28:18

problems in a way that might make

28:20

situations you're in down the road that you're not

28:22

thinking about yet a little bit easier to cope

28:25

with. Well, Chris, as we

28:27

kind of look back to the last sets

28:29

of newsworthy AI stuff happening

28:33

in all over the place, both

28:36

in terms of large language models, Gen

28:38

AI and not Gen AI,

28:40

one of the themes recently that

28:42

it seems like has been

28:45

happening and kind of in getting

28:48

into its prime is

28:51

video generation. I

28:53

don't know if you've been following this

28:55

sort of stuff, but I

28:57

know that there was, I saw

28:59

something from Microsoft. I saw

29:02

something from Alibaba. I think,

29:05

of course, there was the open

29:07

AI video generation stuff. There's

29:09

been things from runway ML

29:12

and yeah. So what are

29:15

your general thoughts on where all of

29:17

this video generation stuff is happening or

29:19

is going? I had a couple of

29:21

thoughts there. I don't think it should

29:23

surprise anyone at this point who's following

29:25

the industry. You know, when we

29:28

were doing our thoughts for 2024 last

29:30

year, we were

29:32

talking about this would surely come next, you

29:34

know, because we were willing to still imagery

29:36

and stuff and the rate that we're seeing

29:39

things progress from a quality standpoint,

29:41

you know, when it's going so fast,

29:43

you know, it was not long ago that

29:46

open AI released Soros. That

29:49

wasn't long ago at all. And we were kind of

29:51

going, wow, look at, you know, it's

29:53

here and look at this first thing. And now

29:55

there are many options available after just a few

29:57

weeks. And I think I've

30:00

been somewhat amused to look at

30:02

the reactions in public about people

30:05

and the concerns about

30:08

safety and you know deep fakes

30:10

being so much better now

30:12

in two thousand twenty four than they were a year ago

30:14

right now. We're gonna have to

30:16

adjust and take it in and recognize

30:18

the utility and come up with some

30:20

safeguards for it. I guess it

30:22

was kind of obvious to us and

30:24

those of us who are following this weekend and

30:26

we got that we be here and so now

30:28

we're here. I'm waiting to see

30:30

some of the more interesting creative productive things that people

30:32

are going to put this to I'm

30:34

really looking forward at this point

30:37

to seeing some utility coming

30:39

from it that's meaningful. And

30:41

yeah, just so people can go

30:44

out there and look at these

30:46

things. One is called Vasa one,

30:49

which is the one from Microsoft

30:51

research. And

30:54

the kind of tagline there is

30:56

life like audio driven talking faces

30:58

generated in real time. This was

31:00

an interesting one. It kind of

31:02

almost reminded me of the

31:05

sort of videos that I've seen from

31:07

Cynthia and these other companies that kind

31:09

of help create talking heads

31:12

essentially for marketing videos or

31:14

training videos, the sort of

31:16

thing. And very

31:18

impressive stuff there might

31:21

have seen something going through on Twitter,

31:23

LinkedIn with, you know, people always try

31:26

to make the Mona Lisa face talk

31:28

and I felt I was one of

31:30

their examples that they had, which,

31:33

you know, that seems to be a sort of

31:35

given that you try that if you're working in

31:37

this space. And the most recent one wasn't actually

31:39

anywhere close to being the best stuff.

31:41

I saw that maybe

31:45

a week ago and it was pretty cheesy, but

31:48

I mean we're truly arrived in 2024. If

31:50

you can have video now, Certainly

31:52

at least talking head video that is

31:54

indistinguishable from a person, you would be

31:56

very if you were to put, you

31:58

know, compare it. Have two or

32:01

three people and have two or three

32:03

I generate ones. mix them up and

32:05

have people choose which ones are which

32:07

of. I know that I probably could

32:09

not do that successfully. a number. I

32:11

might get lucky and pick one or

32:14

two, but we're getting there and so

32:16

far as I really am curious to

32:18

see how these are put it that

32:20

like beyond the novelty of it's of

32:22

seeing I'm finally arriving. After talking about

32:25

this stuff for a while, I really

32:27

am curious to see how people use

32:29

them for. You know we like to

32:31

talk about Ai for good. I really

32:33

want to see instead of people worrying

32:35

about this are strictly about the security

32:37

concern which is legit. I'd like to

32:39

see some people do some amazing things

32:41

for it. Ah that is gonna benefit

32:43

people in humility at large and I'm

32:45

excited to see this use cases and

32:47

if anybody out there has something please

32:50

point us to it can cite those

32:52

are these cases on Wait to see?

32:54

Yeah and the one if if people

32:56

are searching from Ali Baba's is called

32:58

email or I guess he is. He

33:00

am oh I assume emo

33:03

guy or Ali Baba's email

33:05

and Vasa. From Microsoft if

33:07

you wanna if you wanna take a

33:09

closer look. It kind of seems to

33:11

me chris like a time when. You.

33:14

Know when Dolly came out the first

33:16

one and then there was. It was

33:18

like Dolly stable, diffuse and and that

33:20

the just seem to be the snowball

33:23

really quickly of image sooner. he said

33:25

things. It seems like we're in a

33:27

similar cycle right now with the video

33:29

to nourish and. Stuff.

33:32

And then eventually you know it'll be integrated

33:34

into our chat interfaces and other things that

33:36

I don't think it's going to be long

33:38

at all to get to that point. I

33:40

think we're going to be amazed at how

33:42

fast as get integrated there are because every

33:44

time they keep building on themselves in your

33:46

we have. The one thing we've noticed over

33:48

the last two years is the acceleration in

33:50

the development. I'm we will say something will

33:52

come out and the next year and then

33:54

it comes out two months later and you

33:57

know couple a times said well we predicted

33:59

a prefer hot. The tiring on that?

34:01

I think it's gonna happen pretty darn

34:03

quick. And and to illustrate that there

34:05

was not specific to the suitcase hugging

34:08

face, announce this past week that they

34:10

had crossed over the one million mark.

34:12

There's One million The I Models hosted

34:15

hugging Face Yes, Congratulations to Ah, Hugging

34:17

Face and and the team there that's

34:19

amazing All those you know. it wasn't

34:21

that long ago where they were nowhere

34:24

close to a million, but they keeps

34:26

accelerating and so who hit and they'll

34:28

hit ten million in. No time, I'm

34:31

sure. But on to your point earlier

34:33

that I think it's not just going

34:35

to be seeing these new technologies coming

34:37

out where we're looking at the said

34:39

the demo but I think for like

34:42

the second half of Twenty Twenty Four

34:44

and into Twenty Twenty Five will be

34:46

such a huge push and getting models

34:48

integrated into real world scenarios. You know

34:50

what we would like to say as

34:53

at the edge in all sorts of

34:55

different contacts and are those that's really

34:57

quite honestly what I'm excited to see.

35:00

Is if instead of just a talking head

35:02

with the audio that's indiscernible I I want

35:04

to see that ah and some good contacts

35:06

that are in places that were not used

35:08

to sing on that make a big difference

35:10

and said that will be a pretty cool

35:12

for me that will be of a cooler

35:14

milestone than just sing the demo upfront. Yeah.

35:17

It does seem like that

35:19

There's some big possibilities in

35:21

even spaces like education and

35:24

other places where hey you

35:26

have some tax contents, you

35:28

have some sort of cure

35:31

a son in place but

35:33

creating. Very. Much I'm

35:35

appealing and. Realistic

35:38

looking, Educational content

35:41

that would fit a certain scenarios

35:43

cause there's tons of sort of

35:45

self study stuff online. Are

35:48

some of it has better

35:50

video quality. Than. Others, but

35:52

also some of it's at a

35:55

certain level. that's. You. Know

35:57

if you have one set of

35:59

content a perfect. The records may

36:01

be a video course or something

36:03

that lasts. Me: You'd have to

36:05

watch it for an hour every

36:07

day for many weeks, maybe. But

36:09

if you can read purpose some

36:11

of that content to. Answer

36:14

questions and create engaging, Courses.

36:17

In. Different. Shorter forms

36:19

or four different age levels and

36:21

that sort of thing and some

36:24

of that was able to still

36:26

be video, still be engaging, but

36:28

not take a huge amount of

36:30

video production. To. Create, which

36:32

is very expensive and time consuming. I could

36:34

see a lot of possibility there is probably

36:36

many others Id love to hear. From.

36:39

Our Listeners: If they have ideas about

36:41

this, we'd love to hear about them.

36:43

Inner Slack Channel if you wanna join

36:45

or elsewhere. Just. To illustrate that

36:47

for a moment or and we talk

36:50

we know we talked about education use

36:52

cases many times. those are and how

36:54

it intersects with traditional education in a

36:56

like i have a daughter in middle

36:59

school. Ah and also you know things

37:01

like continue education for grown ups You

37:03

know that are continuing through this ever

37:05

changing world that are the you know

37:08

constitutes our careers but it's very easy

37:10

to leap from. You know the Vassar

37:12

example that we're talking about with the

37:14

Talking Face is being generated Real? Time

37:17

as they know and thinking. Every

37:19

kid in school in addition to

37:21

you know potentially it as we

37:23

as Things are friends, you sing

37:25

forward and we still have traditional

37:27

educational paradigms that most kids are

37:29

involved in. But maybe every kid

37:31

has their own other own personal

37:33

teacher in addition to a classroom

37:35

teacher. And that personal teacher explains

37:37

the mass in a way that

37:39

that student understands compared to the

37:41

student next to them, when you

37:43

get a lot of personalization and

37:45

support that way that. would be wonderful

37:47

to see that and so kids aren't

37:49

left behind and if you don't understand

37:51

the with teachers explaining it you don't

37:53

have to struggle because you already have

37:55

your personal assistant says there's many many

37:57

thousands of use cases along these lines

38:00

So that's the kind of thing that I'm pretty excited about

38:02

for the future. Cool. Yeah Well

38:04

as we kind of draw things to

38:06

a bit of a close here We

38:09

normally tried to provide a learning

38:11

resource for people in these fully

38:13

connected episodes and I want

38:16

to share one today We've been doing

38:18

a bit of experimentation of our own

38:20

Chris with these practical AI webinars These

38:23

I think what we've been calling them gen AI

38:26

mastery. So we've done two at this point One

38:29

related to text to sequel and

38:32

one related to private chat

38:35

UIs and I think

38:37

it's been a good experience so far at

38:39

least to motivate us to do do it

38:41

a bit more And we're

38:43

really trying to make these

38:45

webinars a live good

38:48

learning experience for

38:50

people and And something

38:52

where we have some hands-on, you

38:54

know A visual component with some

38:56

hands-on that you don't kind of

38:58

get in just the audio podcast

39:00

scenario so we we do

39:02

have another one of these planned and I

39:06

would highly recommend that that

39:08

you go to tiny URL

39:10

comm slash gen AI mastery

39:13

three tiny URL comm

39:16

slash gen AI Dash mastery three and

39:18

we'll put that in the show notes

39:20

as well and sign up for this

39:22

next one It's gonna be about multimodal

39:25

AI and we're finalizing the guests But

39:28

I already I think I know who they're

39:30

gonna be and it's gonna be a sort

39:32

of rock star They're helping

39:34

us learn about multimodal AI doing

39:36

cool things with video as we've

39:39

been talking here but also imagery

39:41

and Kind of tying together text

39:43

prompts in there as well for

39:46

kind of multimodal rag sort of

39:48

systems So if you're interested

39:50

in that definitely sign up, it's gonna

39:52

be it's gonna be a great experience So we'll have

39:54

that link in the show notes and look forward to

39:57

seeing everyone there Yeah, it's a lot of fun to

39:59

do this session because it's live real time

40:01

and everybody can see everybody else in

40:03

the chat and there's real time communications

40:05

as we're doing them make

40:08

it pretty special. Yep. All right,

40:10

Chris. Well, it's been fun. I hope you

40:12

can enjoy the rest of your weekend and

40:14

we'll talk to you soon. Take it easy,

40:16

Daniel. All

40:25

right, that is Practical AI for

40:27

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40:29

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