0:22

Welcome to Unsupervised Learning, a security,

0:24

AI and meaning focused podcast that

0:26

looks at how best to thrive as humans in

0:28

a post AI world. It combines

0:31

original ideas, analysis, and mental

0:33

models to bring not just the news,

0:35

but why it matters and how to respond.

0:42

All right. So the first thing for this week

0:44

is I finally turned my 9000

0:47

word I predictions essay into

0:49

an actual video. So if you click on this

0:51

thing all right I'm going to try to do

0:53

something crazy right now I'm going to try.

0:56

This is the whole video I

0:59

go through. I thought it was going to be like 30 minutes.

1:01

I'm like, knows what we want because it has

1:03

all the prefaces in, it knows our journal,

1:05

it knows all the stuff that we plus like

1:07

two hours of editing, which I never should have done.

1:09

But anyway, it is a full

1:11

walkthrough of the illustrated

1:14

essay, and I even give

1:16

a lot more sort of expansion

1:19

narration on top of the text

1:21

that's in the essay, so it's quite good, if

1:23

I do say so myself. I've had a lot of people

1:25

say they enjoyed it, so I would

1:27

say, go check that out. It gets

1:29

me excited to even think about it. Talk about it. It's

1:32

like the fun stuff. Plus I remember

1:34

like doing the art. It's just super

1:36

good time. Okay. Security. Yeah. But

1:38

so go check out the video. All right. Security.

1:40

So Israel's top spy,

1:43

chief Jose Ariel,

1:45

accidentally revealed his identity

1:47

through an Amazon book sale. So I guess we're

1:49

just doxing him now. That's rude.

1:51

Well, I guess he's not going to be that anymore, because

1:54

they're going to be like, you obviously can't do this. So they

1:56

probably got rid of him and replaced him with someone

1:58

who is still anonymous. So

2:00

now he's no longer the spy chief. He's just

2:03

a guy doing an Amazon book sale. All right,

2:05

cvn, Nvda databases are struggling.

2:08

Um, it's causing gaps and inaccuracies.

2:11

So somebody needs to fix that. Uh,

2:13

criminals in Montreal are using Apple's

2:15

AirTags to track and steal cars.

2:17

And police are using Apple's

2:19

AirTags to track criminals. So

2:22

a lot of AirTag use on

2:24

both sides of the fence there. And this one's

2:26

super cool. This sponsor I want to talk about this one

2:28

because I'm actually advising for them the first

2:30

AI SoC analyst that autonomously

2:33

investigates alerts. This thing will

2:35

pull alerts. I've seen this live

2:37

pull alerts. And this is a sponsor, by

2:39

the way. Sponsor. And I'm an advisor for them.

2:42

So I'm just excited about them. It's

2:44

called drop zone AI. So you

2:46

take an alert from anywhere in your stack,

2:48

some tool that you have that produces an alert

2:50

like an endpoint cloud doesn't

2:52

matter. And it

2:54

takes alerts from your environment and performs

2:57

autonomous. It basically goes and starts

2:59

researching exactly like a human. It's

3:01

like starts digging in, boom, get some results

3:04

from that lookup and that investigation

3:06

takes that goes to the next step and

3:08

just starts doing multiple steps, just

3:10

like a regular SoC analyst, just like a human.

3:13

And once it gets done, it puts that all

3:15

together and generates a decision

3:17

ready report. So you could

3:19

basically use that. And

3:22

it's basically exactly as if you had got

3:24

that from a SoC analyst. And you can make a decision

3:26

based on that. And it's no playbooks,

3:29

no code, no prompts required.

3:31

It just you feed it alerts and

3:33

it goes and does investigations and brings

3:35

back a report. It's absolutely insane.

3:38

It's exactly what I've been talking about as

3:40

being like how AI is most

3:42

going to affect security.

3:45

And I've been saying for the longest time

3:47

it's all going to be agent based. And that's exactly

3:49

what this is. And like I said, it's so good.

3:51

I just became an advisor and strop sonar

3:53

AI and you could actually go and see a demo

3:56

of it. Working on a real alert.

3:58

Panera's week long incident

4:00

was, in fact, a ransomware attack.

4:03

Cece's new High Risk Communities webpage

4:05

offers a bunch of guides and volunteer

4:07

support and discounted tools, thanks

4:10

to Defender Fee for sponsoring as well.

4:12

Israel's military used an AI named

4:14

lavender to pinpoint 37,000

4:17

potential Hamas targets, and that's

4:19

definitely getting people pretty upset about that,

4:21

because it's one thing to identify someone

4:23

and do further investigation. It's another thing

4:26

if you're identifying and then like targeting.

4:28

And again, I don't know if that's actually happening.

4:30

I don't know the degree they're trusting

4:32

this targeting that's coming up from lavender.

4:35

I don't know if they're going directly to

4:37

attacks or killing or anything

4:39

like that. But the point is it's

4:41

worth having a conversation about what they're

4:43

doing with it. Given the fact that

4:46

I can be super fast and

4:48

super accurate, but it can also have a lot of flaws,

4:50

and the more serious you're taking the results,

4:53

the more important those flaws are, right? Technology.

4:55

There's a rumor that Sam Altman and Johnny IV

4:58

are building some sort of handheld device

5:00

through a new secret company. Who knows if

5:02

that's a real or not. It sounds

5:05

real to me because we know that Johnny IV is

5:07

actually working with them. We know he's a design

5:09

person. We know we need these types

5:11

of devices. So it makes sense to me.

5:13

OpenAI released improved ways

5:16

of doing fine tuning. Uh, new

5:18

paper shows that adding more agents to

5:20

large language models boosts their performance.

5:22

How could it not? How could it not?

5:24

I mean, like like I've been telling

5:26

everyone agents is the way, agents

5:29

is the way this is all going to move forward. And

5:31

then each individual agent when it

5:33

gets smarter because the AI models improve,

5:35

that just makes the whole thing smarter. But the way

5:38

to get ultimately smart and actually pass

5:40

humans is to have that combination

5:42

of agents working together. That system

5:45

is what's smart. It's the same as our brain is

5:47

no different than our brain. Our brain has a whole bunch

5:49

of areas, each individually

5:52

only do kind of one thing, and

5:54

they're not very smart by themselves.

5:56

The whole thing that's made it smart over

5:58

all these millions of years is the fact

6:00

that they work together and they're sharing

6:02

information, and it's like it's a system.

6:05

The system is what makes us smart. And

6:07

it's going to be no different with agents.

6:09

Now, eventually you might have an AI

6:12

that's just one agent or one

6:14

model or one agent or whatever.

6:16

And it's so smart. It's just smart by itself

6:18

because it's different than a human. But the

6:20

way we're first going to get to AGI, mark

6:23

my words, is going to be through a system

6:25

of AI components working together.

6:27

And I've got a blog on that somewhere. New paper explores

6:29

how I might be leading us towards

6:32

knowledge collapse by oversimplifying

6:34

complex information. I like that,

6:36

but I don't think the complex information

6:38

goes away. Just because somebody is

6:40

simplifying or summarizing

6:43

complex information, it doesn't mean

6:45

we have to stop feeding the AI

6:48

the original raw form. One

6:50

doesn't have to supplant the other, and

6:52

we could just ask for the long form. We can

6:54

ask for the short form. I don't see that as a

6:56

trade off us is trying to get South Korea to

6:58

stop exporting chipmaking tools

7:00

to China, US testing, energy

7:03

storage and heated sand. This

7:05

tech is like trippy to me. Energy

7:07

storage and heated sand 135MW

7:12

of power output for five days

7:14

straight and Aura's rolling

7:16

out symptom radar. They're not calling it illness

7:18

detection for obvious reasons. I

7:20

haven't looked to my app to see if I have that yet.

7:23

I do have an aura though. Okay, Amazon

7:25

is ditching its Cashierless walkout

7:27

technology is kind of sad. I guess

7:29

it's too early, but they're switching to something

7:32

a little more normal, like a hybrid humans.

7:35

New studies are showing the wealthy are starting to have

7:37

more kids than the poor. Again,

7:39

need lots of studies to show that's actually

7:41

true, but interesting trend. NASA

7:43

is doing live streaming the eclipse. I watched it,

7:45

it was super cool. It was actually

7:47

moving through multiple cities and you would see

7:50

each person, each city as

7:52

it was moving. It would go to the full

7:54

totality and everyone would freak out.

7:56

It was quite cool. It was a very cool stream.

7:58

TSMC did not take much damage

8:01

at all. They were actually only down for like

8:03

a day and they went back to start

8:05

full production. And it's because their

8:07

buildings have some really cool stabilization

8:09

tech that allows them to not get too

8:11

messed up from earthquakes. However,

8:14

the earthquake was on the other side of the island,

8:16

so who knows if it's a bigger

8:18

like it was an eight and it was nearby.

8:20

I'm not sure the buildings would be

8:22

able to handle that, but who knows. Israeli

8:24

military dismissed two senior officers

8:26

and reprimanded three others for an

8:28

airstrike that mistakenly killed World

8:31

Central Kitchen volunteers in Gaza.

8:33

The UK's exporting workers

8:35

to fill higher paying US jobs

8:38

and US venture capital investments

8:40

went down $36.6 billion

8:43

in 2024. Had a really cool

8:45

conversation with Mike private from Return

8:47

on Security about these overall economic

8:50

trends, especially around cybersecurity,

8:52

and that will go up soon. McKinsey

8:54

is offering UK employee UK

8:56

employees nine months of pay to voluntarily

8:59

leave McKinsey. Gen Z is going

9:01

for trades like welding and plumbing over

9:03

college and student debt, and home insurers

9:05

are now using aerial images from

9:08

satellites to decide who

9:10

gets dropped from coverage. I assume that's

9:12

because maybe somebody's building something

9:14

in their backyard, or they have

9:16

too many cars. Like, I'm not sure what would be

9:19

on the policy that they'd be able to see in a satellite

9:21

photo, maybe add ons to the house

9:23

or something, I don't know. And all right,

9:25

got a couple cool ideas here. Another

9:27

view of imposter syndrome. So somebody

9:29

said outwork your imposter

9:31

syndrome. That was the post outwork your

9:34

imposter syndrome. And I'm, like, working

9:36

harder isn't the solution. In my opinion,

9:38

the solution is to work on bigger

9:40

problems that are super important

9:42

to solve. That way your focus

9:44

isn't internal, it's actually external.

9:47

And I actually go into this, so I'm going

9:49

to go ahead and open this up. So I

9:51

say framed this way, imposter syndrome is

9:53

ultimately a problem of thinking too much internally

9:55

versus externally. Because you're thinking how

9:58

do I compare to them? What do they think

10:00

of me? Right. And so the solution I

10:02

think is to. Focus

10:05

on. Something

10:08

outside of you, right? Stop

10:10

putting the focus on yourself. How

10:12

do I compare? What do they think of me?

10:15

That's thinking about yourself. Instead,

10:17

focus on the problem. And now you

10:19

won't really have imposter syndrome because

10:21

you're thinking about, like, what am I doing

10:23

that's useful to help me with this really

10:25

big problem, which has nothing to do with me.

10:27

It's about me working on that

10:30

thing. So instead, focus on the problem

10:32

and how to fix it. And this also works

10:34

for happiness. It doesn't come from focusing on self,

10:36

it comes from focusing on other. So

10:38

that was that piece there. And

10:40

this one's really interesting. It's the first time

10:42

I've ever seen Tyler Cohen be wrong. It's

10:44

like one of the smartest people that I know of

10:47

on the planet. And he had

10:49

Jonathan Height on and

10:51

Jonathan High was talking about how bad

10:53

social media is for young

10:56

girls and how

10:58

I could potentially make that worse and everything.

11:00

And Tyler Cohen is like, don't worry about

11:02

it. AI is going to solve this because

11:05

I is going to summarize everything, and

11:07

the summarization of of social

11:09

media is going to solve this problem and

11:11

fix it. And I'm like,

11:14

how are you not seeing this now?

11:16

Jonathan didn't have this point, but

11:18

I'm going to make this point right now. That is how

11:20

Tyler Cohen is going to use

11:23

AI, right? It's how I'm using AI right

11:25

now, and it's how, you know, Jonathan's probably

11:27

going to use it as well. Summarization of

11:29

content. So you're just getting the thing.

11:31

And that might actually take you away from being

11:34

caught up in like, oh he said she said

11:36

and all the drama or toxicity or whatever.

11:38

Well that's fine. And that again,

11:40

that's how they're going to use it. That's how a

11:42

whole bunch of intellectual people who have made

11:44

it in life and are older are probably

11:46

going to use it, but not for young

11:49

people consuming viral and toxic content,

11:51

because for them, the content itself is the

11:53

point, not the summary. And here's

11:55

my example of this. Does Tyler

11:58

think I will send people who

12:00

love stand up comedy a summary of

12:02

the jokes made in a given

12:04

standup as a substitute for going

12:06

to actual comedy shows. And I've got

12:09

I've got an I summary here. Here's your summary

12:11

of this standup. There were three jokes on

12:13

women in stereotypes, four jokes on

12:15

how clumsy the comedian is

12:18

to playful racist jokes. Two hecklers

12:20

were addressed. Applause was three

12:22

out of five compared to other performers.

12:24

We hope you've enjoyed this hilarious

12:26

I summary from comics I.

12:29

Does that work for comedy? No,

12:31

that doesn't work for comedy. And it won't work

12:33

for young kids consuming viral or

12:35

toxic content unless you have

12:37

some sort of like draconic like,

12:40

I guess, massive control

12:42

where they weren't actually allowed

12:44

to go to the real thing. They

12:46

couldn't go to TikTok, they can't go to Instagram,

12:49

and all they get is the stupid summary.

12:51

Nobody would. They they wouldn't even care about

12:53

the summary. I mean, that's not even going to be a thing.

12:55

Nobody cares. And if

12:58

it did, they wouldn't use it. And if

13:00

they had the option or if they had both,

13:02

they wouldn't choose the summaries. They would

13:04

not use the summaries at all, and they would just go to the

13:06

original thing. Now that being said,

13:08

it is Tyler Cohen. So there's

13:10

a chance that I didn't understand what he was saying.

13:13

And also Jonathan definitely didn't either.

13:15

So he could be misunderstanding Tyler's

13:17

point. So I want to offer him that.

13:19

There's also the other thing, which is you

13:21

might just be right, and I'm just wrong.

13:23

Now, I wouldn't normally say that because I

13:25

think fairly highly of my thinking

13:27

capabilities, but it's Tyler Cohen,

13:29

so I'm leaving that window a little

13:32

more open than usual. All right. Deep faked

13:34

content summaries. Oh, yeah. This is crazy.

13:36

So I don't know. I don't know if I woke up with this

13:38

idea. I think the main interface

13:41

that we're about to have for content,

13:43

let's say, okay, I got buddies

13:45

who make content. John Hammond makes content.

13:48

Jason Haddix makes content. Clint

13:50

Gibbler makes content. So they're putting out,

13:53

let's say they're putting out videos, they're putting out

13:55

text, they're doing live talks.

13:57

They're doing all these different things, different mediums,

13:59

different formats. I think

14:01

what's going to be happening

14:04

very soon is let's

14:06

do the R version, even though we don't have

14:08

R yet. The earlier version will just

14:10

be little videos on your phone. But let's

14:12

do the R version or the R version

14:14

combined with a digital assistant, which

14:16

is AI in your head or in your

14:18

mobile device. So it's essentially you say,

14:20

hey, look, what is Jason been up

14:22

to? What is John been up to? What is Clint

14:24

been up to? And it will actually

14:27

deepfake them okay. Because it knows

14:29

how much time I have. Let's say

14:31

I want a two minute summary. It will

14:33

take the long presentation

14:35

that Jason is going to do. Jason is getting

14:37

ready to do an AI talk called Red purple,

14:39

blue AI. Let's say it's actually it

14:41

is like it's a class. Oh, by the way, you should go sign

14:43

up for this class. His class is called red

14:46

purple blue I it's

14:48

going to be an amazing class. I've heard a lot about it.

14:50

I'm going to be in it as well. But for

14:52

example, let's say he gives a talk about that

14:54

a public talk. The other one's not public. But

14:56

let's say he gives a talk about that. Actually he's

14:58

doing a space con coming up soon.

15:01

So that's a good example. Let's say I don't have the

15:03

one hour or the two hours to watch that. I only

15:05

have two minutes. I'm about to get on a train where I don't

15:07

have any connection. Whatever it's going

15:09

to make, Jason and Jason

15:11

is going to. Teach me what he covered,

15:13

but he's going to do it in 30s or he's

15:15

going to do it in 60s. It's going

15:17

to be a deepfake of Jason doing

15:20

Jason's own content. Same for John.

15:22

John Hammond has a thing about this new piece of

15:24

malware. Clint has this new thing about

15:26

this new tool that he made or that he

15:28

saw, and he's talking about deepfakes

15:30

are going to allow the actual

15:33

creator to scale their

15:35

delivery of their content as

15:37

a video to any size

15:40

chunk that the consumer wants to see.

15:42

Give me a ten second summary. Give me a 32nd

15:44

summary. Give me a one minute summary,

15:47

a two minute summary, a ten minute summary, whatever.

15:49

But it will dynamically write the

15:51

content, which is a summary

15:53

of the content, which smashes

15:55

it down to that size, and then it will

15:57

perfectly deepfake that

15:59

creator and the mouth

16:02

will match, the mouth will perfectly

16:04

match. It'll look exactly

16:06

or almost exactly and eventually

16:08

exactly like the creator. Now,

16:10

why would the creator want to do that? Because it's

16:13

still their content, okay? It's still their content.

16:15

It's not the original raw form, but

16:17

in a lot of ways it's going to be better because it's not going

16:19

to have ums and ors. It's going to be very

16:21

crisp and concise, and most importantly,

16:24

it won't be some third party, right?

16:26

Because my digital assistant can also

16:28

render it using their face. But it'll

16:30

be really cool for the for the actual

16:32

creator to be still the one

16:34

that's delivering it. And what's

16:37

cool about that? So here's what's really cool

16:39

about that. It'll do multiple languages.

16:41

So now it's still Clint. It's

16:43

still John. It's still Jason. Jason

16:45

is still saying the thing to me.

16:47

Pedro diciendo

16:49

la content.

16:50

In.

16:51

Espanol. Entonces puedo escuchar.

16:53

En espanol and I won't know the difference.

16:55

It'll look exactly as if Jason

16:58

is speaking in Spanish instead of English.

17:00

And I think that is wonderful. Same with Chinese,

17:02

same with every language. Not any more difficult.

17:05

So now your deepfake content

17:07

is going out to every language

17:09

all at once, as soon as you drop a piece of

17:11

content. So watch this. You drop

17:14

a piece of content. It's one hour long.

17:16

Okay, perfect example. I just released a

17:18

video. It's one hour and ten minutes

17:20

long. I only did it in English because I'm only

17:22

capable of doing it in English. I could do it partially

17:25

in Spanish, but it would be kind of crappy.

17:27

So that one hour

17:29

and ten minute piece of content can now

17:32

be put in Hindi, Spanish,

17:34

Mandarin, Cantonese, Filipino,

17:37

like all these different languages, but not

17:39

just converted one for one

17:41

to the language. Also converted

17:43

to a ten second version, a 32nd

17:45

version, a one minute version. And

17:47

it's still me. It's still my face, it's still

17:49

my whatever gestures, all this,

17:52

it's still me delivering the content. That

17:54

is a game changer. An

17:57

absolute game changer because

17:59

it's scalable content delivery in

18:01

every language, at every bite sized

18:03

chunk. So now when I'm on a train or

18:05

I'm exercising, I could have my

18:07

AR interface. I see the person

18:09

is delivering the content and it's just like,

18:12

I'm watching that now. Maybe there will be some

18:14

sort of tag that says, there's this roar, or

18:16

is this an AI deepfake of it?

18:18

But it's not even quite a deepfake. It's

18:20

using deepfake technology. But

18:22

a deepfake is like almost unauthorized.

18:24

This will be completely authorized. Um, and

18:27

of course, there will be versions of this that are not authorized,

18:30

and that will be an actual deepfake. But anyway,

18:32

you get the idea. This is going to massively

18:34

change how we consume content,

18:36

because we want that content in different forms,

18:39

different languages, but we still want to see

18:41

the creator doing it. All right. AI and music.

18:43

AI is not going to ruin music. Have

18:46

we forgot about pop? Pop is,

18:48

you know, a few chords and a hook.

18:50

It's, you know, a lot of people would say it's

18:52

low quality music, like

18:54

low quality food. But it's

18:56

the same with doing customer service calls, sales

18:58

calls. We forget how low the

19:00

bar is for being better

19:03

than an average human, and that's why I

19:05

music is going to be pretty good. And actually

19:07

I think I have a link to

19:09

one here anyway. Discovery section

19:11

Luke Stefan's hack Luke put out an

19:13

amazing blog talking about his

19:15

evolution of bug bounty automation.

19:18

Talks about going from Bash to Python to Golang,

19:20

and how he eventually ended up at Cloud

19:23

Native. Really great piece, Thomas

19:25

wrote. He's super awesome and

19:27

he wrote a piece about applying LMS to

19:29

Threat Intelligence. Really cool. It's got a

19:31

Jupyter notebook here for the code as well.

19:34

SWE agent autonomously fixes

19:36

bugs in GitHub repos BR

19:38

is a Python framework. Simplifies building

19:40

an AI apps using building

19:43

blocks. Open source textbook

19:45

makes the art of mathematics accessible.

19:48

Jim Graham turns threat modeling

19:50

into a self-hosted web app. This

19:52

one is super, super cool. Chelsea

19:54

now lets you tweak images so you

19:56

can basically have an image that was created

19:59

with Dall-E and you could just like rub a like

20:01

the face or whatever and say, redo that part

20:03

and it will redo it, but integrate it with

20:05

everything around it. So that is something

20:07

that Midjourney had that that Dall-E didn't,

20:10

and now Dall-E has it as well. Claude's

20:12

API now has a new

20:14

tools feature that allows you to, like,

20:16

browse the web and do all kinds of stuff. I

20:18

kind of feel like agent functionality is going

20:21

to blend right into

20:23

the models, so I'm not quite sure

20:25

how long we're going to have, like these

20:28

elaborate agent frameworks,

20:30

because that might just be part

20:33

of using AI. You

20:35

might just say exactly what you want

20:37

to do in the prompt, and that will actually

20:39

be the agent framework. It'll actually spin

20:41

up how many agents are needed to do that.

20:43

And maybe you have some parameters right there

20:46

in the prompt that does it. But I kind of feel

20:48

like that's going to just blend right into

20:50

the language of the of the models

20:52

themselves. And kids are learning math

20:54

from deep fakes. Okay. This is another

20:56

example of this learning math from deep fakes

20:59

of Taylor Swift and Drake on TikTok. And

21:01

it's going well. I'm excited for this.

21:03

I am super excited for this look.

21:05

There are negatives that are going

21:08

to come from defects. Everyone knows that. Let's

21:10

find the positives. The positives are

21:12

if people love Taylor Swift, let's learn

21:14

math. Let's learn calculus from Taylor

21:16

Swift. I would do that. All right. Recommendation

21:18

of the week. Check out Mozart

21:21

on the bass. This is an eye track.

21:23

Yeah. Go listen this tell me that this won't

21:25

be popular. It's a little bit EDM ish.

21:28

So if you don't like that, just compare it to other

21:30

EDM that you don't like, and you'll see that

21:32

I is actually quite good at making

21:34

stuff you don't like. All right, aphorism of the

21:36

week don't explain your philosophy. Embody

21:39

it. Don't explain your

21:41

philosophy, embody it. Epictetus.

21:44

Unsupervised learning is produced and edited by

21:46

Daniel Missler on a Neumann 87

21:48

AI microphone using Hindenburg.

21:51

Intro and outro. Music is by zombie with

21:53

the Y, and to get the

21:55

text and links from this episode, sign up for the

21:57

newsletter version of the show at Daniel missler.com/newsletter.

22:03

We'll see you next time.