WEBVTT

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Welcome to the podcast. We have a stacked lineup

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today. Apple's lawsuit with OpenAI over their

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trade secrets is heating up, especially as there's

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an IPO coming this year. So we're going to talk

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about what some of the negative repercussions

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on OpenAI are. And all of this is happening as

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Apple has just passed NVIDIA as the most valuable

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company in the world, unseating them. Moonshot's

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Kimi K3 is looking to match OpenAI's Opus 4 .8.

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Their valuation has hit $31 .5 billion. cities,

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Hochul, their governor, used AI to review every

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single rule in state law, but still decided to

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ban data centers. Google has renamed Notebook

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LM to Gemini Notebook and is adding code execution.

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And at the same time, an ex -DeepMind researcher

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has just raised $55 million at a $300 million

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valuation for a visual AI startup called Exlorian.

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Databricks also landed funding at a $188 billion

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valuation. We're getting into all of that on

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the podcast today. First, I wanted to tell you

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about the most exciting feature I have added

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to AI Box, which is an MCP, basically a connection.

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that allows Claude or any other AI tool to get

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all the other AI tools inside of it. Particularly

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exciting for me is that I've added image generation

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inside of Claude. You can also do audio and video,

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but image is what I'm really excited about. I've

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spent the entire day making a Facebook ad campaign,

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and every single ad I created with this tool

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was using the AI Box MCP. Essentially, what you

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do is when you're using Claude, all you have

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to do is say, generate an image of XYZ. You can

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put the regular prompt you'd put into ChatGPT

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or something else and just say, use AI Box, or

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it really just understands that that's a tool

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that can generate images. So you could just say,

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generate an image of XYZ. Claude will go. Use

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your AI box account, generate the image, pull

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it in and open it right there in your cloud desktop.

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So you can see the image inside of cloud. It

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feels magical. I'm not going to lie. And the

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thing that I love about it is that it can do

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multiple images simultaneously. So I'm like,

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I work with cloud to come up with like a template

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of an image that I like for the ad, but it needs,

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you know, images and little graphics inside of

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the ad. So I work on that and then I'm like,

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perfect. This looks great. Now make 20 different

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variations of this, you know, change the title

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and headline and change these graphics, go use

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AI box for all of that. So. It uses AI box to

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generate all the little images and graphics and

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pulls them into its template it made and it spits

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out 20 of them. And it does it in like a few

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seconds because it can do simultaneous image

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generation on AI box. That is what I'm super

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excited about. If you want to try it out, it

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is AI box dot AI slash MCP. Okay, let's talk

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about the lawsuit between Apple and OpenAI. I

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think a lot of people are talking about this

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right now, particularly because the story broke

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that Apple has passed Nvidia to claim the world's

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most valuable company title. So now we have the

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biggest company in the world coming against opening

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eye, which is looking to IPO soon. Apple hit

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a $4 .88 trillion market value on Friday. And

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the reason for this isn't just Apple growing,

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but also Nvidia falling. Nvidia went down 3%,

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which basically ended their run. the top in the

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entire market which they've been sitting there

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for quite some time apple's valuation while it

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hit that um it surpassed nvidia's valuation of

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4 .8 trillion Nvidia shares fell, like I said,

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Apple's up 22 % this year, and Nvidia has gained

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about 7%. It's interesting because we're seeing,

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you know, Nvidia that had such a good run for

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so long, and we're shifting out of that being

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the hottest segment. And a lot of Wall Street

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has rotated towards memory and infrastructure.

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Companies like Micron Technologies and SanDisk

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are becoming really popular. And so it feels

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like, you know, maybe Nvidia isn't just the hottest,

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sexiest company. Now, while this is happening,

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Apple is doing incredibly well in the stock market

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and their lawsuit of OpenAI is pushing forward.

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They are alleging that OpenAI hired over 400

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former Apple employees and they misused trade

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secrets through their chief hardware officer.

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And of course, with the IPO that's coming up,

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this is something that... OpenAI obviously doesn't

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want to have, you know, tarnishing their name.

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Apple named OpenAI's chief hardware officer in

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this whole complaint. And this is all happening

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at the same time that OpenAI has released their

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first piece of hardware. It is a $230 keyboard

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for Codex, their coding tool, which I have purchased,

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by the way. So I'll give you guys a review when

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that comes in the mail. I'm actually really excited

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about that. Was it a spur of the moment purchase?

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Yeah, I actually saw the news drop that this

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thing was available and I was covering it on

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the AI Hustle podcast. And like mid -podcast,

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Jamie starts talking and I'm like, okay, I gotta

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buy this keyboard because it said while supplies

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lasted. I knew the supplies were not gonna last.

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So I went and purchased it. Side note, OpenAI

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also released a basketball that they're selling

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and it just looks like a weird gradient color

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basketball with the OpenAI logo on it. That also

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said supplies last. I just, I saw this and that

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came out, I guess, a few hours ago. I went and

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looked and that was already sold out. So the

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basketball and the keyboard are sold out, but

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it looks like OpenAI is making these physical

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products, which is kind of funny. Will this save

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them from... their IPO woes? I don't think so.

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But it's going to be interesting because that

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was their first piece of hardware that they're

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releasing and they're working with the former

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Apple iPhone designer, Johnny Ive, to come up

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with a new undisclosed piece of hardware. Some

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people say it's basically like a smart speaker

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on your computer. In any case, I've looked over

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a lot of the accusations Apple's made. It looks

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pretty bad. Basically, they brought over a new

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chief of hardware and he came from Apple and

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they gutted the entire... design team of Apple.

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They hired like 400 people from the design team

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of Apple. You know, he used to be over there

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at Apple. So he knew everyone. He pulled them

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in. And when he pulled them in, Apple's allegation

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is that he told all of them as they were coming

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to OpenAI, this is how you get around all of

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the, basically when you quit Apple, how you get

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around all of the, you know, retaining all the

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information. So bring little components, give

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us the secret words, tell us what's going on

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at Apple. And in some case, they said that one

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of the employees kept like a laptop and used

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some like VPN. end loophole to keep access to

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some data at Apple. That's kind of Apple's lawsuit

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in any case. I mean, it's an important lesson

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though, when your employees leave, everything

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in their head also leaves with them. So what

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type of confidential information do they move

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over? That's what the lawsuit is going to be

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covering. Moonshot's Kimmy3 is looking to beat

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Anthropic right now. And on one important benchmark,

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which is a front end developer benchmark, it

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is... ahead of Fable 5 even. So it's really doing

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well. It's a two to three trillion parameter

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open weight model. And with all of this, it's

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coming from a Chinese lab. And the Chinese lab's

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valuation, Moonshot, jumped to $31 .5 billion

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in two months as they're coming out with this

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model. And it's beating even Anthropocon, a bunch

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of different... benchmarks. This is the largest

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open weight model that has ever been released

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from China. They raised $2 billion at a $20 billion

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valuation back in May, and now they're valued

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at 31 billion. So their valuation's increasing,

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their model's getting really good. This is all

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coming to a time with Anthropic, they're getting

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kind of held back by the government. It feels

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like we're getting a lot of regulation, these

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30 day kind of hold back periods where the government

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can go and review the models before they release

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them to the public. None of that is happening

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in China and they're releasing all of these models.

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open weight so people can actually get them and

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fine tune their own models on them. A lot of

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enterprise buyers prefer this because if you

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can grab something like Kimi K3, put it on your

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own hardware, it's not tied to China, it's not

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tied to Moonshot. They don't see into anything

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that you're doing. You fine tune your own stuff

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on this system. And then you can basically access

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it for quote unquote free, but you're using it

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with... all on your own hardware. Now, some people

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are like, hey, don't use the Chinese models.

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I think maybe the play for the Chinese models

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are open, basically release a bunch of these

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open weight models, get people fine tuning on

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top of them. So they're really, they're kind

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of embedded in your ecosystem basically. And

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then you could probably release better models

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that maybe are paid, or you could just say, hey,

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look, if you don't want to run it on your own

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hardware, you can also run it on our, on our

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data, on our like servers and stuff, which is,

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which is a pocket. strategy. Right now we have

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New York's governor, Governor Kathy Hochul. She

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said that she used AI to review every state rule,

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regulation, and policy in the last couple months.

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And she said that the work they were able to

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do in reviewing all of this in the last couple

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months, she said it would have taken the staff

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five years if they didn't have AI. This, in my

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opinion, is showing a massive gap right now.

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New York is using AI to streamline, and particularly

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Kathy is using AI to streamline the government.

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she's doing all of this while at the exact same

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time she put a one year ban on new data center

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build -outs inside of their state. So she's using

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the AI, but she's banning it. It feels like all

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of the people that fly on private jets to environmental

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conferences and burn a billion pounds of fuel

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and then tell everyone not to drive their car

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because it uses too much fuel. So that's kind

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of what it feels like to me. She said with what

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she was able to do with the AI though in reviewing

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all the laws, which by the way, phenomenal. So

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I'm not like... not begging on everything. I

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think that's amazing if she can use AI to streamline

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all of the laws. She said she found a bunch of

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outdated laws. One of them was a $25 dog hunting

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fee. If you wanted to go hunting with your dog,

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you had to pay a $25 fee. Apparently there was

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a fee for pregnant workers. They had to go get

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a permit if they wanted to work after midnight.

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There's just like all these random laws and regulations.

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And you know, this just kind of happens when

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a a state has been around for so long and all

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these regulations get added no one ever goes

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and takes the regulations away so i'm all for

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deregulating and i think they did you know a

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great job they found a bunch of things hoshel

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didn't say what ai model they used for all of

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the reviews and they didn't say what their methodology

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was for for doing all this but Overall, she said

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that this was a huge productivity jump. She said

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it's 30x productivity jump on what she was able

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to do. So she gets some points for looking like

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the cool governor for using AI to streamline.

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And honestly, I hope every state does that. So

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good on her for that. Bad on her for banning

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data centers for a year. Although it doesn't

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really matter because every other state will

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get them instead, I guess. Okay. Google has renamed

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Notebook LM to Gemini Notebook. I mean, it makes

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sense. They're trying to keep with the branding.

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Google loves changing the name and changing the

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products and killing the products of everything.

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I'm just happy that Notebook LM is still alive.

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They've added code execution to it. It's funny

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because they just basically had a runaway product

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that was random. They released tons of products.

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Notebook LM just caught fire for some reason.

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I think a lot of students just would throw their

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textbooks into it and have it. do a podcast talking

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back to them. They liked that. But in any case,

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it can now do code execution. It has a secured

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cloud computer that can write code against your

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own documents for data analysis. The app has

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30 million users. 600 ,000 organizations are

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using Notebook LM. Honestly, it blows my mind.

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I mean, I've played with it. I've used it. I

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know people that religiously use it. It's not

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part of my go -to, but it blows my mind that

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they have 30 million users and now it's called

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Gemini Notebook. So they're just giving Gemini.

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a better name, and a little bit of a good PR

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boost with this popular tool. The code execution

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is live today, so you can go use that for Google

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AI Ultra subscribers and for Workspace customers.

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It's rolling out to all pro users over the coming

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weeks. Notebooks will now sync with the main

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Gemini app, which honestly, I'm all for that.

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I hate it when there's all of these different

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tools and they're not connected, especially when

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it's from the same company. Google really should

00:11:39.970 --> 00:11:41.889
have everything connected, so I think that that's

00:11:41.889 --> 00:11:43.870
great. It's going to appear inside of Google's

00:11:43.870 --> 00:11:46.059
search AI mode. basically let you pull answers

00:11:46.059 --> 00:11:48.179
from your own documents instead of just the web,

00:11:48.320 --> 00:11:50.720
which is really cool, right? If you have a whole

00:11:50.720 --> 00:11:53.179
bunch of documents on your Google Drive and you

00:11:53.179 --> 00:11:55.000
want to, you know, and you go in and search in

00:11:55.000 --> 00:11:56.580
the search bar on Google and all of a sudden

00:11:56.580 --> 00:11:58.340
it gives you answers from that, that could be

00:11:58.340 --> 00:12:01.039
a really useful bit of context. The app started

00:12:01.039 --> 00:12:04.539
as a project at Google I .O. back in 2023 and

00:12:04.539 --> 00:12:06.899
now it has grown. It got really famous and viral

00:12:06.899 --> 00:12:09.830
from TikTok. Okay, all of this is at the same

00:12:09.830 --> 00:12:12.950
time that Andrew Day, a former Google DeepMind

00:12:12.950 --> 00:12:17.669
researcher, raised $55 million for Alorean at

00:12:17.669 --> 00:12:21.230
a $30 million valuation. He did all of this before

00:12:21.230 --> 00:12:23.730
the startup shipped anything. Dai is basically

00:12:23.730 --> 00:12:26.610
betting that visual reasoning teaching AI to

00:12:26.610 --> 00:12:28.970
understand images and video the way the current

00:12:28.970 --> 00:12:31.610
systematic text handles is the next frontier.

00:12:31.830 --> 00:12:33.610
And he basically turned down a whole bunch of

00:12:33.610 --> 00:12:35.450
really high offers to take strategic investors

00:12:35.450 --> 00:12:39.769
like NVIDIA who understand how expensive AI research

00:12:39.769 --> 00:12:42.730
actually is. So NVIDIA is one of his investors.

00:12:42.889 --> 00:12:44.529
A bunch of other people who got turned down.

00:12:44.629 --> 00:12:47.309
Dai spent over a decade at DeepMind on foundational

00:12:47.309 --> 00:12:50.909
work that all later influenced ChatGPT. Lorian's

00:12:50.909 --> 00:12:53.590
valuation to capital ratio is way more aggressive

00:12:53.590 --> 00:12:56.789
than even thinking machines from... a former

00:12:56.789 --> 00:12:59.429
co -founder of OpenAI, which was one of the largest

00:12:59.429 --> 00:13:02.049
seed rounds in US history. Google, OpenAI, and

00:13:02.049 --> 00:13:04.259
Anthropo are all working on multimodal. Understanding,

00:13:04.379 --> 00:13:08.019
which is a recent Stanford benchmark. And that

00:13:08.019 --> 00:13:09.539
benchmark in particular showed that frontier

00:13:09.539 --> 00:13:13.299
vision models are still lagging and they're worse

00:13:13.299 --> 00:13:15.820
than a toddler on basic visual reasoning tasks.

00:13:16.019 --> 00:13:18.820
So he's trying to crack the code and we'll see

00:13:18.820 --> 00:13:22.799
if that is possible. Databricks has landed funding

00:13:22.799 --> 00:13:27.360
at a $188 billion valuation. They just closed

00:13:27.360 --> 00:13:30.080
this funding round. They made it basically in

00:13:30.080 --> 00:13:32.259
the same league as OpenAI and Anthropic on paper

00:13:32.259 --> 00:13:35.600
anyways. The data and AI platform company, they're

00:13:35.600 --> 00:13:37.919
not just building AI models. They're also selling

00:13:37.919 --> 00:13:40.220
a lot of the infrastructure that companies use

00:13:40.220 --> 00:13:42.220
to train, deploy, and run models in production.

00:13:42.779 --> 00:13:45.059
Databricks right now is competing with Snowflake,

00:13:45.059 --> 00:13:48.179
if you've heard of the company, on data warehousing.

00:13:48.669 --> 00:13:51.690
And they're also competing a bunch of other big

00:13:51.690 --> 00:13:55.990
players on modeling serving. They're also strengthening

00:13:55.990 --> 00:13:58.570
their acquisition. They acquired Mosaic ML, which

00:13:58.570 --> 00:14:01.710
I covered on the podcast back in 2023. I don't

00:14:01.710 --> 00:14:02.990
know why, it's kind of funny. That particular

00:14:02.990 --> 00:14:06.850
episode I covered from the San Francisco airport,

00:14:07.210 --> 00:14:10.570
which is funny to me. But anyways, the company

00:14:10.570 --> 00:14:13.690
has basically not done an IPO. So they're not

00:14:13.690 --> 00:14:15.809
publicly listed. They've just done these private

00:14:15.809 --> 00:14:19.500
funding rounds. kind of wild that we have these

00:14:19.500 --> 00:14:21.580
massive ai companies that are doing that right

00:14:21.580 --> 00:14:24.200
now at this new valuation they're now valued

00:14:24.200 --> 00:14:26.580
higher than most established enterprise software

00:14:26.580 --> 00:14:29.059
companies and i I think basically they pushed

00:14:29.059 --> 00:14:30.980
the bar for what it takes to go public because

00:14:30.980 --> 00:14:34.740
at $188 billion, you would have expected this

00:14:34.740 --> 00:14:37.360
type of company to go public in the past. Guys,

00:14:37.419 --> 00:14:38.919
thank you so much for tuning into the podcast.

00:14:39.000 --> 00:14:40.820
If you enjoyed this episode, make sure to leave

00:14:40.820 --> 00:14:42.460
a rating and review wherever you get your podcasts.

00:14:42.700 --> 00:14:45.179
And as always, make sure to go check out AIbox

00:14:45.179 --> 00:14:48.600
.ai if you want to get access to over 80 different

00:14:48.600 --> 00:14:50.740
AI models and the MCP so you can pull all those

00:14:50.740 --> 00:14:53.159
AI models into Cloud. You can get Cloud to generate

00:14:53.159 --> 00:14:56.629
images, audio, video. It will save you so much

00:14:56.629 --> 00:14:59.190
time. It's amazing. It's a buttery smooth experience

00:14:59.190 --> 00:15:01.669
that I've been doing all week long and I love

00:15:01.669 --> 00:15:04.149
it. So if you wanna check it out, AIbox .ai slash

00:15:04.149 --> 00:15:06.389
MCP. All right, I'll catch you guys all in the

00:15:06.389 --> 00:15:06.950
next episode.
