Anthropic CEO's AI Predictions for 5-10 Years
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Investments into generative AI startups have passed $3.9 billion in the third quarter of this year. Today on the podcast, I'm going to be breaking down everything happening in the industry, the state of AI, what is getting money, what investments are getting money, the analytics and data coming out of the industry, and a lot of our polling platforms showing where this money is going and the state of essentially what's going to happen to a lot of these companies.

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So what I want to talk about is the fact that VCs have invested $3.9 billion into generative AI. This is absolutely colossal for this quarter. This is really impressive. There's about 206 different deals that had this $3.9 billion spread across them. That's according to PitchBook. And of course, that's pulling out OpenAI's $6.6 billion round. If that was included, we'd be over...

over $10 billion. But we're pulling that out because obviously that's bigger than everything else combined. And we're going to just talk about some of the biggest. That's also $2.9 billion that went to US-based companies in about 127 deals. And everything else, the other billion was everything not in the US, which is honestly kind of impressive, right? If we're looking at like $4 billion and about 75% is USA-based companies. Pretty impressive of a

for the industry here. So the biggest winners this quarter was Magic at $320 million. They raised in August. We'll talk about them. There was also Glean that raised $260 million in September. Hebia raised $130 million in July. And China's Moonshot AI raised $300 million in August. Sakania AI, which is a Japanese startup focused on scientific discovery, closed $204 million.

all around last month. So I want to talk a little bit about these and then why I think these are kind of indicative of some things that will happen broadly in the industry moving forward. So Magic is a generative AI coding startup.

They raised money from some serious players, Eric Schmidt, right? Former CEO of Google. And then Atlassian, a massive software startup. I would not be surprised if we see like a company like Atlassian investing in this, trying to make a play to acquire them later on or bring them on board at the company. A really impressive company. They have a lot of,

competition though. So it's nothing new. There's Codium, Cognition, Poolside, AnySphere, and Augment, which are all really well-funded companies in the AI space. So they have

raised this $200 million at a $1.5 billion valuation back in July, and now they've just done their next funding round. So really impressive company, and it's going to be one to follow closely. It doesn't have the mass adoption of a lot of other companies. It's, I mean, fairly well used, but there's others that are bigger, GitHub Copilot and others, for example. Next is Glean that is essentially trying to be...

an enterprise version of ChatGPT. It's essentially, you know, software connected to enterprise and third party databases. You can ask plain English requests about your company's databases, data sets.

and enterprise data, and it's going to give you information. You could ask something like, how do I invest in our companies 401k? And it's going to give you info about that. So it's kind of like a corporate chat GPT, which I think is less useful. Like there's only so many questions you're going to ask about your internal company, but maybe that's just me. Maybe there's a lot of questions you need to ask about bigger companies. So anyways, that's an interesting one.

The next one I want to talk about is Hebbia. So Hebbia, they raised $106 million back in July. They have a $700 million valuation. And what's interesting is based off of the $700 million valuation, that's coming off of $13 million of profitable revenue. So $13 million giving them $700 million valuation. These are really, really juicy valuations to say the least.

And A16Z joined in this. There was Index Ventures, Google Ventures, and Peter Thiel. So really interesting company right here. Essentially what they're going to be working on, it was founded by George Suvika while he was working as a PhD in electrical engineering at Stanford. And the company...

is profitable, which is fantastic. They're going to be working on a bunch of really interesting projects in AI. This is an incredibly high valuation, in my opinion, for a company that's essentially

quite new, right? This is a Series B, so they're a little ways into their company, but it's not, you know, it's not one of these older companies. So anyways, Hebia AI is very, very fascinating. They currently sell their software primarily to asset managers, investment banks, and financial institutions. So they're helping people make

I believe that they're a data company that's helping you use AI to sift through your filings and other documents to organize your information about specific companies and their competitors. So it's really for the financial industry, helping them do research. So Hebbia, very interesting company. Last one I want to talk about is China's Moonshot AI that just raised $300 million. And they raised this back in August. So

Essentially, they're at a $2.5 billion valuation. They've raised a billion dollars total. And essentially, they have an LLM that's focused on long context. So it's kind of like everyone's talking about Google Gemini and how they have a 1 million token context limit, which is about 750,000 words. Well, they're looking at even...

I mean, essentially the goal here is for even longer context windows, which you can see the value, right? Maybe you want to give this thing 10 books and help you do, you know, get a bunch of insights out of that. Allegedly it can do eight times the length of what OpenAI's GPT-4 32K can do. And it supports the processing of about 200,000 Chinese characters in a single conversation, which is,

Chinese characters could be like determined as you know words essentially so Anyways, I mean, I think this is impressive. But at the same time you still have Google Gemini that's doing 750,000 so while that's impressive it seems like Google's kind of beating them already So, I mean, I'm curious to see where this goes. I

They've definitely been in this space, but in my opinion, they're going to have to increase that to be a viable company if that's what they're doing. Okay. Last one I want to mention is Sakana AI. This is a Japanese startup that's focused on "scientific discovery." I've researched this company a bit in the past and it's really tricky to figure out exactly what they do because

It's just like, we're like focused on scientific discovery and it's like really not super clear because they're, they're kind of like one of these AI research labs. So they're interested that, you know, they're, they're working on a lot of stuff, but they don't really have a specific product that's crushing it.

There's a bunch of young graduates that are trying to get that are essentially running this and the Japanese government is trying to essentially help attract talent. So they're funding some companies including this one. So anyways, very interesting. They did have Bestmere Venture Partners.

that invested in this, which is a major player. They said, quote, having been fortunate to be a key investor in Toast in the US, supporting it to become a $13 billion company, we see a similar element of success in Dini. So anyways, apparently they think this is going to be big, but it's really kind of the focus on invest in good founders with that one, in my opinion. So

What is going on in the state of the industry? Forrester report predicts that 60% of generative AI skeptics will embrace the technology. This, I think, is pretty obvious. We've seen a lot of people that are quite skeptical at the beginning of after ChaiGPT was launched that are now getting all in on it.

Gartner had a prediction earlier this year that 30% of gendered AI by AI products are going to be abandoned after proof of concept by 2026. Again, I don't actually think that this is too crazy either. A lot of AI companies have made big promises and then essentially have not delivered on these promises. It's true.

harder. We see this literally from companies like Apple who promised us Apple intelligence, really struggled to bring it to us, came out with their new iPhone that didn't have it and said, you know, coming later in this year and early next year for a bunch of features. So if Apple's struggling that bad, you can imagine a lot of startups are too. There was a quote from, I believe, Brendan Burke, who's a senior analyst of emerging tech at PitchBook. And he said,

quote, large customers are rolling out production systems that take advantage of startup tooling and open source models. The latest wave of models show that new generations of models are possible and may excel in scientific fields, data retrieval and code execution. There's a lot of exciting new areas that are being driven. And when I covered all of the companies at the beginning that are raising funds, um,

This kind of was a trend that I was seeing a lot of them follow. So one of the biggest hurdles that they're currently trying to overcome is just the computational requirements, right? All of these companies are struggling to get the H1 and the H200 chips from NVIDIA, the GPUs. And this is, I think, going to continue to be a struggle. Everyone's going to be trying to fight for more compute. Sam Altman himself said he was worried that Elon Musk's XAI was going to get more access to more compute than OpenAI had by next year. So

This is going to be interesting. Bain analysts had a recent study where they were essentially predicting that generative AI is going to push companies to build gigawatt scale data centers that consume five to 20 times the amount of power the average data center consumes today. Right. And at this point, like we're seeing a very similar trend, which is like the more power, the more energy, the more compute we give to these AI models,

the better they're getting to some degree. Now, I think there's a ton of work. And in fact, when I say a ton, I mean an insane amount of work that needs to go towards making these models more efficient, open as working on some projects there. But I do think that this is going to be something that people focus on. Morgan Stanley is estimating that at the rate of the current trends, greenhouse emissions will go up.

I have a counter argument to this, which I mean, you know, take it with a grain of salt 100%. But imagine AI is definitely using more energy. But imagine if theoretically, less people had to go into work or into their offices, because AI was essentially replacing a lot of people at jobs.

You could imagine that that could also cut down on energy consumption of all the energy used in commuting. Now, I don't actually, perhaps I'll steal my own argument and say why I don't think that's probably super accurate. And that is because I don't believe when AI replaces someone or takes a job or does something that that person's just out of the labor force forever. I think they'll find a new job more likely

more startups will be hiring. And so people move from like bigger organizations where lots getting automated to smaller startups. So there's a lot of problems to solve. Problem solving and finding new processes is something that AI is not always good at, especially when there's new tools. Like you really need people for that, in my opinion. So anyways, I don't think that people are going to get replaced. I think it's just going to

um, mix up a little bit and bigger companies will require less people. That's going to actually, I think, be healthy for a startup ecosystem where there's a lot more startups launching and people will be working at smaller companies. So anyways, there's, there's also that, but I just think it's hard to say that one thing is definitively going to make, you know, a massive impact, especially when, um, due to all of this, we have Microsoft and Google that are all announcing investments in nuclear and

I believe Microsoft said they're going to buy all of the electricity coming off of one of the nuclear reactors on Three Mile Island that they're going to use to power all of their AI. And a lot of people are making similar plays essentially going into nuclear, which is an amazing green source of energy, you know, great eco-friendly energy.

energy super clean. So I'm excited about the potential of nuclear and will we be using more energy as we kind of transition that way, right? Because they're saying like, this is prolonging the life of coal fired plants. Yes, probably.

But I think people are pushing making a really big push for nuclear and I'm excited for that I think this is a really good direction the world needed to go this way people were really concerned about it. I will argue that the insane amount of energy that we are required to use now with AI and the demand that people can see today and the forecasts that they can see for in the future is pushing everyone to go to go towards nuclear that was critical skeptical

of it in the past or, you know, fearful of bad PR or something like that. And so I think because of that, you could also make the argument that, yes, we might be like using coal or like other things for longer or more, but really it's what's pushing us towards going towards nuclear, which is going to essentially eliminate the need for that altogether. So if AI didn't exist,

Maybe we would have just stuck on some of these older technologies like coal for much longer and actually used more. I don't know. That's my other argument. In any case, very, you know, lots of arguments going on with energy and AI. And I'm excited to see how a lot of this stuff scales. In any case, investments in generative AI I don't think are showing any signs of, you know, slowing down.

11 Labs is looking to raise funds at a $3 billion valuation, a fan favorite on the podcast. Black Forest Labs, a really interesting company that's created an open source AI image generator, which I think is the best, the number one competitor to Midjourney. It's essentially an open source Midjourney. In my opinion, it's really good. They're in talks to raise funds

a hundred million dollars in funding. So a lot is going on. This is an absolutely fascinating time to be an AI. Tons of money is being raised and I will keep you up to date on who's getting money, how much they're getting and what they are spending in it, spending it all on. If you enjoyed the podcast today, make sure to leave a review, drop a comment if you're watching this on YouTube. And if you're interested in joining the AI Hustle School community, the link's in the description. I will catch you all next time.