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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. So let's get into all of this before I do. If you're interested in creating your own startup, if you're interested in making money online with AI tools or creating an AI side hustle, I would love for you to join my AI Hustle school community. Every single week I create exclusive content I don't post anywhere else showing the tools that I'm using to grow my personal businesses with AI. And in addition to that, I also break down all of the side hustles I'm doing, all the ways I'm making money, how much money I'm making. For a limited time it's $19 a month. But in the future I'm going to raise the price to around $100 a month. So if you get it now, you get a locked in price and I'll never raise the price on you. Let's get into the episode today. The link is in the description for the AI Hustle school community. 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, you know, 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, pretty impressive 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. Second. AI, which is a Japanese startup focused on scientific discovery, closed $204 million round last month. So I want to talk a little bit about these and then what I. 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, Any Sphere 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 chat. 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, you know, something like, how do I invest in our company's 401k? And it's going to give you info about that. So it's kind of like a corporate chatgpt, 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 Hebia. So Hebia, 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 juicy valuations to say the least. And a 16Z 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 Suvica 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. I believe that they're like 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 to, helping them do research. So Hebia, 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 hit a 2.5 billion dollar valuation. They've raised a billion dollars total and essentially they have an LLM that's focused on long context. So it's, you know, 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 GPT432K can do. And it supports the processing of about 200,000 Chinese characters in a single conversation. Which Chinese characters could be determined as words essentially. Anyways, 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. 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 you know that's what they're doing. Okay, Last one I want to mention is Saana AI. This is a Japanese startup that's focused on quote unquote 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, you know, 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 finding some companies, including this one. So anyways, very interesting. They did have Bessemer Venture Partners that invested in this, which is a major player, they said having been fortunate to be a key investor in Toast in the US supporting it to become one, to become a $13 billion company. We see a similar element of success in Denny. So anyways, apparently the thing 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? Forrestore 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 ChatGPT was launched that are now getting all in on it. Gartner had a prediction earlier this year that 30% of gender 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 harder. We see this literally from companies like Apple who promised us Apple intelligence, really struggled to bring it to us, came out through 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, 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 be continued 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 XI 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 is 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 counterargument 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, you know, energy used in commuting. Now, I don't actually, perhaps I'll, I'll steal man my own argument and say why I don't think that's probably super accurate. And that is because I don't believe when I replaces someone or takes a job or does something that that person is just out of the labor force forever. I think they'll find a new job, 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 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 due to all of this we have Microsoft, Google that are all announcing investments in nuclear go. I believe Microsoft said they're going to buy all of the electricity coming off of the, 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, 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 are 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 I 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, 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. Eleven Labs is looking to raise funds at a $3 billion valuation you know, 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 Mid Journey. It's essentially an open source Mid Journey, in my opinion. It's really good. They're in talks to raise 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 is in the description. I will catch you all next time.