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the way that it could become a trillion dollar company is actually by cutting the cost to such a low degree that nobody else can effectively compete with it and then at that point they can become a small small tax you'd rather just pay it than try to compete with it and I think for openai that's actually a very brilliant strategy so that's how they they could get to become very very large in valuation would be to become so pervasively relied upon and where they take such a minuscule take rate of their participation in you building a company that could be really effective for them lesser picks and shovels play in a way to create the developer ecosystem for AI and it's about to your point I mean I think you raise a good point that you know what was their motivation to take such a dilutive round you know the 10 billion that was evaluation at 30 30.
yeah and does that imply that they're not confident I mean the flip side of it could be maybe they know they want to compete on the basis of rapidly you know becoming the developer platform and so they're going to subsidize that developer platform you know with negative gross margins for some period of time and maybe that's why they need a lot of capital and they were in kind of a reflexive Loop of just cost of getting better versus the amount of money they had to get better and so maybe they were forced to do it and then in that point how would you justify you would say well the other 50 is still hugely valuable so that's enough for us and I think that that's that's very logical as well we haven't given enough time for a logical framework of investing to develop which also is tied to a logical framework for entrepreneurship to emerge we're just way way way too early so the thing with all of these language models is that they are Grist for the mill and we talked about this before if it was a highly proprietary asset you would have never sold 49 of it to Microsoft for 10 billion dollars because you would assume that it was worth a trillion dollars so it's a huge tell on the part of open AI their deep understanding and they understand it better than anybody else that it's a bit of a capped upside so what is uncapped I guess is maybe the better question well if you look at the 1849 Gold Rush as an example the people panning for gold in my opinion are the people building language models today they're going to come and they're going to go but who's gonna win well the pick and shovel providers won Levi Strauss one so what is the equivalent of that today I think it's at the Silicon layer because you need to really re-architect how compute will actually work in a world of all of these models those folks will get paid if you look at AMD and Nvidia they've been getting paid for years they continue to get paid they probably will continue to get paid even more and so folks that actually take a step into doing something hard and difficult in AI like custom silicon could get rewarded and then there's what I call the white truffles what are these unique Alba white truffles these singular sources of data that when used in reinforcement learning make your output just zinc item one on the docket today there is just a massive AI fomo frenzy going on economists published a piece this week about the insane fundraising in the generative AI space this is stuff like Chachi PT stable diffusion you've heard these names and there are now 500 generative AI startups according to this report that tracks with what I'm seeing in the early stage and not counting the open AI 10 Billy from Microsoft investment donation rev share round trip whatever that is they have so far collectively raised more than 11 billion dollars the article included this chart which you can see if you're on our YouTube channel and just tons of folks working in audio image and text so we're basically looking at the multimedia basically revolution of PCS in the 90s occurring again and a complete platform platform shift douglioni from Sequoia one of the greatest investors in history of Silicon Valley had this to say and we will comment on the other side of this 50 second clip from Doug the AI is the next platform shift in the same way that mobile was the one before internet was the one before so I think AI is real but I said earlier we are going to overestimate it in a short term we're going to invest in everything in the same way that in 1999 we invested in everything but then Google came out of that or Facebook came out of that so I think you have to have a good head on your shoulder where you don't practice fomo where you don't chase every company AI is real AI is the next platform but how do we not invest in everything that walks how do we make certain Investments based on Market Maps based on thought processes that are more rational and not do every investment just because every other Venture firm is doing everything best okay I want to add one other piece of news that we saw this week which is open AI announced that it's developer AI they were cutting the tax on that or basically the metered rate they charge to use it by 90 percent so I think this is going to be a game changer I think this is based on the chat GPT 3.5 API and of course they're coming out with 4.0 later this year I've already had explained to the audience what an API is and why this is important for those people who don't know just application programming interface it allows a developer of some other application to build on top of you so in other words like a developer wouldn't have to use this chat interface to get access to the large language model you could just submit your request through the API and so give an example of what of like a popular app and how they might use it yeah so API so I think like notion actually had a demo that they published where incredible it was a pretty incredible demo maybe we can find it and it would do things they added actions in the demo like generate a task list so you could take like a document or a meeting summary and would spit out recommendations for next steps or tasks it could you know spit out a table basically it's the autocomplete for everything that we talked about right so now notion doesn't need to build their own llm expertise they just use the API and then the notion app you say hey I'm building a marketing plan and you say well okay give me a list of things that should be on my marketing plan for my new app it sends a signal to the chat GPT API which will be on Azure Microsoft's platform and then it gives you the data back you don't have to build the language model
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