My work

How will OpenAI compete?

OpenAI has some big questions. It doesn’t have unique tech. It has a big user base, but with limited engagement and stickiness and no network effect. The incumbents have matched the tech and are leveraging their product and distribution. And a lot of the value and leverage will come from new experiences that haven’t been invented yet, and it can’t invent all of those itself. What’s the plan? LINK

AI eats the world

Twice a year, I produce a big presentation exploring macro and strategic trends in the tech industry. The latest edition: ‘AI eats the world’. LINK

News

TrillionAI

This really, really isn’t a venture newsletter or a capital markets newsletter, but sometimes that’s the macro story. This week OpenAI closed its latest funding round, raising $122bn at a $852bn valuation, and SpaceX filed for IPO, reportedly aiming at a valuation of $1.75tr (as I pointed out a few weeks ago, the largest ever IPO was Saudi Aramco in 2019, raising $29.4bn at a $1.7tr valuation). Both of these, of course, are bets on an essentially unknowable future. OPENAI, SPACEX

Meanwhile, the New York Times reports that Elon Musk is insisting that banks that want to be included in the IPO (given the size, they will need a lot of banks in the syndicate) need to buy subscriptions to the  ‘Grok’ also-ran LLM that he merged into SpaceX earlier this year. Pay to play. LINK

OpenAI buys a media company

OpenAI bought TBPN, a tech video talkshow that gets views of 75-100k, and apparently had ad revenue of $5m last year and aimed at $30m this year: the price was apparently ‘low hundreds of millions’. I guess the new focus on focus starts next week. 

Friendly, multi-hour video interview podcasts are a big thing in the valley, and when they work (and not all do) they can find a space for wide-ranging discussions between sycophancy on one side and performative attacks on the other. These are tech people talking to tech people for an audience of tech people, and bypassing news brands and news audiences. Interestingly, this one is small on YouTube and seems to be rather bigger on Twitter itself, which remains important for discussions of AI even as the steady stream of racist posts from the owner drove a large portion of the users away (including me). Last month one of the co-founders said they aim at a core of about 200k people in tech (this newsletter has about 170k subscribers, and my presentations get 3-400k downloads). 

That said, while OpenAI might well need a better comms strategy, I don’t know why owning this particular channel could help it affect the public narrative. This isn’t the Washington Post (which disappointed Bezos), nor Twitter (which gave Musk a lot of influence with Trump), and there are many other voices. That said, I’d be happy to give a16z a friends and family discount - if they want to buy me out for $100 million, they know where to find me. LINK, PRICE, BACKGROUND

This week in AI

Fidji Simo, OpenAI’s head of product (and arguably de facto CEO, wth Sam Altman handling funding and research), is taking a medical leave of absence to manage a chronic illness. LINK

A chunk of Anthropic’s source code (but not model weights) leaked, due to  human error in a software configuration. Mostly, this revealed a lot of inside info about product mechanics. LINK

A few weeks ago Ramp corporate spending data (which OpenAI dismissed) suggested that Anthropic is gaining enterprise share, and this week TechCrunch has credit card data which suggests the same for consumers. As I wrote a few weeks ago (see above), for most consumers, these models are commodities with very few switching costs. LINK

Remember Mistral, once the great French hope for AI (other than Yann, obviously)? It just raised $830m to build a data centre in Paris. LINK

Oracle layoffs

Oracle has a cash-generative legacy business that’s in long-term decline, and it’s borrowing heavily against those cashflows to buy its way into data centres instead. Now it’s doing layoffs in that legacy business as well to fund the DCs - certainly thousands, and possibly up to 30k (on a 160k base). LINK

Dating privacy

OKCupid settled with the FTC over a claim it gave personal data for 3m users to Clarifai, a facial recognition ID provider. Much as GDPR is a mess, this kind of thing is why it exists. LINK

Amazon satellites  

Amazon did a deal with Delta to deploy its satellite internet, starting in 2028 (Starlink is already deploying on a bunch of airlines - getting a real 150 meg connection on Qatar is very nice). Meanwhile, Amazon is apparently also looking at buying Globalstar (market cap ~$10bn) to bulk up its effort to compete with Starlink. (NB Globalstar powers Apple’s emergency satellite connection on recent iPhones, and Apple has a 20% stake.)  LINK

Remember Allbirds?

Allbirds was a flagship of the D2C boom a decade ago, and at one point it seemed like every Tesla Model S in Silicon Valley came with a pair. The valuation peaked at $4bn, but it was just bought for $39m, making it a symbol of the D2C bust as well. LINK

Robot IPOs

Unitree, maker of those viral humanoid robots, filed for IPO (PDF in Chinese). It’s profitable and it did about $170m of sales in the first 9m of last year. About half the revenue is from the humanoids, but most of the sales are ‘R&D’ (other researchers) and apparently most of the rest are for trade shows. Still very, very early, but it’s not very clear how far humanoid robots are useful without much more generalised AI than we have now. LINK

Ideas

Outside interests

Data

EU data on AI and productivity, suggesting early effects are mostly on labour productivity rather than employment. LINK

YouTube’s revenue passed Disney, making it the world’s largest media company. LINK

SimilarWeb says ChatGPT is running ads on 0.1% of prompts in the USA. Still purely experimental. LINK

A new version of the ‘humanity’s last exam’ AI eval was just released: humans get 100% and the latest frontier AI models get less than 1%. All of these things are wrestling with the fact that we have no good theory of intelligence and no good theory for why LLMs work so well: we can make empirical measurements, but don’t really know what we’re measuring (one theory, or perhaps definition, is that we will have ‘AGI’ when we can’t think of a new benchmark). LINK

Preview from the Premium edition

What is an AI job? 

As we all try to work out what AI will mean for industries, companies, and jobs, the obvious question is to ask which tasks can be automated and which jobs are made up of those tasks, and by how much. But it seems to me that a much more important question is how much those tasks are where the real value was, and how much they might be incidental to the real job to be done.

We had a very similar kind of question for the internet: the obvious question was how you still need physical distribution or a physical product anymore and how much that could be made digital, but again, the real question was whether that was where the value really was. 

There were some markets where physical was so much the nature of the product or the business, and the internet was such a direct substitute, that those businesses just disappeared. At the other extreme, there were markets where it was very difficult to substitute online, or where the switch from physical to online distribution was peripheral or irrelevant (luxury goods, say, or airlines). However, I think the important part to this about today was the middle case, where the value and the product wasn’t about physical at all, but physical was how the business worked - most obviously, newspapers selling lumps of paper and record labels selling small pieces of plastic. No-one got into the music business or journalism because they wanted to work in specialised light manufacturing, but that was the basis of a business model, and it was the moat, and once it was possible to break that apart both industries came close to collapse. 

Hence, for AI: there are some markets and some jobs that we will be able to automate very easily, and there will be some where AI is irrelevant or peripheral. Just as for the internet, sometimes this will be unexpected: it seemed obvious that airlines didn't face a competitive threat from the internet, but in 1998 you would have said exactly the same thing about hotels and taxis. 

But then there’s the middle question: again, there is a broad category of industries and products where there is a thing that can be automated and a thing that the customer is actually buying, and those might not be quite the same thing, and may now be split apart. Right now this question is especially concentrated around professional services: accounting, law, consulting, some kinds of medicine, and of course software development. 

But what is it exactly that you pay software developers or lawyers or consultants to do, and is that the same as the things you can automate?