From FT Alphaville:
Still, while we’re doodling, it’s worth pondering once more whether the economics of making frontier models and monetising them before free-to-download open-weight versions catch up will really play out. According to Epoch AI we’re talking around four months of lead time:
Apologies to regular readers who have been through all this before, but there's some essential context that needs to be kept top of mind for this story.
We have already spent somewhere in the neighborhood of two trillion dollars on capital expenditures associated with the AI bubble. Major players are now a trillion plus dollars in debt. This is only on track to accelerate over the next few years. Capital expenditures are projected to total more than five trillion dollars by the end of 2030. God only knows what the borrowing would look like.
The justification for all of this money assumes not only that the demand for large language model-based AI will be in excess of pretty much any technology to date, but also that at least some of the major players currently spending that money will achieve extraordinary profits with very high margins. That second condition is exceedingly difficult to achieve with a highly competitive market and is even more difficult if that market were to be dominated by new players.
In a world where open-weight models dominate, the proprietary frontier models of Anthropic and OpenAI will find it virtually impossible to charge monopolistic pricing. Anthropic does have something of a reputational moat, particularly with respect to coding, but OpenAI would find itself in truly desperate straits, and as discussed before, in the highly interconnected and circularly financed world of AI, the company would probably drag others down with it.
Oracle would be completely screwed. SoftBank might be as well. Other companies like Nvidia would probably survive but would likely see a major hit to revenue. It is not difficult to imagine all sorts of catastrophic failure scenarios. Keep in mind, the growing consensus in the financial world is that we are looking at an enormous market bubble waiting to pop. Combine that with the precarious state of the private credit market, what may be a multinational debt crisis, and a United States presidential administration that almost certainly will not be able to deal quickly and competently with a massive financial crisis. If I really wanted to pile it on, I would say something about Ed Zitron's analysis noting similarities between the trillions of dollars of financing of data centers and the 2008 real estate bubble, but I'd hate to be that depressing.
Victor Tangermann writing for Futurism:
A Chinese open-weight AI model called Kimi K3, developed by Beijing-based firm Moonshot AI, has sent a shiver down the spines of AI tech executives. The powerful, 2.8 trillion-parameter model impressed with its competence, igniting a war with far more expensive alternatives being offered by the likes of OpenAI and Anthropic.
Top executives at both companies are sounding alarm, the Wall Street Journal reports, watching as Chinese open-weight models are rapidly catching up to their most powerful proprietary models. As a result, they’re begging the Trump administration to step in and protect them from the influx of cheaper alternatives, which could undermine their increasingly desperate attempts to attract new customers.
Dean Ball, who joined OpenAI as the head of strategic futures after helping shape AI policy for the Trump administration, was seemingly rattled, arguing that allowing Chinese open-weight models to take over would result in “AI communism” in a controversial and widely disputed tweet.
He also suggested the Trump administration would inject enough “fear, uncertainty, and doubt” through “regulatory risk” that would eventually deter hyperscalers from using Chinese AI.
...The incursion isn’t just coming from China. As the WSJ notes, US-based AI labs are starting to switch to open-weight models. Just last week, former OpenAI exec Mira Murati’s Thinking Machine Lab released its first model, which happens to be open-weight.
The trend could put AI companies in a bind: how can they keep financing their enormous AI data center projects and advanced model development if potential customers start switching to heavily subsidized or free AI models that provide good-enough or even frontier capabilities?
Early signs of an imminent exodus are certainly there. Moonlight AI was forced to pause new subscriptions to its blockbuster model just 48 hours after launch due to overwhelming demand, pushing its servers to capacity.
It’s a particularly precarious moment as frontier labs continue to hike up prices to start covering at least some of their unprecedented spending, despite growing fears over an AI bubble. Put simply, why shell out for Anthropic’s Claude Code or OpenAI’s Codex when there’s a far cheaper and highly customizable option out there?