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Open-source AI without Jensen

Open-source AI without Jensen

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Summary
 The resignation of Nvidia CEO Jensen Huang is a major setback for the US development of an open model ecosystem. Nvidia still has the financial interests in supporting open models, which are to avoid concentration in power among a few customers who would develop their own chips and reduce Nvidia’s profits, but supporting the open ecosystem is a tricky puzzle more than an engineering problem to grind out a solution on.Nvidia’s business operations are famously extremely dependent on Jensen as an operator, so it is a consensus opinion that there are challenges ahead (or even more high-profile departures through chip-smuggling investigations or plain-old sharks circling more poachable talent). Nvidia’s number one goal is to stabilize the ship, deliver to customers in the next 24 months, and prevent implosion. Open models have been one of Jensen’s more ambitious, founder-style bets. He has been flooding the zone with funding in a way that will very likely dry up.Interconnects AI is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.In this period, the open model economy is in its nascency. These are crucial years for establishing use-cases, revenue flow, and motives to continue training the next generation models. I discussed the sensitivity of these early years in my recent talk at Fireworks Forge (slides, recording). The core of the argument is one upside for open models, a reason to be optimistic, and one downside.The positive case is that the open model economy has correctly latched onto “ownership of intelligence” and enterprise post-training as a crucial lane. What is to be determined is exactly how big the downstream market is.The downside is that the true long-term benefit of open models, as truly commoditized intelligence, is very far from realization with compute in such short supply. In the near term, where inference startups are also struggling to get enough chips (because Anthropic and OpenAI are buying so much capacity), there’s little margin competition on open-weight models. If open-source models are also served at giant inference margins, as we learned with DeepSeek’s DeepInfer release, they’re far from a commodity. In this paradigm, the closed labs with better economies of scale and integration from model to datacenter and chips will win. I expanded on this challenge in my recent piece on the open model economy.Together, a lot still needs to go right for open models to be a meaningful economic engine. Jensen’s support, and protection, gave the ecosystem time to figure this out.Jensen was more than a cheerleader. He would stop a lot of s**t from going wrong once early winds were stirring. He was willing to use his power on open models.There’s a major swell in Democratic government funding towards candidates that want to regulate the AI industry, fostering “safety”. Many of these people feel a need to do something and have general opinions that open models are unsafe, while not being educated on the complexities of their benefits. My biggest near-term worry is sloppy regulation at the state level, followed by national regulation. We’ve been one, strong Chinese open-weight model away from a crisis since this summer. It still holds – especially as we enter a new, turbulent equilibrium of cybersecurity. We have not seen a major hack driven by a popular Chinese open-weight model, but it is a matter of when, not if. We need someone to encourage caution and an ecosystem perspective when the “open-weight hawks” come hunting. Knocking over the open-source AI domino today is easy — if done, unwinding the downstream concentration of power, reduction in safety research, and stifling of long-term innovation is far harder. On public data, it looks like balancing long-term innovation versus short term risks, but this is due to how horribly hard it is to measure the open model economy (e.g. the most valuable aspects of it run on private infrastructure). It’s a recurring challenge facing the ecosystem and my work.As a brief aside, the extent to which the media ecosystem is revolving around timing today, rather than exact availability of information, is incredible. All of these Jensen affairs were known, but getting them out at the right time, right after the midterm political swing, took down the king.The same goes for the Jacob Coxon brouhaha this summer. All of that safety culture around top labs was well known, but the right timing around datacenters and the Overton window made it a national issue. This could very well happen at some point for open model safety, as it tends to be harm, risk, or safety-related narratives that drive the modern media algorithms. I cannot imagine my work on open-science driving such a media cycle, because it will never happen.The only lasting solution to this is to incubate a truly frontier open model player in the US. For example, I agree completely with Dylan Patel, CEO...
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