Home Speakers Dwarkesh Patel Quote If you’re spending most of your compute on inference, you’re kind of declaring that AI progress has stalled, because it’s not worth investing more in training, and your business is basically that of a cloud provider.
Words found on the source page on Nov 6, 2026.
More from Dwarkesh Patel Podcast What Robert Caro learned about power after studying it for 50 years Oct 30, 2026
If it allows it, Airlock takes action on behalf of the agent, which means your agents never see your API keys or other credentials. Podcast What will computer chips look like in 2045? Oct 22, 2026
There’s never been as big a shock to the semiconductor industry as the current surge in demand from AI. Podcast Si Sheppard – How did a few hundred Spanish soldiers topple two empires? Oct 1, 2026
That way, your software gets tested against scenarios you’d never imagine but that could still arise in the real world. Essay 8 Predictions for the Era of Continual Learning Aug 7, 2026
Continual learning will create a clear moat for leading AI labs that they currently lack. Essay 8 Predictions for the Era of Continual Learning Aug 7, 2026
I don’t think you can have AIs that perform whole jobs as competently as humans if they’re forced to just write Markdown files from session to session. Essay 8 Predictions for the Era of Continual Learning Aug 7, 2026
If you want to change what AI you are using, you basically have to fire an employee that has months of context on your organization and replace them with a fresh one that you have to retrain from scratch. Essay 8 Predictions for the Era of Continual Learning Aug 7, 2026
This is one of many reasons why I think it’s unwise to lock in some kind of regulatory safety regime right now. We simply don’t know what kind of technology we’re going to be looking at even in a year, let alone in five years or ten years, and we’d be entrenching an archaic and potentially counterproductive approach to dealing with the threats from AI. Essay 8 Predictions for the Era of Continual Learning Aug 7, 2026
When deployment becomes part of training, the returns to being ahead will accelerate. Essay Why compute might get 10x+ more expensive in coming years Jul 29, 2026
I want to emphasize the key conclusion here: as AI models become smarter, they’ll better monetize the same amount of compute. If a true human-level software engineer that could run on an H100 equivalent, at current market rates for software engineers, that H100 should rent for over $250k a year. Essay Why compute might get 10x+ more expensive in coming years Jul 29, 2026
I wish we didn’t live in a world with such strong economies of scale of intelligence (because I’m worried about power concentration). Essay Why compute might get 10x+ more expensive in coming years Jul 29, 2026
If by 2028 we’ve automated software engineering and the price of compute is 15x higher than it is right now, then it’s going to be much more difficult for you, with no revenue, to compete for compute against the frontier labs. Essay The data black hole at the center of AI Jun 19, 2026
I think the reason it is relatively easy for open source and previous laggards to catch up to within months of the frontier is that data is the real driver of progress. Essay The data black hole at the center of AI Jun 19, 2026
We see these AIs as a galaxy glittering with capabilities, but at their center, invisible to the naked eye, holding all the constellations together, is an unimaginably massive black hole of data. Essay The mistake of conflating intelligence and power May 16, 2026
But in the real world, power is more the product of having the authority and trust to get lots of people to collaborate with you, rather than some galaxy brain scheming capability. Essay The mistake of conflating intelligence and power May 16, 2026
I’m simply pointing out that the way AI systems are currently becoming smarter (by getting trained to be to be really good at specific economically valuable tasks like coding) is not that strongly correlated with power.
On the same topics Blog Banning self-recursive improvement in AI models? Sep 22, 2026
If the top U.S. labs have to give up on what is supposed to be really important, they will look very “catchable.” The policy creates a big incentive for some other parts of the world to invest a lot more in compute. Blog Frontier Overhangs Sep 21, 2026
A world with sufficient compute is one where intelligence is a commodity, and in commodity markets margin comes from a superior cost structure, which I would expect the leading model providers to have, in part because they have a meaningful lead in scaling and can apply superior AI to their infrastructure. Blog Why I still haven't bought into true RSI Sep 19, 2026
I have my doubts that the labs can afford to spend a constant portion of this compute on internal R&D as the total volume goes up, especially with plans to IPO, as they face increased scrutiny on basic economics. Blog Why I still haven't bought into true RSI Sep 19, 2026
It is important to not confuse massive steps in inference-time scaling, a dynamic which should be fairly predictable, with being the outputs of RSI, which is highly uncertain. Podcast Dwarkesh Podcast: Agent swarms, alignment, and recursive self-improvement Sep 17, 2026
If you have five hours, you’re probably going to do a lot better. The AI models are pretty similar. Filing NVIDIA Q2 FY27 earnings release (SEC Form 8-K, Exhibit 99.1) Aug 26, 2026
AI has reached its inflection point. It’s doing useful work. Its tokens are productive and profitable. Now, compute is revenue... About this quote 
Quotesby Glyph