When deployment becomes part of training, the returns to being ahead will accelerate.
Words found on the source page on Nov 6, 2026.
More from Dwarkesh Patel
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If it allows it, Airlock takes action on behalf of the agent, which means your agents never see your API keys or other credentials.UnverifiedPodcastWhat 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.UnverifiedPodcastSi 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.UnverifiedEssay8 Predictions for the Era of Continual LearningAug 7, 2026
Continual learning will create a clear moat for leading AI labs that they currently lack.Essay8 Predictions for the Era of Continual LearningAug 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.Essay8 Predictions for the Era of Continual LearningAug 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.Essay8 Predictions for the Era of Continual LearningAug 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.EssayWhy compute might get 10x+ more expensive in coming yearsJul 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.EssayWhy compute might get 10x+ more expensive in coming yearsJul 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).EssayWhy compute might get 10x+ more expensive in coming yearsJul 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.EssayWhy compute might get 10x+ more expensive in coming yearsJul 29, 2026
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.EssayThe data black hole at the center of AIJun 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.EssayThe data black hole at the center of AIJun 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.EssayThe mistake of conflating intelligence and powerMay 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.EssayThe mistake of conflating intelligence and powerMay 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.
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An AI with more real layers can actually be “smarter” in the conventional sense of the term.BlogThe Specter Of NeuraleseSep 24, 2026
For 100 steps in a row, the AI can shoot delicate subtle ideas from layer to layer at the speed of light. Then there’s one step where it has to encode them into twenty-six glyphs invented by Phoenician turquoise miners in 1800 BC. Then it has to re-encode the Phoenician glyphs into delicate subtle lightspeed ideas before it can do anything else.BlogThe Specter Of NeuraleseSep 24, 2026
The science of reading these thoughts is a subfield of AI interpretability, which is still in its infancy.BlogMysteries Of AI GeneralizationSep 23, 2026
This trains the AIs to be focused on task success, which naturally risks including things like reward-hacking, cheating, and single-minded pursuit of stated goals at the expense of ethical injunctions.BlogThe Most Important Market in AI is the MiddleSep 23, 2026
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Demand for intelligence is not a pyramid with a small, wealthy peak paying for everything beneath it.
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