The brick walls are there for a reason. The brick walls are not there to keep us out. The brick walls are there to give us a chance to show how badly we want something. (1/2)
In April he said AI was a multiplier and everyone has to use it.
If they're now facing a slop problem, that start's at the top.
AI is a multiplier. If it's being used to create slop grenades it's multiplying the things the leadership rewards.
Prepare yourself in Q3 for investors and founders doing a historic U-turn on their AI psychosis and dropping "insight" content signaling ahead of the curve thinking on AI "realism" which is practically 3 quarters delayed from the builder status quo.
"AI is likely to produce neither a job apocalypse nor productivity utopia, but something harder to measure: a quiet degradation of the quality of the jobs that remain," per Bloomberg
100 TB of RAM, saved by shrinking a consistent hash ring. The last 90,000 hashes per server were buying 0.7% load balance improvement. Math said stop. We stopped.
https://t.co/76XojaaDQG
Imagine being the strategist behind this “smart plot” and then the whole tech community calls your bluff in minutes.
Next few months are going to be interesting
Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead.
You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement.
I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible.
But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier.
Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want.
Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well.
So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it.
If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.
All the regulations being floated by frontier model companies must be viewed through the lens of them losing tokens to Open-Source models.
The timing of these regulations seems to line up perfectly with Open Source closing the gap significantly (but not completely) — and @nvidia going all in on open source in the last 60 days.
If we’re gonna regulate, why don’t we require that last year’s frontier models and weights be open-sourced?
Get ready for all of the investors in frontier model companies to suddenly flip to regulatory capture mode today
Their investments in frontier model companies are currently at risk/capped because the biggest buyers of tokens are embracing open-source models: vertical AI companies, the government and enterprises
That’s all this is about: stopping open source — which I’ve been saying on the pod for two years
If you want safety, you want disclosure — and open source is the ultimate disclosure process
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On tokens and prices per token.
I said I’d write more about this, so here goes: an OpenAI token != another model’s token. We compare AI prices in dollars per million tokens as if a token were a standardized unit, like a gram or a kilowatt-hour. It isn’t. Different models use and produce the exact same text using different numbers of tokens, which means a lower price per token does not necessarily mean a lower bill.
Imagine two identical pizzas. One is cut into 8 slices at $2 each. The other is cut into 16 slices at $1.25 each. The second place advertises cheaper slices, but the whole pizza costs $20 instead of $16. Bummer ... your stomach doesn't actually care about the number of slices you just ate.
I know you are hungry now, but back to tokens. In one small comparison spanning English, technical, multilingual, and numerical text, the tokenizer we use for GPT-5.6 Sol used 766 tokens versus an estimated 1,170 for Claude Opus 5. That's a very significant difference of about 34.5% fewer tokens. You can get the same exact text, but pay for all those extra tokens. The price per token doesn't really tell this story.
Even correcting for tokenizer differences misses the bigger point. What actually matters is price per successful outcome, and for that you can use benchmarks as a starting point, but really you have to try it and measure on your own use cases.
That's all. May the tokens flow.