I assign essentially 0% probability that Anthropic or OpenAI will slow down frontier development in any meaningful way.
And that majority of the "regulation" they try making is regulatory capture to slow down competition.
1. Anthropic/OpenAI will not willingly hand over their lead to Gemini, xAI, Meta, or another frontier lab.
-> Elon will want a slowdown to catch up with OpenAI.
-> OpenAI will want a regulatory framework to slow down xAI + competition.
Every lab has an incentive to support rules that constrain competitors more than they constrain itself
2. The US is not going to meaningfully slow frontier AI development while China continues advancing. (as seen with Trump's post today about rejecting AI slowdown).
It would be probably the most flagrant national security risk if China leapfrogged the US in capability.
Especially when both sides have called frontier AI capabilities "cyber nuclear weapons"
3. China will not slow down frontier AI development. That is a given.
It will be theater if any of these parties agrees so publicly, because behind the scenes:
-> They'll likely keep on progressing, whether it's OpenAI, the US Government, or China.
If they wanted to slow down, they could have done so themselves at any point in time:
Yet everyone is still fighting over the scarce resources to run AI as seen with memory procurement from Samsung going all the way to 2031.
Or the $NVDA / $AVGO supply constrained 70-100%+ Y/Y growth protections.
So I suggest people unfollow the clowns on X that predict AI stocks from $NVDA to $TSM to $MU will crash for engagement.
All this does is cause retail to panic short term and hand over the keys to the kingdom over to others.
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: https://t.co/OGyPb7yaYt