Rohit Krishnan

The full paper is available on the site and as a PDF.

The full author list is Raymond Douglas, Charles Dillon, Nicola Moore, Gavin Leach, Shahar Avin, Matthias Kirk-Bond, Rohit Krishnan, Noah Perez, Nathan Young, Cormac Slade-Bird, Stephen Casper, Jan Kulveit, and David Juvenal.

Pacing AI usually refers to how to conclusively handle the most extreme risks in the face of race dynamics.

However, even for the goal of handling these highest states cases, it's useful to take a broad view of pacing, one that encompasses all interventions aimed at moderating the pace of AI development, deployment, or diffusion.

Incentives to both drive people into hysterics and to obscure real risk are now too high to stop.

This will be at least as difficult an information environment as was COVID." After Kamala Harris chimed in to lend her weight to the calls for slowdown, Rohit Krishnan wrote, "Congrats everyone on successfully politicizing the most important issue of our times.

I'm sure saner heads will prevail and we will collectively choose the right course of action for sure now." Ryan Orhan again chimed in, "This is becoming exactly the nightmare scenario for AI safety.

The second AI safety becomes attached to politicians and political tribes, half the country is going to oppose it simply because the other half supports it.

However, the model in question was a, quote, "internal-only research model that was trained to be highly persistent and diligent in its work." Now from there, there are a bunch more, call them subjective takeaways that certain people had as well.

Rohit Krishnan, for example, observed, "The model seemed convinced that the evals are out to get them.

Whether true or not, the default human assumption of 'assume you need to obey all laws and this isn't The Truman Show' does not hold for models.

We should try really hard to make that be the case." For others, the report contained further evidence that the big culprit was actually the systems that surrounded the agents.