Plateau: There may be unexpected development plateaus that come into effect at around human-level intelligence. These plateaus could be architecture-specific (scaling laws break down; getting past AGI requires something outside the deep learning paradigm) or fundamental to the nature of machine intelligence.
That doesn’t prevent any of those four things I mentioned: it doesn’t prevent (1) the AGIs escaping control and self-reproducing, nor (2) the code / weights leaking or getting stolen, nor (3) other companies reinventing the same thing, nor (4) the AGI company (or companies) having an ability to transform compute into profits at a wildly higher exchange rate than any other compute customer, and thus making unprecedented amounts of money off their existing models, and thus buying more and more compute to run more and more copies of their AGI
It doesn’t prevent (1) but it does make it less likely. A ‘barely general’ AGI is less likely to be able to escape control than an ASI. It doesn’t prevent (2). We acknowledge (3) in section IV: “We can also incorporate multiple firms or governments building AGI, by multiplying the initial AGI population by the number of such additional AGI projects. For example, 2x if we believe China and the US will be the only two projects, or 3x if we believe OpenAI, Anthropic, and DeepMind each achieve AGI.” We think there are likely to be a small number of companies near the frontier, so this is likely to be a modest multiplier. Re. (4), I think ryan_b made relevant points. I would expect some portion of compute to be tied up in long-term contracts. I agree that I would expect the developer of AGI to be able to increase their access to compute over time, but it’s not obvious to me how fast that would be.
Pause: Government intervention could pause frontier AI development. Such a pause could be international. It is plausible that achieving or nearly achieving an AGI system would constitute exactly the sort of catalyzing event that would inspire governments to sharply and suddenly restrict frontier AI development.
That definitely doesn’t prevent (1) or (2), and it probably doesn’t prevent (3) or (4) either depending on implementation details.
I mostly agree on this one, though again think it makes (1) less likely for the same reason. As you say, the implementation details matter for (3) and (4), and it’s not clear to me that it ‘probably’ wouldn’t prevent them. It might be that a pause would target all companies near the frontier, in which case we could see a freeze at AGI for its developer, and near AGI for competitors.
Abstention: Many frontier AI firms appear to take the risks of advanced AI seriously, and have risk management frameworks in place (see those of Google DeepMind, OpenAI, and Anthropic). Some contain what Holden Karnofsky calls if-then commitments: “If an AI model has capability X, risk mitigations Y must be in place. And, if needed, we will delay AI deployment and/or development to ensure the mitigations can be present in time.” Commitments to pause further development may kick at human-level capabilities. AGI firms might avoid recursive self-improvement to avoid existential or catastrophic risks.
That could be relevant to (1,2,4) with luck. As for (3), it might buy a few months, before Meta and the various other firms and projects that are extremely dismissive of the risks of advanced AI catch up to the front-runners.
Again, mostly agreed. I think it’s possible that the development of AGI would precipitate a wider change in attitude towards it, including at other developers. Maybe it would be exactly what is needed to make other firms take the risks seriously. Perhaps it’s more likely it would just provide a clear demonstration of a profitable path and spur further acceleration though. Again, we see (3) as a modest multiplier.
Windup: There are hard-to-reduce windup times in the production process of frontier AI models. For example, a training run for future systems may run into the hundreds of billions of dollars, consuming vast amounts of compute and taking months of processing. Other bottlenecks, like the time it takes to run ML experiments, might extend this windup period.
That doesn’t prevent any of (1,2,3,4). Again, we’re assuming the AGI already exists, and discussing how many servers will be running copies of it, and how soon. The question of training next-generation even-more-powerful AGIs is irrelevant to that question. Right?
The question of training next-generation even-more-powerful AGIs is relevant to containment, and is therefore relevant to how long a relatively stable period running a ‘first generation AGI’ might last. It doesn’t prevent (2) ad (3). It doesn’t prevent (4) either, though presumably a next-gen AGI would further increase a company’s ability in this regard.
It doesn’t prevent (1) but it does make it less likely. A ‘barely general’ AGI is less likely to be able to escape control than an ASI. It doesn’t prevent (2). We acknowledge (3) in section IV: “We can also incorporate multiple firms or governments building AGI, by multiplying the initial AGI population by the number of such additional AGI projects. For example, 2x if we believe China and the US will be the only two projects, or 3x if we believe OpenAI, Anthropic, and DeepMind each achieve AGI.” We think there are likely to be a small number of companies near the frontier, so this is likely to be a modest multiplier. Re. (4), I think ryan_b made relevant points. I would expect some portion of compute to be tied up in long-term contracts. I agree that I would expect the developer of AGI to be able to increase their access to compute over time, but it’s not obvious to me how fast that would be.
I mostly agree on this one, though again think it makes (1) less likely for the same reason. As you say, the implementation details matter for (3) and (4), and it’s not clear to me that it ‘probably’ wouldn’t prevent them. It might be that a pause would target all companies near the frontier, in which case we could see a freeze at AGI for its developer, and near AGI for competitors.
Again, mostly agreed. I think it’s possible that the development of AGI would precipitate a wider change in attitude towards it, including at other developers. Maybe it would be exactly what is needed to make other firms take the risks seriously. Perhaps it’s more likely it would just provide a clear demonstration of a profitable path and spur further acceleration though. Again, we see (3) as a modest multiplier.
The question of training next-generation even-more-powerful AGIs is relevant to containment, and is therefore relevant to how long a relatively stable period running a ‘first generation AGI’ might last. It doesn’t prevent (2) ad (3). It doesn’t prevent (4) either, though presumably a next-gen AGI would further increase a company’s ability in this regard.