You can make the argument that Amodei is dishonest or that he suffers from psychosis.
However, he has made no claims that Anthropic has solved this, and expressing a hope to solve this in the next 5-10 years is hardly fraudulent.
That's why I think that something is very weird with his statements. Like, how would this even work?
The feedback loop is much, much, much too slow right now for AI to make things better.
Like, step 1 is build a digital model of the human organism. If you can do this, then yeah maybe the rest is possible. But step 1 is incredibly hard, so it feels unlikely.
That being said, I think the stimulants hypothesis upthread may be correct, as I've heard a lot of crazy stuff from friends on them.
If we linearly interpret the last year of progress from GPT-5 to Opus 5.5, times 5x, assuming no plateau, could such an intelligence realistically achieve a task like that?
Maybe also not, perhaps some form of RSI would need to deliver accelerating progress.
There are a lot of assumptions and speculation here. Still, at the end of the day, it does not seem that unlikely that they succeed in creating AI that can reason over so many parameters as to remove all intellectual bottlenecks from the process, leaving mainly the physical limitations.
And what is the limit there to building a good model of the human organism? I won't pretend that I know, but simply pointing to clinical trials, as some here do, instead of making an argument based on how such a digital model cannot be created seems unserious.
I don't think they are holding anything back in revolutionary results or internal models, a week before the IPO.
People are routinely claiming that as someone in tech, Amodei lacks credibility on biology and has no idea about science.
I'm yet to see someone claim his academic credentials validate his predictions.
I wasn't talking about Amodei specifically, but in general: my take is that overweighting credentials is probably the number one mistake that is made in evaluating whether a complete stranger is qualified to do something or not, especially in positions of power.
If you gather 500 PhDs and put them in one room, and 500 individuals without post-secondary education in another, give them all a quiz, I'm sure that the former room will outperform the latter room on average. Pick one of those 500 PhDs at random and I can probably find a topic where they're completely out of their depth, and perhaps even arrogantly so: https://en.wikipedia.org/wiki/Nobel_disease
The architecture of ML as it currently stands does assist us in modeling things like protein folding. But that's what they are; models. And before some person chimes in by saying "look how the AI pessimists move the goalposts", see my first point. Biological systems have high entropy and discoveries in biology often do not follow from preexisting discoveries whatsoever and are completely novel. Barring some quantum leap in ML design and architecture you cannot predict stochastically or deterministically how exactly a new enzyme will function in vivo. There is absolutely no evidence that Anthropic has solved this, even if they gobbled up every ML tool used in drug design and trained their models on every biomolecule known to man, it would not work because of fundamental gaps in what can be observed. They are a for-profit company trying to juice their IPO.
Now could LLMs and ML potentially speed up the pace of this research? Absolutely. But it's like saying a Formula 1 car is faster than a NASCAR. Yes, one is very clearly faster, but it's not as if the NASCARs are slow.