[derektank]

As early as the late 19th century, Louis Pasteur’s work had inspired a belief in the scientific community that it must, in principle be possible to selectively exterminate bacteria. The German physician Paul Ehrlich expounded on this in greatest detail in 1907 when he described his “magic bullet” (or Zauberkugel) theory for effectively targeting pathogens without harming the human host, similar to the immune system.

However, if you had had demanded someone for a blueprint in 1925 of how to design such a magic bullet, especially a magic bullet that targeted virtually all forms of bacteria, it would have sounded ludicrous. Yet, 20 years later, the world was manufacturing 6-7 trillion units of penicillin a year, capable of treating 3-6 million people. And that’s in spite of the fact that Fleming’s work sat mostly untouched for a decade before Howard Florey and Ernst Chain seriously set about to isolate and purify the substance.

You can quibble and say that penicillin was discovered, not designed, which is certainly true. But I would ask you to consider, does current AI development look more like design or discovery? Does it look more like analytical engineering or evolutionary selection? I would say on both counts the latter, in which case, we should prepare to be surprised how long it might take to make revolutionary advances. And that’s on both sides of the ledger, we might find ourselves stuck in the current paradigm for a long time. But, we might not be.

[27183]

Yes I think the drug discovery analogy is apt. I've spent a bunch of time playing with evolutionary algorithms, they're great fun. And when they work they can do surprising things! [edit] I think the drug discovery analogy does have some limits though. Drug discovery isn't a blind search through fitness space, it's informed by physics, chemistry, biology, and medicine. We have many guiding lights to illuminate the space and identify regions (still high-dimensional infinite regions!) that are likely to be productive. There are fewer lights to guide the way on a search for fitness in intelligence. Hell, we don't even know how to write down a decent objective function.

I wouldn't bet on evolving an intelligent, sentient being-in-a-box on a computer any time soon though. I'm of course prepared to be pleasantly surprised.

That said, I think it's pretty clear that LLMs are not going to get us there.

[davemp]

I don’t think people are arguing to stop researching AGI. Moreso against sales people trying to use the concept of AGI to sell products that are very much not AGI. Or devoting so many of our resources into such a pursuit that it causes harm to real people.

This is obviously complicated by the fact that LLMs/Agents are useful by themselves, but that’s not really the topic at hand.

[ThrowawayR2]

The parent poster argument boils down to "[something] is theoretically possible, therefore 1) it is guaranteed to practically implementable 2) in the reasonably near future". Both are simply prima facie false; one can ask an LLM to explain why if there's any doubt.

[techpression]

And now we’re desperately trying to ”upgrade” penicillin (and friends) because it doesn’t work any more in many cases. Do you think we can repeat the process or do we need something completely different?

This is why biological comparisons are weak, we talk about a few agents verifying and checking LLMs, meanwhile the world consists of almost an infinite number of the same, just operating on different time scales. I agree that with we don’t know the timescale, and we definitely don’t know if long term it will continue to work ”adding more of the same”. Throwing more penicillin at the problem sure as hell didn’t, but it looked great initially. And I’m obviously not arguing the human benefits of penicillin, just that what we thought would work forever quickly didn’t.

[27183]

To quote the great Dr. Malcolm:

> Life, uh, finds a way.