nonotan t1_jdln1d9 wrote
Reply to comment by sweatierorc in [R] Reflexion: an autonomous agent with dynamic memory and self-reflection - Noah Shinn et al 2023 Northeastern University Boston - Outperforms GPT-4 on HumanEval accuracy (0.67 --> 0.88)! by Singularian2501
We already know of complex organisms that essentially don't age, and also others that are cancer-free or close to it. In any case, "prevent any and all aging and cancer before it happens" is a stupid goalpost. "Be able to quickly and affordably detect, identify and treat arbitrary strains of cancer and/or symptoms of aging" is essentially "just as good", and frankly seems like it could well already be within the reach of current models if they had the adequate "bioengineering I/O" infrastructure, and fast & accurate bioengineering simulations to train on.
ML could plausibly help in getting those online sooner, but unless you take the philosophical stance that "if we just made AGI they'd be able to solve every problem we have, so everything is effectively an ML problem", it doesn't seem like it'd be fair to say the bottlenecks to solving either of those are even related to ML in the first place. It's essentially all a matter of bioengineering coming up with the tools required.
SmLnine t1_jdlwhtu wrote
>but unless you take the philosophical stance that "if we just made AGI they'd be able to solve every problem we have, so everything is effectively an ML problem", it doesn't seem like it'd be fair to say the bottlenecks to solving either of those are even related to ML in the first place. It's essentially all a matter of bioengineering coming up with the tools required.
We're currently using our brains (a general problem solver) to build bioengineering tools that can cheaply and easily edit the DNA of a living organism. 30 years ago this would have sounded like magic. But there's no magic here. This potential tool has always existed, we just didn't understand it.
It's possible that there are other tools in the table that we simply don't understand yet. Maybe what we've been doing the last 60 years is the bioengineering equivalent of bashing rocks together. Or maybe it's close to optimal. We don't know, and we can't know until we aim an intellectual superpower at it.
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