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We're already doing those experiments. Tailor made mRNA vaccines targeted to one's own specific cancer mutations can be bought right now. The techniques are get

We're already doing those experiments. Tailor made mRNA vaccines targeted to one's own specific cancer mutations can be bought right now. The techniques are getting more sophisticated and more targeted every year. Our ability to predict what happens at these levels is improving by leaps and bounds too thanks to AI like AlphaFold. Anyone can be reasonably confident that no AI or teen can do this now or in the next few years, but are you really so confident what might be possible in 10 years?

alevskaya 7d ago
I worked in immuno-oncology: cancer vaccines work in melanoma where many things work because of the neoantigen abundance, they've generally been very mixed in efficacy. And even BionTech's BNT111 failed in melanoma! We have hope for these approaches but the reality of this stuff is way more nuanced than you think it is. Alphafold can't reliably predict thermal energy landscapes or make functional predictions - and how could it? It wasn't trained on anything that could capture structure - function relationships. Again, most people just have no idea how hard - fundamentally hard - molecular physics is to predict, and how necessary experiments are for any development of biological systems.
- naasking 6d ago
  > We have hope for these approaches but the reality of this stuff is way more nuanced than you think it is. Sure, everything has more nuance. The point is this stuff is available now; this isn't some future sci-fi, it's only going to get better, it's not the only research on gene targeting, and AI is starting to help with this research. By the time AGI is actually here, consider the breadth of knowledge and capabilities that will be at its disposal. > Alphafold can't reliably predict thermal energy landscapes or make functional predictions - and how could it? It wasn't trained on anything that could capture structure - function relationships. If your point is that the only reason an AI like AlphaFold can't make functional predictions is that we haven't trained an AI to do that, then unless you're arguing we can't or won't ever do that, I'm not sure how that's supposed to be an objection to the argument that AI will be able to make use of this information without doing all of the experiments people seem to think would be necessary. Like I said, we're already going to be doing these experiments because it's useful to us, and we will train AIs to make these predictions, again, because it's useful to us. Stop imagining what an AGI has access to now, and start thinking what it will have access to with the inevitable march of progress that we're already on. Edit: and of course, this doesn't even take into account the fact that an AI could acquire resources to pay people to do this research. The internet provides ample opportunities like this now.
owebmaster 7d ago
> but are you really so confident what might be possible in 10 years? Do you think we are finally 10 years away from curing baldness?

alevskaya 7d ago

I worked in immuno-oncology: cancer vaccines work in melanoma where many things work because of the neoantigen abundance, they've generally been very mixed in efficacy. And even BionTech's BNT111 failed in melanoma! We have hope for these approaches but the reality of this stuff is way more nuanced than you think it is. Alphafold can't reliably predict thermal energy landscapes or make functional predictions - and how could it? It wasn't trained on anything that could capture structure - function relationships. Again, most people just have no idea how hard - fundamentally hard - molecular physics is to predict, and how necessary experiments are for any development of biological systems.

naasking 6d ago
> We have hope for these approaches but the reality of this stuff is way more nuanced than you think it is. Sure, everything has more nuance. The point is this stuff is available now; this isn't some future sci-fi, it's only going to get better, it's not the only research on gene targeting, and AI is starting to help with this research. By the time AGI is actually here, consider the breadth of knowledge and capabilities that will be at its disposal. > Alphafold can't reliably predict thermal energy landscapes or make functional predictions - and how could it? It wasn't trained on anything that could capture structure - function relationships. If your point is that the only reason an AI like AlphaFold can't make functional predictions is that we haven't trained an AI to do that, then unless you're arguing we can't or won't ever do that, I'm not sure how that's supposed to be an objection to the argument that AI will be able to make use of this information without doing all of the experiments people seem to think would be necessary. Like I said, we're already going to be doing these experiments because it's useful to us, and we will train AIs to make these predictions, again, because it's useful to us. Stop imagining what an AGI has access to now, and start thinking what it will have access to with the inevitable march of progress that we're already on. Edit: and of course, this doesn't even take into account the fact that an AI could acquire resources to pay people to do this research. The internet provides ample opportunities like this now.

owebmaster 7d ago

> but are you really so confident what might be possible in 10 years? Do you think we are finally 10 years away from curing baldness?