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A colleague of mine in chemistry gave his thoughts on AI for protein folding recently: “things keep getting better, but they’re nowhere close to being good”. I
by aabhay 7y ago
A colleague of mine in chemistry gave his thoughts on AI for protein folding recently: “things keep getting better, but they’re nowhere close to being good”.
I think part of the issue at play here is the cost of confirming success, not simply the cost of generating a plausible solution. In most domains of AI that have shown success, the cost of confirmation is trivial (look at the image and check the label) whereas the cost of generating a plausible solution was high.
Like many AI fields, I believe that the real breakthrough will not be a direct approach, but an approach the solves the most pressing barrier to using AI in the first place.
- bobosha 7y ago> but an approach the solves the most pressing barrier to using AI in the first place. what do you think is the "most pressing barrier to using AI"?
- ethanbond 7y agoFrom my perspective, in the life-sciences space, it’s certainly the lack of high quality data. To be more specific, there’s tons of data, but it’s sloppy, lossy, and non standardized. Many of those discussing the promise of near future AI are either academics or new to the field. The real data landscape is so much worse than they would imagine it is.
- aabhay 7y agoThe cost of confirming success. If we can decrease the cost of going from theoretical protein to physical test, then I think the AI part will be quickly solved.
- TheGallopedHigh 7y agoI think the point here is slightly missed. Protein folding simulations are accurate ok hydro all models where brute force is used to explore the parameter space. The AI models could narrow that space and then employ the stricter models. Therefore I don’t think the cost here is great.
- deleted 7y ago[deleted]