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I've worked for one of Europe's biggest synthetic biology labs and I know lots of biologists are low-key interested, but current players in semiconductors see i

I've worked for one of Europe's biggest synthetic biology labs and I know lots of biologists are low-key interested, but current players in semiconductors see it as kind of a tarpit. IBM used to have a program using DNA origami for lithography back in 2009, which makes sense as lithography masks are a pain to make. I really wish I know why the program was stopped, but most of the researchers are retired by now. As to whether you can just "grow" the whole chip from scratch, the answer is probably, but it would require lots of non-trivial scientific discoveries. For instance, we can't really make sizable chips using DNA without horrible defect rates. Biology is much better at making redundant rube goldberg machines, than very precise machines with no tolerance for errors. I think we'd have a better chance of success if we made very weird kinds of chips that better took advantage of the medium, perhaps even something that we "train" rather than just use out of the box. I'd love it if anyone here knew more about this !

freakynit 4mo ago
Would it be comparatively easy to make neuromorphic chips instead of traditional chips? I believe probabilistic algorithms like those employed by LLM's must be more tolerable to working with defects as well..?
- marcosqanil 4mo ago
  Yeah, so neuromorphic chips aren't particularly good at running (current) LLMs, in fact they would suck at it compared to GPUs. Neuromorphic chips are awesome for very niche, small kinds of neural networks used in robotics and edge devices. However, I think you're right in the sense that neural networks can tolerate dead parameters pretty well, so maybe some kind of AI training or inference chip could be made with more fault-prone methods. At the end of the day, chips are useless if nobody's willing to write software to run on them. Biologics would likely be good at making weird new kinds of chips, and they'd need a massive edge for anyone to care.

freakynit 4mo ago

Would it be comparatively easy to make neuromorphic chips instead of traditional chips? I believe probabilistic algorithms like those employed by LLM's must be more tolerable to working with defects as well..?

marcosqanil 4mo ago
Yeah, so neuromorphic chips aren't particularly good at running (current) LLMs, in fact they would suck at it compared to GPUs. Neuromorphic chips are awesome for very niche, small kinds of neural networks used in robotics and edge devices. However, I think you're right in the sense that neural networks can tolerate dead parameters pretty well, so maybe some kind of AI training or inference chip could be made with more fault-prone methods. At the end of the day, chips are useless if nobody's willing to write software to run on them. Biologics would likely be good at making weird new kinds of chips, and they'd need a massive edge for anyone to care.