61–70 of 100 posts
This writing feels so strongly LLM flavored. It's too bad, since I've really liked Alexander Mordvintsev's other work.
Can anybody point out what's special about this?
I'm interested in a nearby, but dissimilar project, almost it's reciprocal, wherein you can generate a logic design that is NOT uniform, but where every cell is independent, to allow for general purpose computing. It seems we could take this work, and use it to evolve a design that could be put into an FPGA, and make far better utilization than existing programming methods allow, at the cost of huge amounts of compute to do the training.
This is exciting. Michael Levin best posited for me the question of how animal cells can act cooperatively without a hierarchy. He has some biological experiments showing, for example, eye cells in a frog embryo will move to where the eye should go even if you pull it away. The question I don't think he could really answer was 'how do the cells know when to stop?' Understanding non-hierarchical organization is key to…
Can anybody point out what's special about this?
The impression I got, and I'd be happy to have someone help me improve this impression, is that it's a way to craft a CA that behaves the way you want as opposed to the traditional approach to studying CA's which involves tinkering with the rules and then seeing what behaviour emerges.
This is exciting. Michael Levin best posited for me the question of how animal cells can act cooperatively without a hierarchy. He has some biological experiments showing, for example, eye cells in a frog embryo will move to where the eye should go even if you pull it away. The question I don't think he could really answer was 'how do the cells know when to stop?' Understanding non-hierarchical organization is key to…
> The question I don't think he could really answer was 'how do the cells know when to stop?' I'm likely missing something obvious but I'll ask anyway out of curiosity. How is this not handled by the well understood chemical gradient mechanisms covered in introductory texts on this topic? Essentially cells orient themselves within multiple overlapping chemical gradients. Those gradients are constructed iteratively, e…
I haven't thoroughly read all of Levin's papers, so I'm not sure to what extent they specifically address the issue of whether textbook models of morphogen gradients can or cannot account for these experiments. I'd guess that it is difficult to say conclusively. You might have to use one of the software packages for simulating multi-cellular development, regulatory logic, and morphogen gradients/diffusion, if you wanted to argue either "the textbook model can generate this behavior" or that the textbook model cannot.
The simulations/models that I'm familiar with are quite basic, relative to actual biology, e.g. models of drosophila eve stripes are based on a few dozen genes or less. But iiuc, our understanding of larval development and patterning of C Elegans is far behind that of drosophila (the fly embryo starts as a syncytium, unlike worms and vertebrates, which makes fly segmentation easier to follow). I haven't read about Xenopus (the frogs that Levin studies), but I'd guess that we are very far from being able to simulate all the way from embryo to facial development in the normal case, let alone the abnormal picasso and "eye on tail" tadpoles.
I wish we were all commenting about the ideas embedded in this paper. It intrigues me, but is out of my comfort zone. Love to read more content-related insights or criticisms rather than the long thread on the shamefully smooth, engaging, and occasionally rote style.
That said, I put in like 4 minutes skimming this paper, so my opinion is worth about the average of any Internet forum opinion on this topic.
Anyway, I suggest reading Wolfram as well on this, it’s pretty provocative.