by jsomers on 3/21/24, 11:29 AM with 213 comments
by talkingtab on 3/21/24, 1:55 PM
Part of our problem is the way we think. I am a person. I am not a complex adaptive system. And yet I am. I am made of entities. There is a messaging bus, the entities sense, act and interact. But I don't think of myself as a CAS or talk about We. Wecellfs?
Perhaps this a Sapir-Whorf thing. Our language limits what we can think. What is the difference between a pile of ants and an ant colony? A colony is collection of entities, but what do we call the entity that is the colony? Are the ants smart or is the colony smart.
by seatac76 on 3/21/24, 12:36 PM
[1] https://www.amazon.com/Song-Cell-Exploration-Medicine-Human/...
by ta8645 on 3/21/24, 2:01 PM
Amen. You could easily teach quite intricate biology in grade school, if you focused on a fascinating example or two. How many more people would be inspired, rather than bored?
by jonnycat on 3/22/24, 1:36 PM
But of course, every neuron in the brain is bafflingly complex and we still don't know or understand how that complexity manifests itself in thought and intelligence. Given physics and the interactions of "things", every cell in the brain is more complex than the LLMs we're using today. Not to say that every cell is capable of producing the same output as an LLM of course, just that the behavior that it contributes to the overall system is that complex.
by the-mitr on 3/21/24, 2:28 PM
Instead of thinking in terms of a discontinuity between animals or putting humans categorically different, Bonner builds this idea of a continuum instead for both culture and learning. Of course there are differences,
https://press.princeton.edu/books/paperback/9780691023731/th...
This post of course goes deep in the rabbit hole so to speak.
by wslh on 3/21/24, 12:38 PM
[1] https://www.amazon.com/Biophysics-Computation-Information-Co...
by photochemsyn on 3/21/24, 2:51 PM
"Quantitative modeling of bacterial chemotaxis: Signal amplification and accurate adaptation, Yuhai Tu"
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737589/
The main points are:
* Both receptor cooperativity and accurate adaptation can be described quantitatively by simple mathematical models.
* An integrated model (the “standard model”), which contains both signal amplification and adaptation, is developed to predict responses of it E. coli cells to any time-dependent stimuli quantitatively.
* Exponential ramps induce activity shifts, which depend on the ramp rate through the methylation rate function F(a).
* Responses to oscillatory signals reveal that E. coli computes time-derivative in the low-frequency regime.
* E. coli memorizes the logarithm of the ligand concentration and the Weber-Fetcher law holds in E. coli chemotaxis.
It also goes into cooperative phase transitions in the receptor complexes as a means of signal amplification, using the same model as in Ising ferromagnetic spin-spin interactions in physics.
by londons_explore on 3/21/24, 1:34 PM
How close are we to being able to make a map of all atoms within a cell? There are 1E23 atoms in 1 ml of water, and an ecoli is about 500nmx500nmx1um. That means there are only about 2E10 atoms in the whole cell!
Would it be possible to somehow freeze a whole cell, then use an electron beam to knock off and identify (via mass) every atom there?
by dbrgn on 3/21/24, 12:11 PM
by nyc111 on 3/21/24, 12:16 PM
And the scale invariance of nature is clearly visible here. The cell is "small" compared to human scale but it is as complicated as any machine existing in human scale. There is no absolute small or big in nature.
by jmyeet on 3/21/24, 2:08 PM
The first is cell specialization, particularly neurons. It seems like nature really came up with a universal neuron. There aren't neurons for eyesight vs thinking, etc. They've experimented with this on frogs where they've reweired the optic nerve to a different part ofd the brain and the frog seems to see just fine. They've even added an eye and the frog seems to cope and use it just fine.
The second is the OpenWorm project [1]. This is an attempt to simulate a relatively simple organism with IIRC ~280 neurons. Despite lots of effort, the simulated version just doesn't match up to the real thing. In artificial neural networks we have a stupidly simplified model of neurons that tends to get reduced to a binary signal and an activation function. Thius can do a lot but it's clearly wholly inadequate for any realistic modelling. The protein interactions in a cell are mind-bogglingly complex.
The third is the three-body problem. To summarize, we have a general solution for the grvity interactions of two bodies. Add one more and we don't. We have classes of solutions but no general solution. This is why JPL needs to use supercomputers to calculate flight plans with a relatively low number of bodies. We see a relatively simple set of interactions lead to massive complexity with protein folding. I imagine that it just won't be computationally viable to simulate even a single realistic cell given all th einteractions that go on. We're simply left to make estimations.
by verisimi on 3/21/24, 12:36 PM
> We don’t yet have the technology to just observe all of the activity inside a living cell. That Goodsell painting above that shows the crowded cytoplasm packed with proteins is an artistic composite—backed by rigorous research to be sure—because there’s no way to capture all the different players in situ at once.
> A group at University of Illinois at Urbana-Champagne uses atomic-scale molecular dynamics simulations, in software, to understand structural details
> It’s a world that’s hard to see; sometimes you just have to imagine what’s going on down there, and back up those imaginings with the right experiments.
> One reason I’m particularly attracted to studies of E. coli chemotaxis is that it’s an early star of what’s been called “in silico” biology. It’s been the subject of many computer models.
Honest, at least.
by kaiwen1 on 3/22/24, 2:48 PM
by PcChip on 3/21/24, 12:03 PM
by javajosh on 3/21/24, 2:23 PM
I guess 'naming things' isn't just hard in CompSci.
by pmayrgundter on 3/21/24, 2:43 PM
So I believe intelligence arises from the cells and is an essential function of life, not only an emergent phenomena. The organs serve as division of labor amongst the cells in community for what they are already originally capable of themselves.
More musings in this direction https://sites.google.com/site/pablomayrgundter/mind
by sethammons on 3/22/24, 1:02 PM
Kinda felt similar to the cell comms. I wonder what interesting distributed coordination ideas we could learn in distributed systems computing from cellular biology.
by begueradj on 3/21/24, 2:53 PM
A person is billions of billions of more effective cells than an E.coli cell: still our sense of smell, drive and memory do not seem to be billions of billions times more efficient.
by janpmz on 3/21/24, 12:18 PM
by oersted on 3/21/24, 5:52 PM
by singularity2001 on 3/21/24, 1:22 PM
by retskrad on 3/21/24, 1:06 PM
by yehosef on 3/21/24, 2:42 PM
by bell-cot on 3/21/24, 1:19 PM
OTOH, English really needs another word, meaning "like intelligence, but it could be simulated by an analog computer with a good handful of of discrete components".
by swader999 on 3/21/24, 12:12 PM
by stephc_int13 on 3/21/24, 12:43 PM
We're still quite far from replicating this kind of tech.
by scrubs on 3/21/24, 11:36 PM
by chahex on 3/21/24, 3:49 PM
by crudcodersare on 3/21/24, 6:09 PM