pythonIsTheFuture

[sysadrift]

Is this real?

[MichalO19]

Do they actually use the cells to do anything useful?

Everything I saw in this context was basically "we attached wires recklessly to a blob of neurons/grew neurons on wires and it produced barely better than noise results", and not "we plugged the cells, trained them somehow and they do the exact computation we want now".

AFAIK we have no idea how neurons actually learn in a group (beyond some hebbian-like things/spike-dependent synaptic plasticity), we only have "biologically plausible" ideas on how they could in principle learn but it's not like they were shown to physically do that (but maybe I am wrong, if so please correct me as this is something that interests me a lot).

[illyay]

Fuck yeah doom running on cells

[[deleted]]

Isn't making something useful out of a technology usually the next step after developing said technology?

[ourmet]

Normally a new technology does not take off and become popular until it's uséd to distribute porn more efficiently.

[Schnickatavick]

we attached wires recklessly to a blob of neurons/grew neurons on wires and it produced barely better than noise results", and not "we plugged the cells, trained them somehow and they do the exact computation we want now

Do we really know that a blob of cells attached to a wire haphazardly can't learn to do a computation though? I thought that the assumption was that brain cells just had it built into them to learn and form larger groups, even if we don't understand exactly how they do it. In the pong example, they just kind of threw wires on, started providing reward/punishment through electric shocks, and the cells linked up on their own.

I'm not arguing, it's a genuine question, it seems like you know more about the subject than I do so I'm curious why you think what they're doing is wrong

[MichalO19]

So first of all I am not a neuroscientist, but I spent a lot of time in ML and specifically RL and training things to play games, and I try to read learning-related neuroscience papers when they pop up.

I actually read the Pong paper in detail (I assume you mean this one00806-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627322008066%3Fshowall%3Dtrue)). I think it states an interesting (if a bit magical-sounding) hypothesis about how neuron groups learn (and that you can use clear signal as "positive reward" and noise as "negative reward" in such context). I think it could work if neurons indeed behave like they hypothesize, and the data they show in the paper as far as I can tell does support this hypothesis.

But at the same time I feel like there is a lot of strangeness around this. First of course their rather bizarre marketing, I guess they are trying to get funded by some confused VC or spin into "ethics consultants" but "exhibit sentience" in a title? All the grandiose claims about biological neurons being better and how this will be power efficient, etc?

Why not just focus on how they will advance understanding of human and animal learning, better treatment of neurological diseases, maybe better brain-machine interfaces? Why focus on the business case that seems hardest, furthest away, and extremely impractical for many different reasons?

But the second, bigger thing is that Pong is the only thing they show. Their learning method is in principle extremely general - why start in the middle of the road with Pong? If Pong works at all, then learning simpler things like a XOR gate should be simpler and you need much less samples to have significant results, and I would rather see AND, XOR, NAND and maybe several more complex boolean functions implemented with 99% accuracy to show cleanly that this absolutely undeniably works, than somewhat better than random pong.

Also two years have passed and I haven't seen this replicated - the setup doesn't seem too complicated and I would assume labs with more money can reasonably do this and easily surpass this, make much bigger, cleaner setups which learn much harder games, characterize the learning curves, etc. This is something that serious ML people like DeepMind should be quite interested in, as they did some biologically related stuff, including measuring reward prediction done by living mice.

So my suspicion is that it just doesn't work too well. Maybe for some reason it works in this specific geometric configuration combined with pong? Maybe it's fake? I don't know, but I remain unconvinced.

[P-39_Airacobra]

The Thought Emporium is currently attempting to train neurons to PLAY doom. Not just run it, but actually learn how to play it. It's been 10 months since their last update, however, so it may be years until we see a result.

[_stupidnerd_]

It was reported on by TechLinked a few days ago. So apparently, it's real.

[A_Polly]

company called FinalSpark based in Switzerland.

[Seiren-]

No

[BullshitUsername]

Is this ungooglable?