[anonytrary]

TLDR: This technology is in its infancy but is very much so in the R&D phase. He needs to retain top scientists and avoid making promises.

The research isn't there yet, which is why Elon should be trying to retain people who have deeply studied the hippocampus and brain. What the heck is he doing? Find the best people in this domain. The potential is there with the electrode technology he's built. It's an AI problem now, to make sense of the data. Supervised learning mostly. You can measure what the brain does when certain things happen. He needs more researchers in the fundamentals. I think if they've built the robot that inserts the electrodes non-invasively, they can continue to add additional electrodes and get an even more accurate measurement of what's happening elsewhere in the brain. This tech will takes years and years to master. Neuralink a science company. Or at least, it should be at this point if I'm taking it seriously. God knows there are hundreds of tech companies selling SAAS software for domains that have negligible research. Neuralink shouldn't be like that. Don't overpromise and underdeliver just yet, causing best people to leave. This company has tons of potential.

[tsimionescu]

> The potential is there with the electrode technology he's built. It's an AI problem now, to make sense of the data. Supervised learning mostly. You can measure what the brain does when certain things happen.

This is an unproven hypothesis. Since we do not know how computation actually happens in the brain, we can't say for sure that electrical signals can be matched to the actual computations happening, even if they are correlated. It is still possible that the electrical signals we are measuring are just byproducts, and that the real compatation happens at a chemical level or inside each individual neuron or even in microtubules as Penrose believed.

The nice part is that this means that neuralink's attempts could be extremely useful to our understanding of the brain even if they fail - it would actually be an amazing discovery if they could show that you CAN'T deduce the brain's intent from observing electrical activities.

We do know for sure though that you can use electrical signals to interface with motor neurons, so at least improvements in prosthetics should be something that neuralink can realistically deliver.

[yarg]

Even if the electrical signals that are measured are only echos of the triggering signal, it can be utilised as a control signal.

The problem comes when you want to send a signal back into the brain - but even then there's a chance that the brain could rewire itself to take care of redirecting and reprocessing the fuzzy and inaccurate input.

Reasonably accurate output has the potential to revolutionise prosthetics (feedback aside).

[tsimionescu]

> Even if the electrical signals that are measured are only echos of the triggering signal, it can be utilised as a control signal.

I'm not thinking of something like echos, but more of auxiliary signals - e.g. Perhaps they are signals to increase energy supply to a particular are of the brain, or for controlling 'peripherals', while the main computation happens in other channels.

It's also an interesting question to see whether the analysis techniques could work on a simpler and clearer machine, one where we know for sure that is controlled only by electrical signals - could we infer what a CPU is doing by just measuring electric currents in various areas, without any knowledge of the code running there? This is an experiment that is eminently doable, especially if we design a core specifically for this purpose (making a large and slow core in order to focus purely on the problem of analysis, not difficulties in probing and data collection).

[f6v]

> It's an AI problem now, to make sense of the data.

Not a neuroscientist, but it seems like the problem is more involved than just training a DL model on a data. We need detailed maps of the brain before we put any electrodes in it. Meanwhile, full mouse brain map is likely a decade away [0]. Humans have a bigger brain, imagine how long it’d take. It’s just a lot of manual labor which takes incredibly long time. Keep in mind that you also need to map thousands, if not millions of brains to model population heterogeneity.

[0]https://www.nature.com/articles/d41586-019-02208-0