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by auastro 1105 days ago
One of the early CorticalLabs founders here. This is like dissing AlphaZero because "This is not a new result; computers have been playing chess since the 50s!". We are standing, as always, on the shoulders of giants. Steve Potter is one of our advisors.

We've improved on every axis 10x. We process over 1000 signal channels in real-time and respond with sub-millisecond latency from our simulated environment. We've recorded thousands of hours of play time from mouse and human neurons. We're investigating biological learning with top neuroscientists from around the globe. This is by far the most rigorous, extensive and technologically advanced work on in-vitro learning ever produced.

Our work goes well beyond Hebbian, "fire together, wire together", We have follow up papers in the pipeline that study internal non-linear dynamics and show how whole-network dynamics changes during game play and learning. Being able to observe and measure cognition has huge applications to drug testing and discovery.

For background, frisco (the above commenter) helped start NeuralLink. Consider this, our DishBrain is a completely reproducible, highly controlled test bed for brain computer interfaces. This will massively accelerate neural interface development, all without sacrificing any chimpanzees.

> On the other hand, these cultures have essentially no advantage over digital computers and modern machine learning models

The brain is the single existing example of general intelligence. A human brain can do more computation than our largest super computers with 20W of power (a million times more efficient). Trillions of interacting synaptic circuits, rewiring themselves on the molecular level. Biological learning is the only game in town, honed by a eons of evolution. There are fundamental physical limits to hot slabs of silicon. Do you have a single credible proposal for building such a machine that isn't growing one?

> (I built a shitty counterstrike aimbot using a cultured neural network in college based on their papers.)

Nice humble brag. I trained neural networks from my bedroom in highschool in 2002. There is a long road between a cool university project and building a world class neuroscience R&D company, you know that!

CoriticalLabs is always open to collaborations. We're here to talk when you want to integrate some of our cutting-edge neuroscience technology with your work. Instead grumbling about the 90's, let's look forward to what neuroscience looks like in the 2030's

3 comments

> The brain is the single existing example of general intelligence.

This is incorrect. It is not pedantic to point out that we have never interacted with a "brain" in isolation: the human brain is an organ of the human organism. The human being is the single existing example of general intelligence.

> let's look forward to what neuroscience looks like in the 2030's

This is very interesting science without question. Are there existing ethical and moral frameworks guiding the development of your field?

All I’m saying is that I think it will be challenging to produce a commercial product that achieves product-market fit for an application other than basic neuroscience research. It’s a cool tool but the practical drawbacks are myriad, and when you say “the brain is the single existing example of general intelligence,” that’s true of the whole thing, with glial ion buffering, ephaptic coupling, global oscillations, and so much more. We should be honest here: the system being studied in DishBrain is very far removed from that, so it’s tough to use the existence proof like you are doing.

I hope I don’t come across as uncivil, but you guys alienated a lot of people both in how you talked about “sentience” and also seemed to heavily hype this as totally novel.

I would never root against cool progress in neural engineering, but I would be curious as to what you think your first big product will be based on this. Past attempts have usually ended up pivoting to stuff like artificial noses.

Edit: I tried to ignore it but the bad faith attack on neuralink, which, look, I have complicated feelings about too — you should know the animal use data in the press is extremely out of context (to the point of simply being wrong) and also neuralink has had zero chimpanzees in its entire history.

> “the brain is the single existing example of general intelligence,” that’s true of the whole thing, with glial ion buffering, ephaptic coupling, global oscillations, and so much more. We should be honest here: the system being studied in DishBrain is very far removed from that, so it’s tough to use the existence proof like you are doing.

Our vision is incredibly ambitious. We can't build a whole brain yet, only small 2D fragments. We have a roadmap that goes all the way to a complete synthetic biological intelligence. The short and medium term milestones are concrete, achievable and valuable. The long term goals are more speculative, we're clear about that. It's a path, a tightrope, but still a path.

> [...] but you guys alienated a lot of people both in how you talked about “sentience” and also seemed to heavily hype this as totally novel.

We clearly defined our terms, our paper was accepted via a long peer review process into a prestigious academic journal. We coauthored with multiple top neuroscientists from around the world. Our discussion section alone has more citations than most entire papers. If scientists are "alienated" by this, it's a grievance that we cannot remedy.

Our work was hyped, we hyped it, it deserves to be hyped. Can you cite an example in our own words where we claim our work is totally novel?

> I tried to ignore it but the bad faith attack on neuralink, which, look, I have complicated feelings about too — you should know the animal use data in the press is extremely out of context (to the point of simply being wrong) and also neuralink has had zero chimpanzees in its entire history.

Please accept my apologies; it was meant to be more collaborative. I really do think that our system could be used to reduce the need for animal sacrifices and this is a good thing. I also believe you take making animal sacrifices seriously.

Can you provide the missing context re Neuralink animal usage?
Unfortunately I can’t share specifics about Neuralink. But the general points I will make are:

- in this field, monkeys are high value animals and experimenters will often work with the same ones for many years; they are not, generally speaking, a high throughput model.

- to the extent a company does need to go through a large number of animals for a study, the way this works is you start by figuring out all of the problems you might be worried about, and choosing some rarity threshold to verify absence of (safety against), and then animal numbers are derived from the power calculation. For example, to rule out a potential complication to no more than 1% of patients with 95% confidence… you need a lot of animals, especially considering multiple study arms. This is the values tradeoff we as a society have chosen to make and empower our regulators to enforce. There is often a negotiation for the least controversial species to use that will satisfy the scientific goals.

> A human brain can do more computation than our largest super computers with 20W of power

The power needs of the human brain are likely to be measured quite accurately.

The same is not true of the "amount of computation" performed by the brain. How are you measuring that?

We can estimate the amount of information processed. Visual is like 10mbit [1] plus other senses it might be up to 100mbit. Only doing similar sensor fusion and extracting features in realtime on computer requires more power. But there's also the symbolic processing, doing something similar too requires much more power on computer. Then there is other stuff such as maintaining homeostasis we don't really know how to compute yet.

[1]https://www.eurekalert.org/news-releases/468943

> We can estimate the amount of information processed.

I'm not sure this makes sense. Here is a simple dynamic programming problem from Project Euler: https://projecteuler.net/problem=67

You can estimate the amount of information being processed in a few different ways. But that's not really relevant; the whole point of solving this problem is that you can do the same job with less computation than it looks like you need.

There is no particular connection between "amount of information processed" and "amount of computation performed".

There is a connection. How can any computation be done without moving information around? In absence of better measure, we can roughly estimate the computational complexity of a black box from looking on the input and output.

If the brain's job could be hypothetically done by some optimized system using an picowatt is irrelevant. We don't have such a system.