Alas, it's not even close to "done." It's a work in progress and a surprisingly difficult one.
For context, the worm (c. elegans, at least) has a very stereotyped nervous system with 302 neurons. The anatomy, down to the cellular level, is known incredibly well. Their behavioral repertoire is not huge and they're fairly easy to study. Nevertheless, we can't even simulate a worm very accurately. (There was a good twitter thread about why yesterday: https://twitter.com/OdedRechavi/status/1086992699528544256)
The human eyeball has about 120M rods, 6.5M cones, and projects to a brain containing ~86B neurons, which is about 8-9 orders of magnitude more cells. The number of possible interactions scales even faster. In summary, we're not close, not at all....
When biology comes into play, you can see how weak our understanding and abilities are. We can barely simulate small proteins of a few thousand atoms. Accurately simulating an entire cell is (at the moment) in the realm of science fiction. Only inaccurate abstractions can be used to model it.
However I have to object in a way about the brain.
To me, there's an unanswered question: Is the rest of the human brain as simple and "generic" as the convolutional neural networks we made inspired by the vision system? Or is each networks' architecture and "algorithms" developed specifically for a task? In the latter case we might still be a very long way from anything resembling AGI.
However my personal estimation is that most of the things we do can be modeled using existing tools when scaled and modified appropriately (ie RNNs). There's also the ugly job of stitching those systems together, but it's not that different from what happens in nature.
The brain in question is 302 neurons, which is probably fewer than most of us have lost whilst participating in this discussion! But they also need to simulate a nervous system, mobility, food needs, interaction etc to have a remotely persuasive argument that a 302 node neural network actually resembles a worm brain. It can't be as smart as even a really stupid worm until it can perform analogous tasks to the worm, which means having some sort of artificial body to wiggle.
(parallel arguments but for human/mouse level complexity of bodies and stimuli responded to would suggest that whole brain emulation is going to be an incredibly painful way to attempt to achieve AGI)
Alas, it's not even close to "done." It's a work in progress and a surprisingly difficult one.
For context, the worm (c. elegans, at least) has a very stereotyped nervous system with 302 neurons. The anatomy, down to the cellular level, is known incredibly well. Their behavioral repertoire is not huge and they're fairly easy to study. Nevertheless, we can't even simulate a worm very accurately. (There was a good twitter thread about why yesterday: https://twitter.com/OdedRechavi/status/1086992699528544256)
The human eyeball has about 120M rods, 6.5M cones, and projects to a brain containing ~86B neurons, which is about 8-9 orders of magnitude more cells. The number of possible interactions scales even faster. In summary, we're not close, not at all....
When biology comes into play, you can see how weak our understanding and abilities are. We can barely simulate small proteins of a few thousand atoms. Accurately simulating an entire cell is (at the moment) in the realm of science fiction. Only inaccurate abstractions can be used to model it.
However I have to object in a way about the brain. To me, there's an unanswered question: Is the rest of the human brain as simple and "generic" as the convolutional neural networks we made inspired by the vision system? Or is each networks' architecture and "algorithms" developed specifically for a task? In the latter case we might still be a very long way from anything resembling AGI.
However my personal estimation is that most of the things we do can be modeled using existing tools when scaled and modified appropriately (ie RNNs). There's also the ugly job of stitching those systems together, but it's not that different from what happens in nature.
Not done. OpenWorm is a project to create a worm simulation. An important distinction.
More like “overdone”, it’s a cellular simulation including the brain as a first step.
The brain in question is 302 neurons, which is probably fewer than most of us have lost whilst participating in this discussion! But they also need to simulate a nervous system, mobility, food needs, interaction etc to have a remotely persuasive argument that a 302 node neural network actually resembles a worm brain. It can't be as smart as even a really stupid worm until it can perform analogous tasks to the worm, which means having some sort of artificial body to wiggle.
(parallel arguments but for human/mouse level complexity of bodies and stimuli responded to would suggest that whole brain emulation is going to be an incredibly painful way to attempt to achieve AGI)
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