171–180 of 208 posts
Earlier quoted context omitted.
Fortunately, the whole chain of slicing, imaging, and analysis are now at least partially automated, so in theory you can repeat the process with nothing more than some time on the equipment and a bit of compute. In practice, I suspect there's a fair bit of grad student manual labor that keeps the pipeline flowing...
They crowdsourced three million manual corrections to the AI output, yeah.
Related: my favorite HN comment ever from a similar submission a year ago: > There's lots of very exciting work going on around the fully mapped fruit fly connectome. For example, I'm a CTO of a stealth startup that aims to do for utilitarianism what carbon credits did for environmentalism. We are selling 'utility credits' which translates directly into us simulating trillions and trillions of fruit fly brains in a s…
About as useful as the carbon credits themselves
Related: my favorite HN comment ever from a similar submission a year ago: > There's lots of very exciting work going on around the fully mapped fruit fly connectome. For example, I'm a CTO of a stealth startup that aims to do for utilitarianism what carbon credits did for environmentalism. We are selling 'utility credits' which translates directly into us simulating trillions and trillions of fruit fly brains in a s…
Interesting stuff, but I don't understand HOW they've done it. There's something called Connectome Annotation Versioning Engine (CAVE). Which appears to be software(?) which allows researchers to examine a dataset and annotate it in some way. Presumably the dataset consists of images of the neurons themselves and the job is to map which neurons touch which other neurons? That's the thing I am not understanding. How d…
The sections can be imaged with TEM or SEM in high vacuum, the block face can be imaged with SEM.
The resulting 3d volume can be segmented with neural networks.
CAVE is for manual editing / correction on top of the automatically generated segmentation.
It was my understanding that all this connectome-based research was largely a deadend, because it doesnt capture dynamics, nor a vast array of interactions. if you've ever seen neurones being grown (go search YT), you'll see it's a massive gelatinous structure which is highly plastic and highly dynamic. Even in the simplest brains (eg., of elgans), you get 10^x exponential growth in number of neurones and their conne…
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It’s a neural network without weights. And it doesn’t have a body. Figuring out the behaviour of the neurons could take decades, although I have no doubt that people will eventually. And simulating a whole fruit fly body seems like it’s going to be out of reach for a very long time.
> It’s a neural network without weights. It has approximate weights. Neuron connection strength is determined by the number of synapses (1-100s, sometimes 1000s), the type of synapse neurotransmitter, and the number of receptors. The connectome has 1 and 2 and is only missing 3. The number of receptors may not even be that important- the fact that the number of synapses is important may well mean the number of recept…
But the astrocytes are dynamically modulating the signal at the synapse, it doesn't seem like we really know "the" weight.
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This reminds me of the coastline paradox. I wonder if it applies to mapping an organism’s brain. For example, one can say they know the length of Scotland’s coastline but as the resolution increases, so does the coastline’s length. It’s infinite.
The resolution increases but the information doesn't. Apply some compression algorithm on the higher resolution coastline and you will find that you can reduce size massively. Same with LLMs and same with mapping the brain probably.
Do we have an accurate model of a single neuron or very small group of neurons? I understand the reality may be chaotic, but I would hope to have a simulation such that it mirrors the evolution of neurons to a reasonable extent.
No.
Many unknowns and even more being discovered regularly (e.g. tunneling nanotubes connecting neurons dynamically)
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About as useful as the carbon credits themselves
Curious if you could elaborate? It seems like the issue isn’t carbon credits, but the lack of a regulated level of carbon that would make them effective. Market incentives work best with dollar incentives, not virtue points.
So this kind of scenario has to be carefully taken into account in favor of scenarios which lead to actual emission reductions. It's not a simple fungible asset or commodity as some (naively) assume.
Related: my favorite HN comment ever from a similar submission a year ago: > There's lots of very exciting work going on around the fully mapped fruit fly connectome. For example, I'm a CTO of a stealth startup that aims to do for utilitarianism what carbon credits did for environmentalism. We are selling 'utility credits' which translates directly into us simulating trillions and trillions of fruit fly brains in a s…
They have a branding opportunity. Karma Kredits Perhaps a co-branding opportunity with Krispy Kreme donuts? Buy a donut, and experience some Joy, which handily comes with Karma Kredits to offset that Joy. Have some KK with the KK!