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I think we have all the technical understanding we need to attempt such a thing, but the R&D costs for trying to get this crazy process to work would be astrono
by astrodust 10y ago
I think we have all the technical understanding we need to attempt such a thing, but the R&D costs for trying to get this crazy process to work would be astronomical and way beyond the budget of most university labs. I'm speaking mostly in terms of theoretical ability.
We have large scale FPGA devices. Adapting this to be not just reprogrammable in a formal capacity, but constantly self-reprogramming isn't a huge conceptual leap even if it is an enormously complicated thing to prototype and get working.
This is just how the technology behind the transistor made modern computers possible, we've just been iterating and refining on the same basic principle ever since, even though some of those iterations are very painful and expensive to get working. See the current pains around 10nm processes.
When I say we have the technology I don't necessarily mean we have the will or the budget to pursue it. As the costs come down it's inevitable someone will find a solution that's not billions of dollars, but instead mere hundreds of millions.
We're a long way from a proven, working design and process, but at least we can make such a thing, theoretically speaking.
- imaginenore 10y agoThe largest scale FPGA we "have" is probably UltraScale VU440, which you can't really buy yet. It has 4.4M logic units. Again, that's 6 decimal orders of magnitude on the number of neurons alone. Not sure about connectivity architecture. That's maybe enough to simulate the cockroach brain. http://wikipedia.org/wiki/List_of_animals_by_number_of_neurons http://wikipedia.org/wiki/List_of_animals_by_number_of_neuro... Don't get me wrong, I really really really want this to happen. I just doubt it will happen in the next 3-5 years. There are other challenges, main one being creating the right connections. It took a long time for the evolution to create and perfect our brain. And it was a highly parallel process too.