RFC: Synapse Yellow Paper – Synapseai

  • RFC: Synapse Yellow PaperTL;DR: Yellow paper here.At Synapse we’re building a global decentralized brain that anyone can help build and tap into.Decentralized topologies look alike, whether they’re the internet or the pathways in our brain.When the team originally launched the very first version of our white paper we included everything we were…
  • We ended up with a bunch of feedback that resulted with us creating more of a marketing brochure rather than any technical exposition.We’ve set-out to create that experience inside our yellow paper.
  • The balance between verbosity, succinctness, and technical detail, without being pseudo-technical is what we’re striving for.
  • This is an open, living, and versioned document so expect revisions and upgrades.This is also a Request For Comment (RFC) so we’re looking for feedback from the community on what more we can add or explain, and any contributions anyone would like to add.Best,The Synapse TeamCome visit with us on…

When the team originally launched the very first version of our white paper we included everything we were thinking about, all the questions, and answers that had come up while architecting the…
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Artificial synapse could be key to brain-like computing

Artificial synapse could be key to brain-like computing  #ai

  • It behaves like a transistor, with one terminal regulating the electricity flowing between two others.
  • While it’s not exactly natural, it’s largely made out of carbon and hydrogen, and should be compatible with a real brain’s chemistry — the voltages are even the same as those that go through real neurons.The ultimate aim is to create neural networks that exhibit more of the properties of their fleshy equivalents, and they’ve achieved some degree of success.
  • There’s only one synapse so far, but the team has shown that a simulated array of them could accomplish real computing tasks with a high degree of accuracy: the network could recognize handwritten numbers after training on three data sets.
  • The biggest challenge is shrinking the synapse so that it achieves true synapse-like efficiency (they’re still using 10,000 times more energy than a real synapse needs to fire).
  • If scientists can get anywhere close to that, though, you could see neural networks that are not only low-power, but are safe enough to interact with real biology — think AI-driven implants.

If you’re going to craft brain-like computers, it stands to reason that you’d want to replicate brain-like behavior right down to the smallest elements, doesn’t…
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