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Neuromorphic Computing

A human brain runs on twenty watts. A GPU cluster training a frontier language model draws several megawatts. The gap is six orders of magnitude....

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This Shipslides page presents Neuromorphic Computing as an interactive HTML presentation deck in the Future catalog with 31 slides. The share page keeps the uploaded deck sandboxed while exposing readable context, topics, and a slide outline for viewers and search engines.

A human brain runs on twenty watts. A GPU cluster training a frontier language model draws several megawatts. The gap is six orders of magnitude. Neuromorphic computing is the proposition that closing it is possible — and that the architectural recipe is brain-like rather than von-Neumann. Key sections include: Neuro morphic.; opening What if computers worked like brains?; chapter i Carver Mead's bet.; chapter ii The basic primitive.; chapter iii How spiking networks learn.; chapter iv IBM's 2014 chip.; chapter v Intel Loihi 1 & 2.; chapter vi Manchester's million-core machine.; chapter vii Heidelberg's analogue path.; chapter viii Event-based vision..

Key sections

  • 01Neuro morphic.
  • 02opening What if computers worked like brains?
  • 03chapter i Carver Mead's bet.
  • 04chapter ii The basic primitive.
  • 05chapter iii How spiking networks learn.
  • 06chapter iv IBM's 2014 chip.
  • 07chapter v Intel Loihi 1 & 2.
  • 08chapter vi Manchester's million-core machine.

Topics covered

futureneuromorphiccomputing

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Slide outline
  1. 01Neuro morphic.
  2. 02opening What if computers worked like brains?
  3. 03chapter i Carver Mead's bet.
  4. 04chapter ii The basic primitive.
  5. 05chapter iii How spiking networks learn.
  6. 06chapter iv IBM's 2014 chip.
  7. 07chapter v Intel Loihi 1 & 2.
  8. 08chapter vi Manchester's million-core machine.
  9. 09chapter vii Heidelberg's analogue path.
  10. 10chapter viii Event-based vision.
  11. 11chapter ix Compute-in-memory.
  12. 12chapter x The 10,000× claim.
  13. 13chapter xi What it's good at.
  14. 14chapter xii What it's not (yet) good at.
  15. 15chapter xiii Reservoir computing.
  16. 16chapter xiv Why brains, specifically.
  17. 17chapter xv Light-based neuromorphics.
  18. 18chapter xvi The competing edge.
  19. 19chapter xvii Brain-computer interfaces.
  20. 20chapter xviii The 2024–2030 roadmap.
  21. 21chapter xix Akida and the commercial play.
  22. 22chapter xx The skeptical case.
  23. 23chapter xxi Computation in nature.
  24. 24chapter xxii The people.
  25. 25chapter xxiii What we benchmark on.
  26. 26chapter xxiv Where to start writing code.
  27. 27chapter xxv Twenty essentials.
  28. 28chapter xxvi Watch & read.
  29. 29chapter xxvii Where this is.
  30. 30chapter xxviii Five takeaways.
  31. 31end of deck
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Updated
2026-05-17
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