Synaptic update energy ranged from approximately 2.5 picojoules down to around 45 femtojoules. The devices also reproduced spike timing-dependent plasticity and maintained stable synaptic operation across roughly 40,000 electronic spikes.
The current deposition process requires temperatures of around 700°C, which exceeds standard CMOS manufacturing tolerances. "This is currently the main challenge in our device fabrication process," Bakhit said. "But we're now working on ways to bring the temperature down to make it more compatible with standard industry processes."
All materials used in the device stack are fully CMOS-compatible, and a patent application has been filed through Cambridge Enterprise .
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usertests I've been hearing about memristors for decades. It's not coming soon, like this: https://www.tomshardware.com/tech-industry/artificial-intelligence/thermodynamic-computing-could-slash-energy-use-of-ai-image-generation-by-a-factor-of-ten-billion-study-claims-prototypes-show-promise-but-huge-task-required-to-create-hardware-that-can-rival-current-models However, this does seem like the path we want to take. Low power, processing-in-memory, which could be similar to how neurons work. Neuromorphic systems built from memristors could reduce computing power consumption by more than 70%, according to the paper. Not 99.9%? And not to be confused with classical computing. Reply
bit_user What about density? How well can they scale down, using modern process nodes? Reply
Diogene7 The endurance seems far too low (10⁴–10⁵ cycles), and the retention time is also very limited (10⁴–10⁵ seconds!!!). For comparison, the FerroElectric Spin-Orbit (FESO) concept from the French lab Spintec could achieve an endurance of at least 10⁵–10⁶ cycles for inference, with retention times on the order of years or even decades. It therefore appears to be a much more promising concept. Reply
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://www.tomshardware.com/tech-industry/SPONSORED_LINK_URL
- https://www.tomshardware.com/tech-industry/new-cambridge-human-brain-inspired-chip-could-slash-ai-energy-use#main
- https://www.tomshardware.com
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Informational only. No financial advice. Do your own research.