The NeuroMem CM1K chip can solve pattern recognition problems for text and data analytics, vision, audio, and multi-sensory fusion with orders of magnitude less energy and complexity than modern microprocessors.
The chip features 1024 neurons, all interconnected and working in parallel, recognizing or learning one pattern in 500 nsec and this regardless of the number of neurons committed in the chip. The neurons behave collectively as a K-Nearest Neighbor classifier or a Radial Basis Function and are especially suitable to cope with ill-defined and fuzzy data, high variability of context and novelty detection. The neurons also feature a collective built-in model generator which means that learning is done in real-time on the CM1K chip. Last, but not least, multiple CM1K chips can be daisy-chained to scale a network from thousands to millions of neurons with the same speed performance and simplicity of operation as a single chip.
The behavior and architecture of the NeuroMem neurons is highly inspired by the human brain
- Queries or stimuli arebroadcasted to all the neurons at once
- Winner takes all and inhibits weaker responders
- The neurons know when they do not know and can therefore learn
- Auto-correct themselves if a teacher contradicts their original response
- Operate at low frequency (Mhz) and are low power
- The number of neurons is highly scalable
- Finally, the neurons offer a feature which nature cannot reproduce yet and that is the ability to save and restore their knowledge.
- Understanding the behavior of the neurons…Movie tutorials