Small Numbers, Big Power: How Log Tricks Make Neural Nets Tiny and Smart
Imagine your phone running smart features faster and using less battery, while the app still guesses nearly as good.
Researchers found a simple trick: store network numbers with a logarithmic style so tiny and large values get treated the way they matter more.
That lets a big model shrink down to just 3-bit numbers, and the drop in performance is barely noticed, thats real surprising.
Because most learned values are not spread out evenly, this log way fits them better, and that means you can ditch the heavy math parts — no bulky multipliers sitting in hardware — so devices run cooler and cheaper.
Training the whole system with a slightly finer log code at five bits gives even higher accuracy than old linear ways at same size.
This idea opens doors for smarter apps on small gadgets, wearables and other embedded devices, where power and space are tight, and performance still needs to shine.
Read article comprehensive review in Paperium.net:
Convolutional Neural Networks using Logarithmic Data Representation
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