How to Achieve 1000x LLM Speed for Efficient and Cost-Effective Training, Testing, and Deployment

Too Long; Didn’t Read

How can you create LLMs at a fraction of the current cost, time, and manpower requirements? Here is one viable way that will blow your mind in terms of its simplicity and effectiveness.

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by Thomas Cherickal @thomascherickal. Multi-domain specialist and independent research scientist: https://thomascherickal.com & https://thomascherickal.net

Originally published at https://hackernoon.com.

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Binary Number Representation in LLMs

An Original Research Idea

Binary representations can enable more efficient storage and computations compared to floating point vectors in certain cases, perhaps even the general case.

Since binary vectors only need to store 0s and 1s, they require less memory and allow faster processing of certain operations like Hamming distance calculations.

This could be advantageous for very large vector datasets in training, testing, deploying, and production.