Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...

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If you start naively without any library that avoids the problem then memory access is the problem. Have a look at how much effort is needed to avoid the problem, for example with blocking algorithms.

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.