Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.
Walk into any modern AI lab, data center, or autonomous vehicle development environment, and you’ll hear engineers talk endlessly about FLOPS, TOPS, sparsity, quantization, and model scaling laws.
A new technical paper titled “Towards Memory Specialization: A Case for Long-Term and Short-Term RAM” was published by researchers at Stanford University and Microsoft, and an independent researcher. ...
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