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By trading heavy FP16 MatMuls for SRAM lookups and 1-bit additions, our custom quantization pipeline squeezes state-of-the-art models down to approx. 3 bits per weight with minimal accuracy loss. Here is how bypassing Tensor Cores could reshape the design of future edge AI chips.

In this blog post, we will discuss about Controlling reasoning effort in LLMs ( the gpt-oss-style ) and Calibrating LLM Reasoning effort via Label-Free Alignment.

Why deterministic query translation should often come before embeddings in enterprise RAG systems, and how to combine both in a hybrid approach.