133 summarised stories about Inference Optimization, each linking back to the original source. Browse all topics →
TechCrunch 2 months ago 15
Kog, a French startup, says it can accelerate large language model inference on conventional data-center GPUs via its Kog Inference Engine. It reported 3,000 tokens per second on a demo using Laneformer 2B, and CEO Gaël Delalleau expects its first major model to reach 10x speed by September. Kog is shifting from demos toward implementing larger models and using early customer traction to raise its Series A.
TheSequence 2 months ago 51
Inference systems turn a trained model into a streaming service that handles asynchronous user traffic, varying prompt sizes, and GPU scheduling for transformer computation. A described example uses a 4,000-token prompt requesting a 300-token answer. The shift is that “inference” is treated as a full request/token pipeline (tokenization, context assembly, routing, memory management, sampling, and streaming) rather than a single forward pass.
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TLDRocket
16 October 2026
The biggest thread running through today’s AI news isn’t model quality; it’s control—over cost, over context, and over what agents do once they’re let loose. Anthropic’s expected IPO pricing, with some investors floating a valuation near $2.3–$2.4 trillion after a roughly $1.8 trillion price target, sharpens the same executive question CFOs have been asking: even if unit costs fall via open models, total spend can rise as adoption broadens. That pressure echoes in Uvi’s argument that agent platforms “relearn” company knowledge and charge customers again—switching from direct tool connections that can cost $0.75–$1.41 (or more) per answer to a semantic-layer approach priced around $0.10–$0.16.
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