TTT-Discover optimizes GPU kernels 2x faster than human experts — by training during inference
Researchers from Stanford, Nvidia, and Together AI have developed a new technique that can discover new solutions to very complex problems. For example, they managed to optimize a critical GPU kernel to run 2x faster than the previous state-of-the-art written by human experts.Their technique, called “Test-Time Training to Discover” (TTT-Discover), challenges the current paradigm of letting models “think longer” for reasoning problems. TTT-Discover allows the model to continue training during the inference process and update its weights for the problem at hand.The limits of 'frozen' reasoningCurrent enterprise AI strategies often rely on "frozen" models. Whether you use a closed or open reasoning model, the model's parameters are static. When you prompt thes [...]
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New ‘Test-Time Training’ method lets AI keep learning without exploding inference costs
A new study from researchers at Stanford University and Nvidia proposes a way for AI models to keep learning after deployment — without increasing inference costs. For enterprise agents that have to [...]
Baseten takes on hyperscalers with new AI training platform that lets you own your model weights
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The team behind continuous batching says your idle GPUs should be running inference, not sitting dark
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When the transformer architecture was introduced in 2017 in the now seminal Google paper "Attention Is All You Need," it became an instant cornerstone of modern artificial intelligence. Ever [...]
Together AI's ATLAS adaptive speculator delivers 400% inference speedup by learning from workloads in real-time
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Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference
The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use inference-tim [...]
AI inference costs dropped up to 10x on Nvidia's Blackwell — but hardware is only half the equation
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Inference is splitting in two — Nvidia’s $20B Groq bet explains its next act
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