Now production-ready, llm-d can help orgs squeeze distributed inference performance from GPUs, potentially expanding AI ...
Contributors to the llm-d project announced llm-d 1.0, a Kubernetes-native distributed inference serving stack, on October 20 ...
CoOpt, an algorithm-hardware co-design framework that boosts large language model inference throughput by up to 13.43 percent ...
When OpenAI unveiled its Managed Agents platform at DevDay Monday in San Francisco — a system designed to let enterprises build, configure, and deploy AI agents through a unified hosted environment — ...
A research article by Horace He and the Thinking Machines Lab (X-OpenAI CTO Mira Murati founded) addresses a long-standing issue in large language models (LLMs). Even with greedy decoding bu setting ...
Run Reflection’s Beam model on Google Cloud AI Hypercomputer with llm-d and NVIDIA Dynamo for up to 5x higher throughput and ...
Architect's Liquid Inference auctions every LLM request across competing providers, locking a max price before the first token.
“Large Language Model (LLM) inference is hard. The autoregressive Decode phase of the underlying Transformer model makes LLM inference fundamentally different from training. Exacerbated by recent AI ...
Treat the LLM as a brain, not a source of facts. A practical guide to multi-agent LLM systems: prompts, orchestration, RAG, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results