– High-performance document parsers to rapidly ingest, text chunk and ingest common document types. – Comprehensive intuitive querying methods: semantic, text, and hybrid retrieval with integrated ...

The AI chip giant says the open-source software library, TensorRT-LLM, will double the H100’s performance for running inference on leading large language models when it comes out next month. Nvidia ...

Deploying a custom language model (LLM) can be a complex task that requires careful planning and execution. For those looking to serve a broad user base, the infrastructure you choose is critical.

Nvidia plans to release an open-source software library that it claims will double the speed of inferencing large language models (LLMs) on its H100 GPUs. TensorRT-LLM will be integrated into Nvidia's ...

Using these new TensorRT-LLM optimizations, NVIDIA has pulled out a huge 2.4x performance leap with its current H100 AI GPU in MLPerf Inference 3.1 to 4.0 with GPT-J tests using an offline scenario.

Dublin, Jan. 17, 2025 (GLOBE NEWSWIRE) -- The "Development Trends in GPU Cloud Access Technologies Amid the Rise of LLM and GenAI" report has been added to ResearchAndMarkets.com's offering. This ...

Until now, AI services based on large language models (LLMs) have mostly relied on expensive data center GPUs. This has ...

Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...