Slow but useful ...

I finally stopped babying my MacBook.

Chat With RTX works on Windows PCs equipped with NVIDIA GeForce RTX 30 or 40 Series GPUs with at least 8GB of VRAM. It uses a combination of retrieval-augmented generation (RAG), NVIDIA TensorRT-LLM ...

David Nield is a technology journalist from Manchester in the U.K. who has been writing about gadgets and apps for more than 20 years. He has a bachelor's degree in English Literature from Durham ...

Nvidia has launched an AI chatbot called Chat with RTX. It offers Windows users with Nvidia GeForce RTX GPUs a way to create a local LLM AI chatbot that links up and uses the content on their PC. When ...

Tom Fenton explains how local AI fits into the broader private AI discussion for VMware environments, distinguishing enterprise-scale private AI deployments from smaller local AI setups running on ...

ChatRTX is a demo app that lets you personalize a GPT large language model (LLM) connected to your own content—docs, notes, images, or other data. Leveraging retrieval-augmented generation (RAG), ...

Even an older workstation-class eGPU like the NVIDIA Quadro P2200 delivers dramatically faster local LLM inference than CPU-only systems, with token-generation rates up to 8x higher. Running LLMs ...

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.

' LLM Checker ' is a CLI tool that scans your PC's hardware and recommends locally executable LLMs, and is characterized by its full integration with Ollama. Pavelevich/llm-checker: Advanced CLI tool ...

For the last few years, the term “AI PC” has basically meant little more than “a lightweight portable laptop with a neural processing unit (NPU).” Today, two years after the glitzy launch of NPUs with ...

A new technical paper, “Characterizing CPU-Induced Slowdowns in Multi-GPU LLM Inference,” was published by the Georgia Institute of Technology. “Large-scale machine learning workloads increasingly ...