Most people assume local AI requires expensive hardware, but my real-world test on integrated graphics tells a different story.

Unlocking more RAM for local models.

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 ...

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 ...

As technologies change and adapt, we’re often left with seemingly useless junk that has nowhere to go. Certainly anyone still sitting on a pile of floppy disks feels this way sometimes, but odds are ...

As the demand for local AI workflows grows, understanding the differences between Neural Processing Units (NPUs) and Graphics Processing Units (GPUs) is increasingly important. NPUs are designed for ...

Local AI tools are more powerful than ever, but most of the magic ain't happening on NPUs—much to Microsoft's disappointment, I'm sure. For the last few years, the term “AI PC” has basically meant ...

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.