Local AI refers to artificial intelligence systems that run directly on personal computers, workstations, local servers, or private infrastructure rather than relying entirely on cloud-based services. This approach is especially relevant for privacy, data control, reproducibility, cost management, and experimentation with open-source models. In healthcare, research, education, and software development, Local AI can support workflows such as document analysis, coding assistance, clinical text processing, knowledge retrieval, and agent-based applications while keeping sensitive data under closer user control. This tag collects articles on local language models, AI infrastructure, private inference, open-source tools, and practical workflows for building AI systems outside the cloud.
Series: The AI Giants Enter the CardiacSurgery ICU — “I Big entrano in corsia” – Clinical Challenge 1 A mean arterial pressure of 76 mmHg. Cardiac index 1.7 L/min/m². Lactate still rising. Has the patient improved? In the first episode I set GPT-6 Astra, Claude Fable 5.1 and Gemini 4 Argon a small clinical challenge, … Read more
Series: The AI Giants Enter the CardiacSurgery ICU — “I Big entrano in corsia” Three frontier AI models, twelve fictional clinical scenarios, seventy-two answers. Scoring them turned out to be harder than I thought. I expected differences. Some diagnostic shortcuts, a few questionable therapeutic choices, maybe one spectacular mistake (the kind that makes for a … Read more
Introduction For a few years now, “artificial intelligence” has mostly meant large language models. The routine is familiar: we type a prompt, the model returns a stream of words, and someone reads it (or some other piece of software parses it). Jev starts somewhere else. TypeSafe AI released it in September 2026 as its first … Read more
Abstract Running a language model locally gives you a kind of control that hosted chatbots often hide. LM Studio, Ollama, llama.cpp, vLLM, and similar tools expose settings such as temperature, top_p, top_k, min_p, repeat_penalty, and context length. The problem is that their names say very little about what an ordinary user will actually notice on … Read more
More Expensive, Slower but Actually Better? Every frontier release arrives with the same implicit promise. Better reasoning, better reliability, better behaviour on the hard cases. Higher cost too, of course, which tends to be presented as the price of that improvement rather than as something anyone is expected to verify. When GPT-6 Astra became available … Read more
A reproducible 300-question evaluation across medical exams, biomedical literature, multilingual question answering, and clinical calculation Meta released Muse Glimmer on 10 August 2026: thirty billion parameters, open weights, built for agentic work on consumer hardware.[1,2] I tested a quantized version five days later on a single NVIDIA RTX 3090 — partly because it was the … Read more
Hunting for the largest language model you can run on a personal computer has turned into a discipline of its own. Forums, repositories and social feeds circulate configurations that load models of 70, 120, even several hundred billion parameters, using consumer GPUs, generous amounts of system RAM and increasingly aggressive quantisation. The results are frequently … Read more
There is a specific moment, familiar to anyone who has gone down this road, when you finish downloading a model with “Med” in its name and realise you have no idea whether it is actually any good. The name promises domain expertise. The model card promises benchmarks. Neither tells you what happens when you ask … Read more
The most compliant place for a patient’s record to meet a large language model might be a machine sitting under your own desk. That sounds like a provocation. It is closer to a legal observation. In May and June 2026 the European Union rewrote part of its own AI rulebook, and most of the coverage … Read more
Upgrading a local AI workstation from an RTX 3060 12GB to an RTX 3090 24GB with real-world LLM, Flux and Whisper benchmarks. Article authored by Michele D. Pierri, MD Cardiac Surgeon & Medical Technology Researcher Last checked: June 10, 2026 Reading time: 5 minutes There are days when you don’t go to the operating room. … Read more