Tracked topic
Large language models are machine learning models trained to predict and generate text and other language-based outputs.
…Conferring with a colleague, they noticed that "LLM-assisted hunters were converging on the same bugs almost simultaneously." This conclusion is further backed up by triage engineer @d0rsky, who notes that once…
…Improving the training of an LLM requires an influx of new and improved information, which is why Karp claims that frontier labs are double-dipping by both selling customers LLM utilization all…
…The reductions in both compute and HBM make it less attractive for LLM training and inference. The standard Instinct MI455X has 432 GB of HBM4 and 19.6 TB/s of bandwidth…
…Why focus so much on memory bandwidth for local LLM performance to begin with? To keep it very short, the decode phase of LLM inference is virtually always sequential. Every output token…
…The research team found that an LLM will hallucinate the location of a recent code repository up to 85% of the time, a figure that can reach 100% for trending agentic skills…
…The LLM enthusiast has designed “a fully offline suitcase robot [based-] around a Jetson Orin NS Super 16GB” called Sparky. It runs Gemma 4 E4B locally, includes 30+ sensors for context awareness…
…For the kind of things I’m using AI for, even the bleeding-edge frontier models aren’t much better than the local LLM options, though I appreciate that there’s a…
…Earlier this year, the company claimed that DeepSeek, Moonshot, and MiniMax used 24,000 fraudulent accounts and made 16 million exchanges collectively to train their own AI LLMs on Claude’s output…
AI-generated slop code has been a plague for some open-source projects, namely but not only Gentoo Linux, Curl, and Ghostty, limiting or outright banning LLM-created contributions. And yet, just…
Fancy a gaming laptop that's a little different? Something that can be used to play games, run small local LLMs, and even transform into a tablet for on-the-go use…