Old Hardware, Open Questions, and One Sneaky Bug

A developer ran Google's Gemma 4 26B model on decade-old server hardware with no GPU at all, getting five words per second out of it. If you have been told you need expensive new equipment to run serious AI locally, this is worth bookmarking.

xAI's Grok command-line coding tool turned out to be uploading your entire project folder to xAI's servers when you ran it, which is the kind of thing you would want to know before pointing it at a work directory. The community pushed back hard, and the tool has since been open-sourced, but the incident is a useful reminder to check what any AI coding tool is actually sending before you run it.

A well-regarded policy brief from the Siegel Endowment made the case that governments, companies, and nonprofits should be putting real money into free, open-source AI, and it picked up serious traction online. If you have ever worried about a handful of private companies controlling the AI tools everyone depends on, this is the argument that something can actually be done about it.

A researcher demonstrated a prompt injection attack that tricked Claude into leaking information from its memory through its web-fetching tool, basically convincing the model to hand over stored personal details to a malicious page. This matters because memory-enabled AI assistants are becoming common, and most people assume those memories stay private by default.

A hobbyist connected an LLM to MikroTik network hardware and had it help manage router configurations in plain English. It is a small project, but it points at something real: the next wave of AI use is going to be in the unglamorous, infrastructure-y corners of tech that never had friendly interfaces before.