273 GB/s of memory bandwidth (also only currently available with 48GB)
When it comes to inference speed, you want your model to fit in memory, and then to have as much memory bandwidth as possible. In this case a hypothetical Mini with 1TB of memory would still be over 2x slower with 27-35B models.
And FWIW I have an M4 Max MBP 128GB that I keep on a Roost laptop stand, with a separate keyboard/mouse/video. It does fire up the cooling jets when running local LLMs, but stays within tolerance for me on noise. I haven't heat-tested it on longer runs, but I imagine the risen airflow helps a ton.
FWIW I vibe coded https://github.com/astrostl/surplies to detect evidence of the Axios and LiteLLM malware, using StepSecurity's writeups as a data source.
FWIW I vibe coded https://github.com/astrostl/surplies to detect evidence of the Axios and LiteLLM malware, using StepSecurity's writeups as a data source.
Disagree. We all are — or should be — Linux kernel developers. What's more, we should align to a specific and singular VCS worldview informed by BitKeeper, which no longer exists, whether or not we used it. Therefore Git. Thank you for your attention to this matter!
The quality of the ChatGPT Mac app is a major driver for me to keep a subscription. Hotkeys work, app feels slick and native. The Claude Mac app I found so poor that I'd never reach for it, and ended up uninstalling it — despite using the heck out of Claude Code on a Max plan — because it started blocking system restarts for updates.
Yep. Consumer Reports' "Find a Car" page has sorting options for Overall Score, Road Test Score, Predicted Reliability, and Predicted Owner Satisfaction. I think they're a tremendous pro-consumer non-profit, and that a $39/year membership more than pays for itself by way of better major purchases.
Rivian, by the way, is the lowest-ranked of 26 covered auto manufacturers in terms of predicted reliability, below Ram and Jeep. The top 3 are Toyota, Subaru, and Lexus.
> That doesn't seem like enough to entirely shape worldwide discourse around nutrition and sugar.
IDK, see the "BLOTS ON A FIELD?" by Science ("A neuroscience image sleuth finds signs of fabrication in scores of Alzheimer’s articles, threatening a reigning theory of the disease") or "The 60-Year-Old Scientific Screwup That Helped COVID Kill" by Wired (regarding the anti-scientific refusal to acknowledge it as airborne) for a couple of recent examples. Once underlying assumptions stop getting questioned, I think anything is at least possible.
This is why I use Go as much as reasonably possible with vibe coding: types, plus great quality-checking ecosystem, plus adequate training data, plus great distribution story. Even when something has stuff like JS and Python SDKs, I tend to skip them and go straight to the API with Go.
Most recently (yesterday), vibe coding a better interface for Roblox screen time: https://github.com/astrostl/blockblox . Claude Code crushes, and I'm preferring Go for everything I can to take advantage of typing, quality ecosystem, and distribution. Still need to implement the QE side on this as I have on other things.
Having been through cycles of manual writing with '#' and having it do it itself, it seems to have been a push on efficacy while spending less effort and getting less frustrated. Hard to quantify except to say that I've had great results with it. I appreciate the spirit of OP's, "CLAUDE.md is the highest leverage point of the harness, so avoid auto-generating it" but you can always ask Claude to tighten it up itself too.
I have Claude itself write CLAUDE.md. Once it is informed of its context (e.g., "README.md is for users, CLAUDE.md is for you") you can say things like, "update readme and claudemd" and it will do it. I find this especially useful for prompts like, "update claudemd to make absolutely certain that you check the API docs every single time before making assumptions about its behavior" — I don't need to know what magick spell will make that happen, just that it does happen.
614 GB/s of memory bandwidth
> MacMini M4 with 64GB of RAM
273 GB/s of memory bandwidth (also only currently available with 48GB)
When it comes to inference speed, you want your model to fit in memory, and then to have as much memory bandwidth as possible. In this case a hypothetical Mini with 1TB of memory would still be over 2x slower with 27-35B models.
And FWIW I have an M4 Max MBP 128GB that I keep on a Roost laptop stand, with a separate keyboard/mouse/video. It does fire up the cooling jets when running local LLMs, but stays within tolerance for me on noise. I haven't heat-tested it on longer runs, but I imagine the risen airflow helps a ton.