Apple hardware uses a unified architecture. That means the CPU and RAM are integrated together: it is very difficult/impossible to strip the RAM from these systems.
This unified architecture makes Apple hardware very good for AI work, where latency between RAM and CPU is very important
Even the SSDs (which are normally more strippable) use a proprietary hardware form factor.
I think the article mentioned the real draw:
> Apple noticeably promoted the ability to link multiple Mac Studios together into a single, more capable system for running large frontier AI models, a feature aimed at business and developer customers rather than everyday consumers.
(Couldn't read the source cited, might have more info: The Information)
I have been considering adding labels/filters based on sentiment analysis to my HN reader. I wonder if your classifier-based method would be more effective.
I added filters that blur posts from new HN accounts based on age/karma thresholds (as suggested by another HN user). However, instead collapsing, I just blurred them. This allows quickly peeking via hover. My reader also highlights posts with higher points/comments, and those orange highlights survive the blurring.
That’s very nice. Feel free to integrate if you want :) Just request https://classify.stylometry.net/violations/49458161 or whatever item ID (as long as it was posted later than a few weeks ago) and it will return the scores for that post/comment and all its children.
Wow that was quick :) Meh, I feel like comment points have become somewhat untethered to comment quality (at least assuming threads are roughly sorted by comment score). It’s a good heuristic usually but it’s wrong often enough for it to be difficult to rely on.
I want to improve the classifier scores too. There’s some parameters in the loss function I could play around with more when training which basically optimize for more false negatives or false positives. Problems with no ground truth are very frustrating lol (though I suppose dang/tomhow’s manually written warnings could be treated as labels instead of using labels from GPT, but I suspect there’s not enough of them).
For me, I'm not sure if "slow" is the right word. I think "delayed" or "sporadic" is more accurate.
Thoughts for me are like when a word is on the tip of your tongue, but you can't think of it right away. Often you'll think of the word later: you weren't actively thinking about it, but the thought was simmering in your mind and just randomly pops up.
You can add instructions in the CLAUDE.md/AGENTS.md file to modify output behavior like:
# Response Style
Keep routine answers concise. Lead with the result, include material caveats and the next action, and omit introductions, repetition, generic reassurance, and optional background. Expand only when the task requires explanation.
While writing a document I got good mileage out of doing something like this for every paragraph:
Let's analyze this paragraph:
- List the main points.
- Can any points be removed? (Do any points need to be added?)
- Reword each point. Be as succinct and clear as possible.
I'm not sure how many extra tokens it would consume to do this for every output. But it may be better than just asking for "TLDR pls"
(I've actually never used Claude Code. I've never had problems with verbosity in harnesses like OpenCode or T3-code. And recently I've been using Codex, not Claude models.)
> Big monitors are the easiest way to increase white-collar productivity, and anyone who makes at least $50,000 per year ought to have at least 1600×1200 screen resolution. A flat-panel display with this resolution currently costs less than $500. So, as long as the bigger display increases productivity by at least 0.5%, you'll recover the investment in less than a year.
- Comments have 3 LOD (L:full, M:single line, S:collapsed)
- Optimal default LODs
- Simple to expand groups of comments (direct replies, comment thread ("spine"), full sub-tree)
- Highlight specific users like OP, or other interesting users
- Search for text within thread (automatically expands LOD)
- Highlights new comments (since last visit or set time)
It matches the way I want to read HN comments, anyways.
reply