powera

The priesthood doesn’t like that the peasants can read the Bible for themselves now.

I'm seeing very low quality results on LMStudio with this model. Worse than Gemma 3 12B.

It is getting questions like "David has 18 apples and Ivan has 7 apples. How many apples do they have together?" wrong half the time, while Gemma3 12B could very consistently answer that. Other smoke tests (like Chinese translation, and the infamous "Rs in Strawberry" test) also show poor results.

I don't know if it is a quantization/release issue, if the parameters needed for accurate responses have changed (i.e. it needs "thinking" tokens to handle its base error rate), or if the model has been so focused on audio/video that the text processing is bad.

He (or ChatGPT) is throwing spaghetti at the wall. Not having the standard API key be able to delete the database (and backups) in one call makes sense. "Wanting a human to type DELETE as part of a delete API call" does not.

I'm not sure they've found/understand it yet. My two main theories:

1. A bunch of people with new Claude Code codebases in December now are working with a larger codebase, causing more context. Claude reads a lot of code files, and doesn't effectively prune from the context as far as I can tell. I find myself having to hint Claude regularly about what files to read (and not read) to avoid having 75k of unrelated files in the context window.

2. Claude Code tries to do more now, for the benefit of people who don't know exactly what they want. The trade-off is that it's worse at doing exactly what people want, when they do know. The "small fix" becomes a large endeavor for Claude.

Click-bait title; the article goes on to say "Open source isn't actually broken" as long as you buy their product.

Wikinews never worked; the principle of "verifiability" that Wikipedia was based on simply doesn't work for news-collection, which requires trusted first-party accounts.

The project was also already dead; the English Wikinews has had 10 "articles" posted in the last 3 weeks, two of which were trivial sports stories (a second-division Queensland football match, and the retirement of a pitcher whose last substantial year in MLB was 2019). The most recent story is that an amateur jazz group recently played at a library.

It will no longer be an attractive nuisance to the few who stumble across it. Rest in peace.

(January 2025)

I've been waiting for this update.

For many "simple" LLM tasks, GPT-5-mini was sufficient 99% of the time. Hopefully these models will do even more and closer to 100% accuracy.

The prices are up 2-4x compared to GPT-5-mini and nano. Were those models just loss leaders, or are these substantially larger/better?