powera
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.
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.
Ozempic for Broiler-Breeder Chickens
Many African families spend fortunes burying their dead
The Quinoa-Kitniyos Conundrum (2019)
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.
GPT-5.4-nano is less impressive. I would stick to gpt-5.4-mini where precise data is a requirement. But it is fast, and probably cheaper and better quality than an 8-20B parameter local model would be.
( https://encyclopedia.foundation/benchmarks/dashboard/ for details - the data is moderately blurry - some outlier (15s) calls are included, a few benchmark questions are ambiguous, and some prices shown are very rough estimates ).
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?
Nippon Life Sues OpenAI over Legal Advice to Ex-Beneficiary
Claude Code on the Web broken?
I have been trying to use Claude Code on the Web (and also mobile) this morning, and the LLM responses are never showing up. There is a diff generated (so something is happening), but the text is just "Computing...", "Determining...", etc.
Ask HN: Best multi-lingual text-to-speech system
I'm looking for a way to bulk-generate audio based on text files. Ideally, it would be a system I can run locally (M3 mac, 24GB RAM), and support at least 10 languages natively.I have tried a few systems (eSpeak, Piper, QWEN) and none of them have given satisfactory results. Huggingface seems to have no text-to-speech models with particular acclaim, either. I have been using OpenAI's...
The left is missing out on AI
Suneung: The day silence falls over South Korea (2018)
Two months ago, Claude was great for "here is a specific task I want you to do to this file". Today, they seem to be pivoting towards "I don't know how to code but want this feature" usage. Which might be a good product decision, but makes it worse as a substitute for writing the code myself.
The demo leans heavily on "choose the words for the sentence", which avoids spelling/keyboard issues, and maybe generalizes around the problems of N->N language maps better. The "decoy selection" for multiple choice answers also isn't great - I am getting sentences mixed with numbers for the translation of "three".
It also has the Duolingo-esque audio "reward" sounds. I personally hate them, but a lot of people feel otherwise.
What Is Genspark?
One of the Super Bowl commercials today was from Genspark.ai , a company I had not heard of before today. Their website looks like a generic ChatGPT clone. Their LinkedIn page boasts about their revenue, but doesn't describe what they do in a meaningful way.Has anyone heard of this product, or used it? Is this anything other than a thin wrapper around another company's LLM agent?
The "outliers" are posts that were deleted and re-submitted, or possibly boosted by the moderators. The "visible for 44 days" post was only submitted 14 days ago; either it was deleted or it is a glitch in this guy's script.
Please.
It is priced at about twice what people will expect, has very limited apps, and very limited "immersive media". Some of that will get better over the next year ... but a promise of "better next year" won't move units today.