anon373839

4 ms·

31.
by anon373839 1mo ago
Does anyone have an idea how this might perform on a DGX Spark at longer contexts? I've been trying to investigate their performance with these medium-sized MoE models, but I'm seeing a lot of incomplete and conflicting informatio
32.
by anon373839 1mo ago
That's an interesting paper, but there is virtually no discussion of reasoning behaviors or optimization for long-horizon tasks (i.e., all of the recent advances in LLMs that people care about). The evaluation methodology also is prett
33.
by anon373839 1mo ago
How about proof that black-box distillation can deliver these results without a very sophisticated RL pipeline doing the heavy lifting?
34.
by anon373839 1mo ago
It's fun to imagine that it could be GLM 5.3-Flash. Between GLM 4 and 5, the flagship's total parameters doubled and the active parameters went up 25%. GLM 4.7-Flash was 30B / 3B active. If this model were 60B / 4B activ
35.
by anon373839 1mo ago
Agreed. I think LLMs are best used as pair programmers or typists for users who already know what they’re doing. Or as tutors for users who want to learn. Vibe coding is mostly garbage. But it can be useful for creating instant, disposable
36.
by anon373839 1mo ago
This is such a tough problem. Anthropic would need access to some kind of technology that could, like, intelligently handle unforeseen circumstances and nuances. Yeah, that’s definitely not something we should expect of them.
37.
by anon373839 1mo ago
The issue is that, if there is a “good enough” point approximately here, it is only a matter of time before models become small and efficient enough not to need all those data centers. Though, it should be good for companies that sell compu
38.
by anon373839 1mo ago
GPT-OSS 20B didn’t really merit the fanfare even when it was released; it’s definitely not competitive now. Even the 120B version has been well eclipsed by smaller LLMs at this point. The last version of Qwen 27B/35B was better, and no
39.
by anon373839 1mo ago
> We've been seeing that headline for a few weeks now and I really don't understand the problem. It’s powerful symbolism. It reminds me of that tone-deaf iPad ad that sparked outrage in 2024. The one where all the cultural arti
40.
by anon373839 1mo ago
But it’s the most useless canary ever. We already know that certain topics are taboo in China. As for all the other uses the models have, it seems pretty clear they’re not doing anything weird. If they were, people would be posting example
41.
by anon373839 1mo ago
This, 100%. I don’t think the industry knows how to scale LLMs’ general intelligence much further. The training paradigm is about maximizing very specific behaviors / very specific tasks, but doing lots and lots of them. Which can crea
42.
GOP issues stark warning to AI companies(axios.com)
6 points by anon373839 1mo ago|5 comments
43.
by anon373839 1mo ago
… while concentrating immensely more wealth and power in the hands of a few weird and depraved people.
44.
by anon373839 1mo ago
> how do you differentiate a non-addictive platform vs an addictive platform? Legal systems have dealt with these sorts of slippery definitional issues for centuries! In this specific case, I would venture that the applicable legal stand
45.
by anon373839 1mo ago
Police can and should be reined in. There are so many better levers that can be pulled to do this, if only the political will were present. A technofeudalist surveillance state is a poor solution.
46.
by anon373839 1mo ago
> How does this have value? Is any and every sentence in an e-mail considered 'fact' and thus to be fed into the AI? I have a hunch what this is for. AI companies want to make bigger inroads into nontechnical work settings. But
47.
by anon373839 1mo ago
The gains from increased parameter scaling are sublinear: there's no more hockey-stick improvement to be seen going in that direction. That doesn't mean some improvement isn't possible - it's just going to be increasingl
48.
by anon373839 1mo ago
> The top model from 2025 looks silly compared to the top model of the first half of 2026. Do you feel like progress has stalled? I do. Pre-training is where the industry saw the “emergent properties” of LLMs arise and, for a time, peopl
49.
by anon373839 1mo ago
The models are post-trained on these prompt additions so they’re more structural than thinking of them as “system prompts” suggests. (All LLMs ever see is tokens going in, so even the concept of a system prompt is just formatting they’ve se
50.
by anon373839 1mo ago
> Qwen 3.6 35B A3B on medium thinking mode Qwen 3.6 doesn’t have configurable reasoning effort, does it?
51.
by anon373839 1mo ago
Agree. We’re going to hear a lot of buzz about recursive self-improvement in the near future, which I’d cynically say is meant to address the naked emperor you just called out. Can labs get a boost augmenting more of their processes with au
52.
by anon373839 1mo ago
This comment seems needlessly insulting and also kind of obtuse? I don’t think the GP meant that it’s impossible to dispose of a large amount of money. But it is effectively impossible to spend down a certain level of accumulated wealth by
53.
by anon373839 1mo ago
> I’ve been in the “overweight” BMI range with low body fat before. It’s not too hard to get there Did you do that as a natural lifter? It’s hard for me to imagine most guys being able to get into the “overweight” range at < 15% body
54.
by anon373839 1mo ago
> A small model won't know the tax code of every city in the world, as it's probably impossible to fit, and it's the kind of thing that unless you already know about, it's very hard to search for What makes it hard to
55.
by anon373839 1mo ago
> You just can't compress the entire human knowledge into a 30GB file Fortunately, that isn’t necessary! What LLMs need is a level of fluency with key concepts so that they can (1) make effective use of retrieval tools and (2) under
56.
by anon373839 1mo ago
In my experience, the facts that are compressed away in small models are ones you don’t need them to memorize. They need familiarity with the essential concepts in a field, so that they will have better comprehension of material put into th
57.
by anon373839 1mo ago
Holy Streisand effect, that’s some background!
58.
by anon373839 1mo ago
I don’t think this works, for a few reasons. First, intelligence gains from scaling the models bigger is sublinear now. So they could eke out a little extra performance, but the increased cost will eventually eclipse the economic value gain
59.
by anon373839 1mo ago
Yes, RSI seems to be the new AI industry McGuffin of 2026, just as agentic capability has become table stakes and scaremongering has become a punchline.
60.
by anon373839 1mo ago
Yeah, Dax from OpenCode said that it appears to just be traffic shaping, nothing to do with the inference economics. He also said that OC have already replicated the inference cost in internal experiments.

More ›