581–590 of 682 posts
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If the brain does rely on quantum effects, it's still possible the quantum effects in use are able to be simulated efficiently on a classical computer. For example if it's a matter of signal transfer rather than quantum computation, that could be simulated rather easily.
I wonder what company will release the first "quantum LLM"
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What specific technical signals make you think we're close to a shift like that?
The researchers who published Attention Is All You Need didn’t have the benefit of the LLMs they birthed. Take a look at the prompt that solved the Cycle Double Cover conjecture, and which has been adapted to achieve breakthroughs in cybersecurity. The field is entering a feedback loop that is leading to exponential innovation. We’re at the beginning of the curve. And right now the big iron data center approach is br…
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I think it’s also worth pointing out that that there are numerous less evil options to choose from. Perhaps none of the AI companies are shining examples of high ethics, but basically all of them have ethical high ground over Meta. At least Anthropic isn’t sending private videos from pervert glasses to contract workers in Africa. It’s a low bar but it’s a bar nonetheless.
They're still using Elon's servers, though. Not like their models are any good anyways
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Based on the benchmarks, it seems that Muse Glimmer barely edges out against Qwen3.6 27B, except for tool-calling skills (MCP, etc.). I wouldn't be surprised if they released it now because they are afraid they wouldn't beat Qwen3.8 27B.
I would hope that Qwen 3.8 is better. It's been 4 months, and we've seen almost no progress in this space. As people have called out, Glimmer appears to be a trade-off rather than a clear winner. And from what I've been reading, no one is expecting Qwen 3.8's model in this space to be a clear winner, but just slightly and marginally better. That's a little concerning as DeepSeek v4 Flash proved at it larger sizes the…
For contrast, the Newcomen steam engine (widely considered the first commercially useful engine) was used for over 60 years before the next major improvements. Now, 300 years later, we’re still finding ways to significantly improve heat engines.
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FWIW it is entirely possible to square the notion that small models will still be hosted on cloud hardware with the idea that the data centre buildout will end in tears. Many analysts (and Microsoft) think even now that if everything committed gets built there will be considerable oversupply and there is not the revenue to pay for it. If small models do continue to improve in unusual ways (I think there are limits) t…
So far everyone seems to be consistently GPU-poor, despite the huge buildout, and usage keeps going up drastically. I don't know what would make usage drop. Every time they've made smarter models we've wanted the smarter ones, and local models runnable on typical hardware are still very far behind in speed and intelligence (as neat as they are)
That is seemingly not the case. The buildout is actually slow; almost nothing of these giant projects has been completed. Nobody will say how much of anything they have actually finished. And Nvidia have made huge, huge buy-and-hold deals for GPUs that do not have data centres to go into.
Everyone is GPU poor because stuff hasn't been finished but large numbers of GPUs are spoken for, but they are GPU poor on therefore much less demand than is being built for.
Look at how tiny SpaceX's deal is with Anthropic, for example. This meaningfully turned around Anthropic's prospects — allowing them to radically lift rate limits beyond what many users needed -- but it was for just 300 megawatts. Tiny compared to the 31 gigawatts allegedly under construction by the end of last year.
So the picture is partly illusory. GPU prices and RAM prices have been pushed up by the AI firms booking them for data centres they haven't even started building yet, as well as the ones that they've only completed a tenth or an eighth of.
There will be significant oversupply. And if open weights models keep getting good and staying fuel-efficient, that picture gets worse.
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Qwen3.6 27B is the go-to medium sized model for coding, so beating it is not a small achievement
There is a finetune Qwen3.6-27B-Fable-Fus-711-UnHeretic-NM-DAU-NEO-MAX-NEO which seems to be as good at coding as vanilla Qwen, but way, way better at creative writing than Qwen and even better than Gemma 4 26 and 31b.
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While composing a reply to a comment throwing tons of shade on American AI, I took some time to check out the commenter’s HN profile. Their comment history was about 50% such comments. Their submission history started with an article about how Russia was unfairly blamed for some hacking campaign. It’s entirely possible that this is not a foreign influence campaign. Perhaps there’s a group here that is simply anti-Ame…
Would be nice if there were a hn feature, userscript, or plugin to just filter comments from new accounts. Bonus if there was some sentiment analysis or llm-based analysis to filter out unsubstantiated inflammatory comments too.
https://xcancel.com/finkd/status/2086755195535413696 "... Soon we'll also release the weights for Muse Spark 1.2, our latest foundation model..." This is bigger news - good for self hosting enthusiasts and a strategically sound move for Meta. Any push towards 'anti Chinese' models will directly benefit Meta as the competition on the frontier open-weights American models is almost non-existent. Meta will have no probl…
Poolside Laguna was quite good too (if you look beyond some of the teething issues). Had Deepseek V4 Flash 0731 not launched, their latest Laguna release was really intelligent at non-coding tasks and it would have been my go-to model for my local workloads.
Remember when we needed 200 servers for an enterprise website because Apache used one process or thread per connection - and Nginx collapsed that into a single box overnight? That moment for LLMs is near. It’s going to move us from the big iron era of AI to small portable brains. Nature has already proved it’s possible with 20 watts and very little heat generation. And I think the data center buildout will end in car…
I don’t remember that and I was there! The idea that the performance delta between Apache and nginx for any normal workload is anything like 20,000% is absurd.
Remember when we needed 200 servers for an enterprise website because Apache used one process or thread per connection - and Nginx collapsed that into a single box overnight? That moment for LLMs is near. It’s going to move us from the big iron era of AI to small portable brains. Nature has already proved it’s possible with 20 watts and very little heat generation. And I think the data center buildout will end in car…
Side note! Nginx was by no means the first web server to use a non-forking mechanism, nor the first open source web server to do so. Certainly Zeus (which was closed source) was earlier and very useful in this sort of application, and so was thttpd (open source, still exists as Merecat). I used thttpd quite a bit for single box applications and at one of my employers, nginx replaced a mixed strategy with Zeus, Apache…
Fun fact: Igor Sysoev originally wrote mod_accel [1], an acceleration and reverse-proxy caching module for Apache before he made nginx.
I remember using that module in the mid-2000s as a load balancer (and to offload SSL encryption/decryption as it was a CPU-expensive operation).