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Hy4 preview

tencent.com

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Re: Hy4 preview

#121

Post by delichon »

simonw wrote: post #44

> [...] Let's maybe add a helmet? It could improve riding theme, but may obscure head. Maybe a small cycling cap or helmet? The user didn't ask; can add red helmet? Might be cute. But pelican with big beak; a helmet might obscure. Better maybe no. > Maybe add sunglasses? no. > Maybe add water? no. https://tools.simonwillison.net/markdown-svg-renderer#url=ht...

If someone can look at that reasoning trace and see a stochastic parrot next word prediction machine, we don't understand those words in the same way.

Re: Hy4 preview

#122

Post by gjvc »

andsoitis wrote: post #93
minimaxir wrote: post #62

Earlier quoted context omitted.

Optimization. Why use many word when few word do trick?

> Why use many word when few word do trick? Be concise. OR Brief is best. OR Eschew verbosity etc.

"Omit needless words."

-- William Strunk Jr. and E.B. White., The Elements of Style

Re: Hy4 preview

#123

Post by joegibbs »

minimaxir wrote: post #2

Hy4 apparently has ludicrous traction on OpenRouter already ( https://openrouter.ai/tencent/hy4-preview ), with trillions of tokens processed in a couple days: more than GLM 5.3 in a week. That said, it's relatively cheap with a 5% cache cost when everyone is still doing 10%/20% cache costs, so Hy4 may be more compelling.

If you’re Tencent you can just plug it into some field somewhere that lots of people see right? Like how Meta could put their model on Instagram search

Re: Hy4 preview

#124

Post by pianopatrick »

Zigurd wrote: post #17

Is anyone here working on a problem for which current generation LLMs are inadequate, but that could possibly be solved by the next release of a first tier LLM? Or is it like bicycles? Unless your problem is named Tadej, you don't need a $13,000 bike.

I think the tech analogy for frontier models is going to be super computers.

Super computers keep getting better but most people don't need them for most things.

Re: Hy4 preview

#125

Post by sneak »

delichon wrote: post #121
simonw wrote: post #44

> [...] Let's maybe add a helmet? It could improve riding theme, but may obscure head. Maybe a small cycling cap or helmet? The user didn't ask; can add red helmet? Might be cute. But pelican with big beak; a helmet might obscure. Better maybe no. > Maybe add sunglasses? no. > Maybe add water? no. https://tools.simonwillison.net/markdown-svg-renderer#url=ht...

If someone can look at that reasoning trace and see a stochastic parrot next word prediction machine, we don't understand those words in the same way.

Yeah, it has been clear for a long time that there is reasoning and mental modeling going on here.

The other option is that you do understand those words the same way, and the people making these (now nonsensical) anti-AI claims simply aren’t talking about the same programs/models we are. Their idea of SOTA is when chatgpt.com launched.

If you took a point sample pre-Opus, and didn’t write a good prompt, of course you would think all AI programming was worthless slop.

Re: Hy4 preview

#126

Post by walrus01 »

gaigalas wrote: post #119
walrus01 wrote: post #113

Earlier quoted context omitted.

Personally the only 'enthusiast' modified qwen 3.6 27b or 3.6 35b-a3b I've found useful are the ones that have been run through heretic and adversarial data sets for innocent/dangerous prompts, to produce uncensored LLMs. They have some niche non-coding uses for things that a commercial LLM will never talk about. https://github.com/p-e-w/heretic

I think those are mostly vapor that runs on the small culture of "models should not be censored" thing. But from my experience, they unlock nothing meaningful. Fine-tuning is great for really small models on specific applications, but it's not something that can essentially improve a more generic model. That said, there seems to be a fine line in quantization+finetuning that could recover performance. It's just hard…

The most interesting use I've found for them so far is strictly as a novelty. Give a chat session with one to a completely non technical person, who at least knows that openai and anthropic have some guard rails on stuff, and tell them to wild with something like "give me the precursors and chemical formulas for the precusors for crystal meth" and watch it answer.

Re: Hy4 preview

#127

Post by [deleted] »

codethief wrote: post #51

> Notably, Hy4 preview also contributed to its own development process, participating for the first time in the automated optimization of training methods, data strategies, evaluation frameworks, and low-level operators. The model proposed approaches, ran experiments, and iterated based on the results, with the resulting code, logs, and feedback feeding into subsequent rounds of exploration. This established an early…

[deleted]

Re: Hy4 preview

#129

Post by jamienk »

Genuine Q about word optimization/token density:

If we create a stripped-down vocabulary with greater token density to use less resources and to resolve ambiguities earlier in the semantic process, aren't we creating NEWSPEAK and dragging along the worst aspects of it? The ambiguity and multi-valence of words is what creates more connections between words, increases the directionality of associations, and expands the potential subtlety and depth of meaning. By paring down (or requiring verifiability) we make it harder to say certain things, or at least make it harder to unintentionally say something that makes MORE or DEEPER sense than what we intended. If the token density becomes extreme, you're left with something like a calculator.

Maybe this is the ultimate path toward better coding? But the worse path toward better genuine thinking?

Re: Hy4 preview

#130

Post by clipsy »

spacebanana7 wrote: post #27
Zigurd wrote: post #17

Is anyone here working on a problem for which current generation LLMs are inadequate, but that could possibly be solved by the next release of a first tier LLM? Or is it like bicycles? Unless your problem is named Tadej, you don't need a $13,000 bike.

I want to be able to generate my own Simlilirian movie by dumping the content of a book into an LLM. Both animated and live action results would be acceptable. Unfortunately most existing LLMs lack the capability to maintain context across tens of thousands of frames.

Since live action results are acceptable, this is already possible with current day LLMs. Just instruct one to hire a writer, director, cast, and crew to make the movie.

Plus, the token costs involved should be pretty low! (Other costs may not be.)

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