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Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

tongyi-agent.github.io

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Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#61

Post by hamandcheese »

whiplash451 wrote: post #58
Traubenfuchs wrote: post #19

It still feels to me like OpenAI has zero moat. There are like 5 paid competitors + open source models. I switch between gemini and ChatGpt whenever I feel one fails to fully grasp what I want, I do coding in claude. How are they supposed to become the 1 trillion dollar company they want to be, with strong competition and open source disruptions every few months?

Isn’t the moat in the product/UI/UX? I use Claude daily and love the “scratch notebook” feel of it. The barebone model does not get you any of this.

I agree that the scaffolding around the model contributes greatly to the experience. But it doesn't take billions of dollars in GPUs to do that part.

Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#62

Post by ainch »

onlyrealcuzzo wrote: post #47
zurfer wrote: post #8

It makes me wonder if we'll see an explosion of purpose trained LLMs because we hit diminishing returns on invest with pre training or if it takes a couple of months to fold these advantages back into the frontier models. Given the size of frontier models I would assume that they can incorporate many specializations and the most lasting thing here is the training environment. But there is probably already some tradeo…

Isn't the whole point of the MOE architecture exactly this? That you can individually train and improve smaller segments as necessary

Generally you train each expert simultaneously. The benefit of MoEs is that you get cheap inference because you only use the active expert parameters, which constitute a small fraction of the total parameter count. For example Deepseek R1 (which is especially sparse) only uses 1/18th of the total parameters per-query.

Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#63

Post by ainch »

tbruckner wrote: post #34

Has anyone found these deep research tools useful? In my experience, they generate really bland reports don't go much further than summarization of what a search engine would return.

The reports are definitely bland, but I find them very helpful for discovering sources. For example, if I'm trying to ask an academic question like "has X been done before," sending something to scour the internet and find me examples to dig into is really helpful - especially since LLMs have some base knowledge which can help with finding the right search terms. It's not doing all the thinking, but those kind of broad overviews are quite helpful, especially since they can just run in the background.

Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#64

Post by anon373839 »

jlokier wrote: post #28
aliljet wrote: post #5

Sunday morning, and I find myself wondering how the engineering tinkerer is supposed to best self-host these models? I'd love to load this up on the old 2080ti with 128gb of vram and play, even slowly. I'm curious what the current recommendation on that path looks like. Constraints are the fun part here. I know this isn't the 8x Blackwell Lamborghini, that's the point. :)

I use a Macbook Pro with 128GB RAM "unified memory" that's available to both CPU and GPU. It's slower than a rented Nvidia GPU, but usable for all the models I've tried (even gpt-oss-120b), and works well in a coffee shop on battery and with no internet connection. I use Ollama to run the models, so can't run the latest until they are ported to the Ollama library. But I don't have much time for tinkering anyway, so I…

I’d strongly advise ditching Ollama for LM Studio, and using MLX versions of the models. They run quite a bit faster on Apple Silicon. Also, LM Studio is much more polished and feature rich than Ollama.

Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#65

Post by dlisboa »

soared wrote: post #11
rokob wrote: post #9

This whole series of work is quite cool. The use of `word-break: break-word;` makes this really hard to read though.

I actually can’t read it for some reason? My brain just can’t connect the words

That’s why typography matters. You can’t read it because a very basic convention has been broken here and that throws everything off.

Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#66

Post by viraptor »

idiotsecant wrote: post #59
onlyrealcuzzo wrote: post #47

Earlier quoted context omitted.

Isn't the whole point of the MOE architecture exactly this? That you can individually train and improve smaller segments as necessary

I think it's the exact opposite - you don't specifically train each 'expert' to be a SME at something. Each of the experts is a generalist but becomes better at portions of tasks in a distributed way. There is no 'best baker', but things evolve toward 'best applier of flour', 'best kneader', etc. I think explicitly domain-trained experts are pretty uncommon in modern schemes.

That's not entirely correct. Most of moe right now are fully balanced, but there is an idea of a domain expert moe where the training benefits fewer switches. https://arxiv.org/abs/2410.07490

Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#68

Post by andy99 »

tbruckner wrote: post #34

Has anyone found these deep research tools useful? In my experience, they generate really bland reports don't go much further than summarization of what a search engine would return.

My experience is the same as yours. It feels to me (similar to most LLM writing) like they write for someone who’s not going to read it or use it but is going to glance at it and judge the quality that way and assume it’s good.

Not to different from a lot of consulting reports, in fact, and pretty much of no value if if you’re actually trying to learn something.

Edit to add: even the name “deep research” to me feels like something defined to appeal to people who have never actually done or consumed research, sort of like the whole “phd level” thing.

Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

#70

Post by MaxPock »

idiotsecant wrote: post #60
ninetyninenine wrote: post #50

Is China dominating the US in terms of AI? Given that they currently have a model that beats the best models at all formal quantitative benchmarks? What is the state of AI in China? My personal feeling is that it doesn't dominate the zeitgeist in China as it does in the US and despite this because of the massive amount of intellectual capital they have just a small portion of their software engineering talent working…

I think the lesson of the Chinese catchup in AI is that there is a massive disadvantage in being first, in this domain. You can do all the hard work and your competitors can distill that work out of your model for pennies on the dollar. Why should anyone want to do the work?

This sounds like copium . If it was just about distillation,we'd be seeing many awesome models from Europe ,Japan and even India.
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