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Intellect-2 Release: The First 32B Model Trained Through Globally Distributed RL
- esafak 1y agoHow are they ensuring robustness against adversarial responses?
- nsingh2 1y agoFrom the article, seems like TOPLOC: > based on top of novel components such as TOPLOC, which verifies rollouts from untrusted inference workers https://github.com/PrimeIntellect-ai/toploc https://github.com/PrimeIntellect-ai/toploc
- xmasotto 1y agoCan an expert explain how this protects against adversarial actors? At a glance it looks like something akin to a computing a checksum that's locality sensitive, so it's robust to floating point errors, etc. What's to stop someone from sending bad data + a matching bad checksum?
- yorwba 1y agoThe validation procedure is described on page 8 of the TOPLOC paper: https://arxiv.org/abs/2501.16007 https://arxiv.org/abs/2501.16007 The checksum is validated by redoing the computation, but making use of the fact that you already have the entire response to enable greater parallelism than when generating it one token at a time.
- DoctorOetker 1y agoTOPLOC attempts to detect model substitution, i.e. responses being generated by a different model than requested, it comes with certain caveats, as far as I can tell the TOPLOC paper considers verifiable learning / training as out of scope.
- ndgold 1y agoPretty badass
- quantumwoke 1y agoWonder what the privacy story is like. Enterprises don't usually like broadcasting their private data across a freely accessible network.
- bjt12345 1y agoA strong use case here for quantum-safe encryption.
- Zambyte 1y agoWhy? Quantum safe cryptography is mostly interesting right now in the context of defending against store now, decrypt later attacks. That doesn't seem helpful here, because they'll still need to decrypoit for training. Did you mean homomorphic encryption?
- refulgentis 1y agoI guess I'm bearish? It's not that they trained a new model, but they took an existing model and RL'd it a bit? The scores are very close to QwQ-32B, and at the end: "Overall, as QwQ-32B was already extensively trained with RL, it was difficult to obtain huge amounts of generalized improvement on benchmarks beyond our improvements on the training dataset. To see stronger improvements, it is likely that better base models such as the now available Qwen3, or higher quality datasets and RL environments are needed."
- fabmilo 1y agoThe interesting delta here is that this proves that we can distribute the training and get a functioning model. The scaling factor is way bigger than datacenters
- refulgentis 1y agoThe RL, not the training. No?
- itchyjunk 1y agoRL is still training. Just like pretraining is still training. SFT is also training. This is how I look at it. Models weights are being updated in all cases.
- refulgentis 1y agoSimplifying it down to "adjusting any weights is training, ipso facto this is meaningful" obscures more light than it sheds (as they noted, RL doesn't get you very far, at all)
- comex 1y agoBut does that mean much when the training that produced the original model was not distributed?
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- mountainriver 1y agoAwesome work this team is doing. Globally distributed MoE could have real legs
- jumploops 1y agoCongrats to the team on the launch! Personal story time: I met a couple of their engineers at an event a few months back. They mentioned they were building a distributed training system for LLMs. I asked them how they were building it and they mentioned Python. I said something along the lines of “not to be the typical internet commenter guy, but why aren’t you using something like Rust for the distributed system parts?” They mumbled something about Python as the base for all current LLMs, and then kinda just walked away… From their article: > “Rust-based orchestrator and discovery service coordinate permissionless workers” Glad to see that I wasn’t entirely off-base :)
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- Havoc 1y agoGiven the latencies at play python did probably make more sense though
- bwfan123 1y agoThe technical underpinning has nothing to do with the language. It is a different way of optimizing parameters called diloco. I agree though that python is an abomination for systems services componentry when there are languages like rust.
- throwanem 1y agoThere's a name and a logo. "Hubris" feels slightly beggared. https://en.m.wikipedia.org/wiki/The_Metamorphosis_of_Prime_Intellect https://en.m.wikipedia.org/wiki/The_Metamorphosis_of_Prime_I...
- Extropy_ 1y agoThis looks like a startup company. Why shouldn't it have a name and logo?
- Philpax 1y agoTheir point is that the name and logo are clearly drawing from the Metamorphosis of Prime Intellect, with all the potential baggage that comes with it. It's an interesting choice.
- throwanem 1y agoThe novel was the first popular codifier of the concepts of strongly superhuman ASI and hard-takeoff singularity, literally the work that introduced these ideas to the then quasi-New Atheist hangers-on among the kuro5hin crowd who became the initial core of what would develop into the follower base for singularitarianism. It was quite well written for that purpose, with enough sex and action to paper over the slow parts, and a real grasp of what it feels like when time contracts and dilates at once in those dolly-zoom moments where the universe is different forever and nothing outwardly changes. Combined with the seductive appeal and literally universal scope of the ideas that power its plot, it is no wonder the novel should have left so strong an impression on a few. Someone intentionally invoking that history is interesting indeed. Someone doing it by accident might be more so. But I already gave that choice the name I judge it deserves.
- varelse 1y ago[dead]
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- schneehertz 1y agoI used to have an idea related to science fiction novels that artificial intelligence could aggregate computing power through the network to perform ultra-large-scale calculations, thereby achieving strong artificial intelligence. Reality will also develop in this way, which is very interesting
- abtinf 1y agoDoes this have anything to do with The Metamorphosis Of Prime Intellect, or did they just abuse the name and the cover art?
- arthurcolle 1y agoPrime Intellect is a grabby AI :)
- danielhanchen 1y agoI made some GGUFs at https://huggingface.co/unsloth/INTELLECT-2-GGUF https://huggingface.co/unsloth/INTELLECT-2-GGUF ./llama.cpp/llama-cli -hf unsloth/INTELLECT-2-GGUF:Q4_K_XL -ngl 99 Also it's best to read https://docs.unsloth.ai/basics/tutorial-how-to-run-qwq-32b-effectively https://docs.unsloth.ai/basics/tutorial-how-to-run-qwq-32b-e... on sampling issues for QwQ based models. Or TLDR, use the below settings: ./llama.cpp/llama-cli -hf unsloth/INTELLECT-2-GGUF:Q4_K_XL -ngl 99 --temp 0.6 --repeat-penalty 1.1 --dry-multiplier 0.5 --min-p 0.00 --top-k 40 --top-p 0.95 --samplers "top_k;top_p;min_p;temperature;dry;typ_p;xtc"
- 3abiton 1y agoThis is rather exciting! I see the future of Co-op models made by a community of experts on a specific field that would still allow them to be competitive with "AI monopolies". Maybe not all hope is lost!
- iTokio 1y agoIt’s interesting that it does something useful (training a LLM) without trust and in a decentralized way. Maybe this could be used as proof of work? To stop wasting computing resources in crypto currencies and get something useful as a byproduct.
- proof_by_vibes 1y agoThere could be merit to this. Proofs are generally computationally hard, so it's possible that a currency could be created by quantifying verification.
- littlestymaar 1y ago> To stop wasting computing resources in crypto currencies and get something useful as a byproduct. Bitcoin is the only major cryptocurrency that still use proof of work today (others are either using “proof of stakes” or are “Layer 2” chains), and due to its (relative lack of) governance structure, it's very unlikely to ever change.
- fastball 1y agoThe emphasis is indeed on "without trust" – as far as I can tell this project is unable to verify whether the decentralized training nodes are contributing productively. Without the ability to validate that training compute is heading in the globally desired direction, it is unlikely you could use it as the foundation of a (sound) cryptocurrency.
- mentalgear 1y agoThe reward model could be used as a validation/reward for the client. Give the same nodes the same inferences to make, and the one with the highest reward (those could be short, or even partially calculated long-term) will also get the "currency" reward.
- Philpax 1y agoThat sounds like it'll lead to human-driven reward hacking [0]? [0]: https://en.wikipedia.org/wiki/Reward_hacking https://en.wikipedia.org/wiki/Reward_hacking
- Thomashuet 1y agoSummary: We've use the most complexest, buzzwordiest training infrastructure to increase the performance of our base model by a whopping 0.5% (±1%).
- Weryj 1y agoBut this isn’t about the performance, the infrastructure is the product here.
- lonelyasacloud 1y agoIndeed, most reliable way to make money in a gold rush is to sell shovels.
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- Mougatine 1y agovery cool work!
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- bwfan123 1y agoThe most interesting thing I see is the productization of the diloco work done here [1]. If someone can make this scale, then we can say goodbye to expensive backend networking and mainframe-like AI training machinery. [1] https://arxiv.org/abs/2311.08105 https://arxiv.org/abs/2311.08105
- ikeashark 1y agoI wonder why they randomly noted a torch-compile vs non torch-compile figure where torch-compile degraded model performance. What made it degrade? It seems to only appear in one figure and nowhere else.
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