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> Second, clean data. MAI-Thinking-1 was trained on clean and appropriately licensed data, with AI-generated content excluded from pre-training. This matters fo
by keeda 4mo ago
> Second, clean data. MAI-Thinking-1 was trained on clean and appropriately licensed data, with AI-generated content excluded from pre-training. This matters for quality, provenance, and control. If we cannot account for what shaped a model, we cannot fully understand its behavior or credibly improve it.
Shots fired?
It would be interesting to see how far "clean data" can go on the scaling laws.
- onlyrealcuzzo 4mo agoI'm interested how much "Clean Data" is synthetic data from "unclean" models...
- xavriley 4mo ago“ We trained it from the ground up on enterprise grade, clean and commercially licensed data, without distillation from third-party models.”
- azinman2 4mo agoaka all of GitHub OSS
- ChicagoDave 4mo agoYeah this is exactly what I was thinking.
- rurban 4mo agoNot OSS only, likely also the enterprise private repos, with a lot of business secrets.
- ertgbnm 4mo ago> with AI-generated content excluded from pre-training. > without distillation from third-party models sounds like zero unless they are lying.
- deleted 4mo ago[deleted]
- zamalek 4mo ago> with AI-generated content excluded from pre-training. Though this is largely impossible these days, unless they pre-trained on pre-AI era data.
- stymaar 4mo agoThat could be. Just use pre-training for language understanding and let the post-training on synthetic data do the heavy lifting.
- saghm 4mo ago"how many of those shapes are rectangles?" "sounds like zero unless they are squares" Adding "unless" to a statement makes it vacuous if the latter clause is weaker than the first clause. I find it hard to believe that a company willing to violate licenses would have scruples about lying about it.
- chongli 4mo agoAdding "unless" to a statement makes it vacuous if the latter clause is weaker than the first clause I think that's the point. "How do I say they're lying without outright saying they're lying?" It's a common rhetorical trick.
- Leynos 4mo agoOr the speaker is just not in the mood to argue with someone whose response will be, "you trust anything Microsoft say?"
- rocqua 4mo agoNot vacuous, but tautological. Which is different, because tautologies can actually be quite directly informative. Whereas vacuous truths tend to be oblique. Also, “Microsoft is lying” is not a logically stronger statement, because they might be lying about something other than whether they distilled or trained on AI output.
- bicx 4mo agoSo, laundered data?
- vdfs 4mo agoI doubt any lab would say otherwise, they all _claim_ to use licensed data
- keeda 4mo agoMaybe, but Microsoft, through their partnership with OpenAI, is already involved in major copyright lawsuits. That is probably a driving force for this move, actually... I doubt they would want to tempt fate while those lawsuits are on-going.
- deleted 4mo ago[deleted]
- foresterre 4mo agoI would really like to see what "appropriately licensed data" means. Cannot imagine they didn't copy all open repo's on GitHub, and can't imagine they asked for permission, or are reproducing license texts from these repo's now. It sounds hand wavy. P.S. A fairly basic website otherwise, but it unfortunately seems to be hacking scroll for no good reason.
- stingraycharles 4mo agoI assume they took the actual repos’ licenses info account. I don’t understand why they should ask for permission when the license would already allow for it.
- rocqua 4mo agoWhich licenses allow usage for training? MIT, BSD, etc likely do. But I would expect it gets weird for all the various copyleft licences.
- foresterre 4mo agoAlmost all licenses have requirements to redistribute copies of the work, or derivatives thereof. Even permissive licenses do. It's very little to ask when open source dev's provided thousands of hours of free work. For example, the Apache 2.0 license requires in just 4.c: You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; Just because they're tokenized and transformed into a probabilistic mapping, doesn't suddenly mean that they weren't copied. I find it morally unethical that they (likely) just ingest IP of all open source repo's without asking, but also importantly without any attribution. Let me also note that I'm not against LLM's in general. But I do think training on open source must be opt-in, and I look forward to a world with actually ethical, and traceable (i.e. on what they were trained on, like a bill of materials (BOM)), models.
- supermdguy 4mo agoIt's interesting because their last model series (Phi) was based around the thesis that high-quality synthetic data is better than a large pre-training corpus.
- inquirerGeneral 4mo ago[dead]
- swalsh 4mo agoI'd assume it's not up to par with Qwen-3.5 then, which has been distilling Claude, and the quality of the model is probably a direct result of that.
- andai 4mo agoInteresting. Wasn't their previous attempt (Phi) trained mostly on synthetic data?
- vanuatu 4mo agoall the labs "clean" their pretraining data, and you can have your pretraining data to be minimally ai generated but also spam synthetic post-training data