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Open source AI: Red Hat's point-of-view
- thrqka 2y ago> We believe that these concepts can have the same impact on artificial intelligence Where the concept is the exploitation of thousands of volunteers while repackaging their work. (I know that RedHat sponsors some people, sometimes to the detriment of projects, but a lot of it is not sponsored, especially when RedHat established itself.)
- dralley 2y agoSo, what, is HN against open source now?
- 7qW24A 2y agoMore accurate to say that VC and the “startup ideology” has always been at the core of HN - it just so happened that aligned with OSS ideology during the ZIRP era.
- carlwgeorge 2y agoRed Hat pays more people to work on open source than any other company I'm aware of. I am one of these people. I challenge you to find a single open source project included in a Red Hat product that doesn't contain contributions from Red Hat employees. Maybe a few exist, but the vast majority include Red Hat contributions, because we contribute all over the open source ecosystem.
- jmclnx 2y agoNo real information, just a marketing spiel.
- ysofunny 2y agoi mean... it's IBM so what did we really expect?
- globalnode 2y agoI was thinking of trying Fedora (currently using Debian) and this comment made me look up who owns red-hat. ibm now owns red-hat, and apparently vanguard owns a huge chunk of ibm. I wonder how much influence any of the sponsors have over what goes into the os and what direction it takes.
- rat87 2y agoVanguard "owns" a huge chunk of everything. Vanguard runs index funds, most peoples retirements are vanguard buying small shares of an index fund representing all the big companies on the stock exchange
- fny 2y agoVanguard is everyone’s retirement account. Everytime someone buys their S&P 500 ETF, they go buy stocks.
- TZubiri 2y agoAlso they simultaneously hold the ownership rights as well as equivalent owenrship liabilities, so they own shit squat in net terms (excpet maybe their management fees).
- mattkrause 2y agoIt’s even weirder than that! Vanguard has an odd corporate structure where it’s owned by the funds that it manages, so it’s effectively a co-op owned by its customers.
- _yb2s 2y agoI don’t understand why customer owned co-ops aren’t ubiquitous. Vanguard is amazing- low fees, and great services- they beat all of the competition. I had to call their support line today and it was the most professional customer service I’ve ever experienced.
- echelon 2y ago> TL;DR - Red Hat views the minimum criteria for open source AI as open source-licensed model weights combined with open source software components. That's not open source! I'm going to call this "Wizard of Ozzing". You give away the spectacle of magic tricks, but none of the science and machinery to do it yourself. You're still hiding it all behind fake virtue signalling. Open source in AI is open weights, open training scripts, open inference scripts, open training datasets, and associated helper utilities. Without the science lab, you cannot replicate the science. Weights in a vacuum are not open. It's a trick.
- tbrownaw 2y agoYou have the preferred form for making modifications, and the relevant permissions to now get in trouble for it. If you actually go look at the open source or few software definitions, that's what they're about - being able to make modifications. Just like an open source software project doesn't need a public record of the rationale for all architectural decisions in order to qualify.
- nine_k 2y agoOpen source means that you can build from said source. You can e.g. give away a closed-source game engine with an editor, where you can modify the prebuilt levels, and create your own, to your heart's content. But you can't build it from scratch in a controlled environment, and can't audit it. You also can't do modifications where the level editor interface is not sufficient, e.g. in the renderer. That's not open source, that's freeware. For ML models, the training set is a crucial part of their source.
- superice 2y agoOpen source means being able to verify how the sausage is made. Getting a premade sausage and saying “oh you can still eat it and spice it up however you like” isn’t that. I’m happy open weights exist, but it is not truly open source.
- echelon 2y agoDefine these terms: - Pretrain - Fine tune - Catastrophic forgetting - Learning rate - Adapter layer If you understand these terms, then you understand why "open weights" are not the same as "open source". "Open weights" are obfuscated and minified freeware.
- TZubiri 2y agoOr you don't understand the matter being discussed. The classical definition of open source (cited in this release as Stallman's GPL definition of the preferred way in which to modify code) kind of breaks for ML programs. This is a good update on the definition of open source from a quite reputable and influential FOSS source. Your presumption that this article isn't sufficiently pure because in addition to being a company that does Free Software, it needs to do so without doing anything that resembles an ad or in any way ensures profitability is pedantic. If we had it your way the only open source software we would have would be mom's basement projects with shoestring budgets.
- nickandbro 2y agoCongrats NeuralMagic team on being acquired! I don't know if you know this, but I worked with you on discord a few times. Your team's always willing to go above and beyond with pushing out popular models in specific quant formats compatible with vLLM. And one of the few huggingface orgs that my boss can actually trust. Well deserved!
- pabs3 2y agoI prefer the ML policy of the Debian Deep Learning Team. https://salsa.debian.org/deeplearning-team/ml-policy/ https://salsa.debian.org/deeplearning-team/ml-policy/
- sciencesama 2y agoLook whos talking !! The whole fiasco with fedora and now they come to talk about opensource !!
- nine_k 2y agoTo me, the ML situation looks roughly like this. (1) Model weights are something like a bytecode blob. You can run it in a conformant interpreter, and be able to do inference. (2) Things like llama.cpp are the "bytecode interpreter" part, something that can load the weights and run inference. (3) The training setup is like a custom "compiler" which turns training data to the "bytecode" of the model weights. (4) The actual training data is like the "source code" for the model, the input of the training "compiler". Currently (2) is well-served by a number of open-source offerings. (1) is what is usually released when a new model is released. (1) + (2) give the ability to run inference independently. AFAICT, Red Hat suggests that an "open-source ML model" must include (1), (2), and (3), so that the way the model has been trained is also open and reusable. I would say that it's great for scientific / applied progress, but I don't think it's "open source" proper. You get a binary blob and a compiler that can produce it and patch it, but you can't reproduce it the way the authors did. Releasing the training set, the (4), to my mind, would be crucial for the model to be actually "open source" in the way an open-source C program is. I understand that the training set is massive, may contain a lot of data that can't be easily released publicly but that were licensed for the training purposes, and that training from scratch may cost millions, so releasing the (4) is very often infeasible. I still think than (1) + (2) + (3) should not be called "open-source", because the source is not open. We need a different term, like "open structure" or something. It's definitely more open than something that's only available via an API, or as just weights, but not completely open.
- pavelstoev 2y agoIt is really just “open use” with detailed defined by the license type (MIT, etc)
- nine_k 2y agoIt's more than just use (inference), it does open some otherwise secret sauce of the training. It looks like there's no existing word / notion to exactly pinpoint this level of openness.
- smohare 2y ago[dead]
- lutusp 2y ago> More than three decades ago, Red Hat saw the potential of how open source development and licenses can create better software to fuel IT innovation. Thirty-million lines of code later, Linux not only developed to become the most successful open source software but the most successful software to date. This seems to conflate Red Hat and Linux, as well as try to equate Red Hat with open-source. Red Hat is Linux, but Linux is not Red Hat, especially now that Red Hat has decided to restrict access to the RHEL source (https://www.itworldcanada.com/article/red-hat-decision-turns-world-of-open-source-linux-upside-down/543157 https://www.itworldcanada.com/article/red-hat-decision-turns...). And a pet grammatical peeve of mine: > ... in some respects they serve a similar function to code. I see this everywhere now -- IMHO it should be "... serve a function similar to code." Doesn't the original grate on your ear? Also this is a Turing-test bot detector -- bots don't use this weird grammatical construction, only humans do.
- mogwire 2y agoRestrict access to paying customers? Restrict access to companies violating an EULA to not redistribute packages? That fact that people continue to spread this trope is amazing. I pay for RHEL and I have a developer subscription for personal usage and the SRPMs are right there on their download portal. Just because CIQ err Rocky has to take extra steps and violate Red Hat’s EULA doesn’t mean they restricted access.
- davydm 2y agoRed Hat opining about what is and isn't open is absolutely hilarious. Sorry, my dudes, you launched that ship in the wrong direction ages ago.
- worthless-trash 2y agoWhat does redhat ship that isnt open source under the licenses my dude ?
- deleted 2y ago[deleted]
- lrvick 2y agoI largely agree with these points, however it is an awkward position coming from Red Hat which is the best funded Linux distribution there is, and -still- not part of the reproducible builds project or investing in full source bootstrapping which means no one can exactly reproduce their published artifacts from source or prove they were not tampered with. (Same with Fedora) Glass houses.
- dralley 2y ago> (Same with Fedora) ?? https://docs.fedoraproject.org/en-US/reproducible-builds/ https://docs.fedoraproject.org/en-US/reproducible-builds/ https://pagure.io/fedora-reproducible-builds/project/issues https://pagure.io/fedora-reproducible-builds/project/issues https://fedoraproject.org/wiki/Releases/41/ChangeSet#Reproducible_Package_Builds https://fedoraproject.org/wiki/Releases/41/ChangeSet#Reprodu...
- lrvick 2y agoFrom that first link "In the Fedora ecosystem, we cannot achieve reproducibility by the reproducible-builds.org definition" Good to see they are slowly closing some blockers every year or so, but fundamentally today they do builds and signing centrally. There is no way to readily get the same hash of a central fedora supplied rpm locally. Supply chain integrity is simply not a priority. They just trust the central build farm, or the compilers it uses, or everyone with access to it will never be compromised.
- dralley 2y agoThis is a touch dramatic. The hash of the payload and the hash of the RPM header are still reproducible and can be verified. It's just that the existence of internal signatures makes it impossible to do a simple checksum of the file.
- lrvick 2y agoAnd thus RPM was not designed with easy user reproduction and signing by multiple independent parties for high accountability in mind. Most other package managers do not have this problem. This is a flaw that should be corrected. Also, it takes a ton of work and testing and bug fixes and patches to get software reproducible. Assume most packages are not reproducible until proven otherwise. Arch, debian, nix, guix, all do that work and publish the proof, for several years, with far less resources than redhat or fedora. Stagex even has 100% (shameless plug) Easy user hash for hash reproducibility with published reproduction testing proofs is the standard baseline for years now, and even that is nowhere near good enough. Multiple independently signed reproduction proofs with full source bootstrapping is IMO a bare minimum for any distro that expects other people to be able to trust it for more than hobby use cases. Supply chain attacks are becoming very common, and no one should have to trust a single engineer somewhere with a god signing key for a major distro. Also just to spot check a popular package in Fedora, rust, I just confirmed it still downloads a non-reproducible binary rust compiler to build its own rust package, so it is certainly not reproducible from source even putting aside the rpm signing format problems. Fedora blindly trusts whoever builds the binaries on the rust team. I can only assume RHEL does the same. https://src.fedoraproject.org/rpms/rust/blob/8e04e725bbf4eb9213dde7af6750b8fed9fdaa01/f/rust.spec#_208 https://src.fedoraproject.org/rpms/rust/blob/8e04e725bbf4eb9...
- blackeyeblitzar 2y agoDisappointing that red hat is basically validating open weights as open source, and excusing it by saying this: > The majority of improvements and enhancements to AI models now taking place in the community do not involve access to or manipulation of the original training data. Rather, they are the result of modifications to model weights or a process of fine tuning which can also serve to adjust model performance. Well yes, because they have no access to anything more. With training source code and data they might do something different. If you don’t have all the things used to produce the final result, it’s not open source.
- bberenberg 2y agoDo you believe that open source can exist on top of closed hardware? I ask because you can't produce the final result without having someone give you the firmware blob. To me, this seems like an analogue to building on top of open weight models.
- jlouis 2y agoTuring completeness makes it a different problem.
- twelve40 2y agoi have very little knowledge of any of this, but i had an impression that OpenAI was trained on commodity cloud hardware that's available for purchase/rent to anyone, including off-the-shelf GPUs from Nvidia and AMD? are those what you are referring to as "the firmware blob", or was there some other, more specialized and custom-built closed hardware involved?
- PollardsRho 2y agoThe math underpinning an AI model exists independent of the hardware it's realized on. I can train a model on one GPU and someone else can replicate my results with a different GPU running different drivers, down to small numerical differences that should hopefully not have major effects. Data isn't fungible in the same way: I can't just replace one dataset with another for research where the data generation and curation is the primary novel contribution and expect to replicate the results. There's also a larger accountability picture: just like scientific papers that don't publish data are inherently harder to check for statistical errors or outright fraud, there's a lot of uncomfortable trust required for open-weight closed-data models. How much contamination is there for the major AI benchmarks? How much copyrighted data was used? How can we be sure that the training process was conducted as the authors say, whether from malfeasance or simple mistakes?