Yann LeCun on why AI must be open source [video]

https://www.youtube.com/watch?v=EGDG3hgPNp8

by smcleod • 3 years ago

123 48 3 years ago

greyface-2• 3 years ago

Original non-editorialized title: "AI: Grappling with a New Kind of Intelligence"

smcleod5• 3 years ago

I linked to a specific timestamp (https://www.youtube.com/watch?v=EGDG3hgPNp8&t=6525s) within the talk which is where Yann LeCun is talking about why AI must be open source.

raldi• 3 years ago

That seems more editorialized to me than the plainspoken one that the submitter used.

greyface-2• 3 years ago

HN guidelines prefer original titles, even if editorialized, as long as they aren't misleading or linkbait. https://news.ycombinator.com/newsguidelines.html

andy994• 3 years ago

Yann Lecun is actively corrupting the term "open source" in relation to AI. If he really is pro open source, he should loudly acknowledge that all the recent models Meta has released do not qualify and push internally for them to go back to Apache 2.0 licensing and stop with their silly "you can only use it for what we allow" proprietary licenses.

For clarity, llama etc are not open source because of the conditions on the license under which the weights are released. It may not be possible to copyright weights or to apply software licenses to them, it hasn't been decided by the courts. But everyone acts like it's possible, as evidenced by the licenses they use. So under that assumption, Meta is not using an open source license with the weights.

Edit: for greater clarity, the open source definition has the following clause

  The license must not restrict anyone from making use of the program in a specific field of endeavor. For example, it may not restrict the program from being used in a business, or from being used for genetic research.

Similar things appear in the debian free software guidelines, fsf free software definition, etc.

The Meta Llama license lists restrictions on field of endeavour. Ergo, not open source. There are other clauses (the one about the number of users) which would also disqualify it, but the use restrictions are the most egregious.

smcleod5• 3 years ago

The term has been polluted for a long time before AI became well known. Just like "DevOps", "Platform Engineering", "Agile" etc... and like those terms it's not a specific thing (e.g. a specific license like "Apache 2.0", "MIT" etc...) but more a general term without qualification of scope. Do I like it? No. But not liking how people are going to continue using a term shouldn't detract from the importance of the intent.

At the end of the day - having LLM tech that has an open source _code_ base is what many people are talking about, the "data" that forms the model isn't always open source and while it would be nice if that was the case - is somewhat similar to open source software vs the data you run in it.

menzoic6• 3 years ago

LLAMA2 is very much open source. You can use it for commercial purposes. The license only restricts companies that have more than 700M monthly active users from using it.

yumraj• 3 years ago

Releasing the trained model does not make it open source.

Open source means something else.

Calling released trained models open source is akin to releasing the binaries of a software for free, without releasing the source code, and calling it open source.

andy994• 3 years ago

You demonstrably don't understand what open source means, which is basically my point, that people like Lecun have been trying to corrupt the meaning to be equivalent to "source available".

I agree with the point you made elsewhere that releasing the data is irrelevant.

amelius2• 3 years ago

It's only open source if you can generate the binary weights from the training data and the training algorithm and training (hyper) parameters, from scratch. Releasing only the binary weights, does not make it open source, just like releasing only binary executables has nothing to do with open source.

notfed• 3 years ago

This comes down to arguing over semantics. Many will argue that "open source" means using a license listed at https://opensource.org/licenses/ . Even CC0 isn't considered open source by this standard.

Even I feel that "700M monthly active user" gives not-so-open vibes, but frankly many of these "open source" licenses have oddly restrictive requirements as well.

dragonwriter2• 3 years ago

LLAMA2 is very much open source.

The inference and training software used to run the model are open source, the concrete model -- that is, the thing for which the weights are the object code -- is not.

The concrete model is free-to-use closed source, which is better than an undisclosed blob hiding behind a SaaS service, but still not open source.

It's also good that the inference and training code are open source, even though the training data and configuration is not.

evrydayhustling3• 3 years ago

Cutting edge AI is a world-changing technology that is at immediate risk of being monopolized by 1-2 organizations pushing for global regulation against competitors and individuals who would develop their own. We desperately need "Open" in this context to be a broad, directional movement resisting that lockdown, not a rehash of licensing dogma drama. If you care about agency within the software ecosystem that surrounds you, at least differentiate the main points of Yann's arguments from holy wars about Llama's license.

andy994• 3 years ago

This isn't MIT vs GPL. It's literally one of those few corporations that's in a position to monopolize AI calling a license that says "you can use this at our pleasure" open source. Any open source movement definitively cannot include such licenses. If this was a split over a smaller thing I'd get your point.

logtempo• 3 years ago

My two cents is that Europe will push, and are pushing, for open-source AI. They're regulating in that way.

andsoitis2• 3 years ago

Cutting edge AI is a world-changing technology that is at immediate risk of being monopolized by 1-2 organizations pushing for global regulation against competitors and individuals who would develop their own.

Open-source tends to foster monopoly and relies on free labor (see Google, Meta, Linux, etc.)

megaman821• 3 years ago

People can and are building things using Llama2 that are not under Meta's control. Every comment is engaging in the definition of open source, but you obviously know what he is referring to. The pipeline to building a functional AI isn't going to perfectly map to just source code.

zer0c00ler• 3 years ago

Wouldn't open source mean you can recreate the model from scratch by knowing the training data?

There is a weird definition of open source that creeps in here.

Llama2 is effectively, proprietary compiled software. GPT-4 is proprietary compiled and hosted as SaaS.

We have yet to see a true open source LLM...

AI/ML is reinventing so many terms it's a bit annoying.

cactusplant73743• 3 years ago

If we did have access to the training data wouldn’t all these organizations be sued for distributing copyright works?

It appears all my favorite books have been scanned by Open AI. I am assuming that they didn’t purchase them.

JieJie• 3 years ago

Quake is Open Source, Quake's data files are not. Llama2 is actually more open than Quake.

asylteltine• 3 years ago

The source is available, you can get the weights, it’s open source…

aftbit• 3 years ago

The llama models are more open source than gpt-3.5-turbo. They aren't "free software" in the full definition, but they are available to be fine-tuned, modified, run offline, and generally tinkered with.

For AI, "open source" is less about the license and what it allows you to do legally, and more about what the technology allows you to build practically.

If/when Meta gets litigious, this might change in a hurry. Right now, there are bigger risks to AI startups (not Google) than worrying about how they'll choose to enforce the llama license.

cushpush• 3 years ago

No you can't license edge weights any more than you can license concentrations of ethanol in gasoline. Modified DNA can be patented, because it falls into one of the categories "process, machine, composition of matter, manufacture" in that it is a new composition of matter. Edge weights are not that.

Edit: Actually, if the training set is IP and the method to train is IP then maybe the weights are licensable, given that it's trade-secret territory. However, ensuring that the edge-weights are not widely disseminated once shared with a licensee is not straightforward and the infeasibility of such makes it an uphill climb. Not like that stops the lawyers from clawing up the tree, tho.

23B1• 3 years ago

As if it wasn't already confusing enough to most people, LeCun misuses "open source" likely at the behest or benefit of his Meta handlers. Because of this, I cannot take anything he says very seriously.

In this field where the metaphysical benefits (and risks) are so great, you simply cannot shade the truth. It's hard enough filtering everyone else's agenda on matters much less significant.

zelphirkalt• 3 years ago

And yet he works for a company not open sourcing their AI stuff. Must be good payment he gets.

marshray• 3 years ago

Leaving aside all the incredibly vague* and broad restrictions supposedly placed upon its use by the license, it's so strange to me that anybody is referring to a 10 GiB binary blob as "open source".

Am I the only one?

It's like finding out that everyone else has an entirely different concept in their head than the one I thought we agreed on a quarter-century ago.

*E.g., Ctrl+F "obscenity".

ninjin• 3 years ago

There is a lot of interesting discussion already, but I think there is also some (perhaps unnecessary) disagreements regarding licensing arising from what I believe are the very different backgrounds in the community. Thus, I will attempt to summarise my own perspective as someone that has been active in the artificial intelligence community for nearly 15 years at this point.

Firstly, I will state that I am in full agreement with LeCun on what he states in the video about the need for AI systems such as LLMs to be open [1]. I am not sure if I entirely agree with his very high optimism regarding AI safety, but I have always been far more concerned about current risks and I suspect that in practice we are very much aligned.

[1] https://yewtu.be/watch?v=EGDG3hgPNp8&t=6525s

Now, let me move to the issue of licensing that I have already talked about at great length in comments on other, older submissions. So let me do something new here and try to put it into a historical context.

Computer science and machine learning in particular has a tradition of openness that goes beyond that of many other fields. What I mean by this is that over the last twenty or so years, there has been a gradual move towards open sharing of research, research outcomes, etc. All under the umbrella of open science and FLOSS. One of the earliest examples I am aware of (there may be others) is how the Journal of Machine Learning Research was established as a direct reaction to the resistance against open access in another leading journal at the time [2]. Similarly, in natural language processing, which my primary field of research, we have an open anthology where the great majority (if not nearly all) of the most important research going all the way back to the 70s is available for everyone to read and use [3]. In AI, we really have pushed back against the big publishers and this is a beautiful thing indeed (one which LeCun has contributed towards at that). So, given the context of this, I believe you can understand the dismay which the field feels when Google Deep Mind publishes papers such as the one on Alpha Go in journals without open access [4]. Yes, getting hold of the papers is not challenging for us, but it clearly goes against the efforts of the great majority of the filed. Thus the dismay.

[2] https://en.wikipedia.org/wiki/Journal_of_Machine_Learning_Re...

[3] https://aclanthology.org

[4] https://www.nature.com/articles/nature24270

Moving now to FLOSS. When I entered the field nearly 15 years ago, it was somewhat of a rarity to find source code attached to papers. Likewise, training data was also not always made available or came under awful (and expensive) licensing agreements such as those imposed by the Linguistic Data Consortium. However, we as researchers released more and more open data and code, and by 2015 or so it was starting to become the norm that both code and data was attached to papers. Back in those days, training a system given the training data took maybe a day or so, thus model weights were less important. In addition, the models were less complex and thus replicating the training procedure was less problematic. Still, we saw more and more papers being published with their weights. In terms of licenses, there was a healthy mix of MIT-like, Apache 2.0, and GPL. The notable exception in the field would be Google Deep Mind, which despite their prominence at best would publish a library or two. This in contrast to say Google "Proper", which gave us say BERT [5]. It is in this context which I and many others view the last few years of closing down and adding restrictions to the sharing of model code and weights.

[5] https://aclanthology.org/N19-1423

On the topic of Facebook, I have always considered Facebook AI Research (FAIR) to be the most open of the commercial research labs. For the first few years what FAIR seem to have defaulted to the same open standards as most of the research community. As an example, RoBERTA [6] was shared freely and was the basis for a lot of research for the next few years. However, at some point something changed inside FAIR and instead of releasing model code and weights under permissive licenses, they first changed their default license to exclude commercial usage, and now most recently ship with custom weights-available licenses and usage policies. This is still better than a lot of their competition, but I hope that given the historical context I have provided here you can see why many members of the community see this as the tide turning in terms of openness in the field and we are concerned. It should also be noted that FAIR still uses open science and open source as terms, despite not honouring the history of the terms.

[6] https://arxiv.org/abs/1907.11692

I want to state that I am not of the position that we are entitled to the work of others. However, I believe the actions of FAIR and others have and will have negative consequences for the long term openness of the field and thus harm both scientific inquiry and industrial innovation. I also believe that it is blatantly dishonest of FAIR and others to claim to support open science and open source, while being in direct violation of this through their actions [7].

[7] https://blog.opensource.org/metas-llama-2-license-is-not-ope...

A very fair line of reasoning states that what weights-available is still better than what "Open"AI and others are doing. I think this is a good point and I agree with it. Likewise, one could argue that maybe this is the best commercial actors can do in light of the current commercialisation and likely internal political pressure. I again think this is a good point, but I still feel that given the historical context the behaviour is still undesirable. Furthermore, I have heard through colleagues how there is now internal pressure inside several organisations to favour carrying out experiments on their models over those of the competition and I do not believe I need to tell you why this is problematic from a scientific perspective.

To finish this already lengthy post, allow me to highlight some problematic portions of the LLaMa 2 license [8].

You will not use the Llama Materials or any output or results of the Llama Materials to improve any other large language model (excluding Llama 2 or derivative works thereof).

This explicitly forbids an ongoing line of research; thus puts limits on the scientific inquiries one can pursue.

Additional Commercial Terms. If, on the Llama 2 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.

This is a direct violation of both how the Free Software Foundation and Open Source Initiative defines FLOSS. It also puts up barriers for researchers at private research labs; thus has a chilling effect on the amount of research conducted.

[8] https://ai.meta.com/llama/license

Apologies for the wall of text. Hopefully some will find some value in my ramblings, just like I have found in yours. I really should get around to writing a weblog...

Yann LeCun on why AI must be open source [video]

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