Tom Callaway’s Post

I full endorse Spots words here. We need to get it right, more than ever in my view given the challenges we have seen with open source over the past few years.

I totally agree with Tom Callaway—it's so important that we protect the true spirit of open source in AI. The way we define this now will impact innovation for years to come. Let's make sure we're getting it right. #openSource #Innovation #AI

'Openwashing': An anonymous reader quotes a report from The New York Times: There's a big debate in the tech world over whether artificial intelligence models should be "open source." Elon Musk, who helped found OpenAI in 2015, sued the startup and its chief executive, Sam Altman, on claims that the company had diverged from its mission of openness. The Biden administration is investigating the risks and benefits of open source models. Proponents of open source A.I. models say they're more equitable and safer for society, while detractors say they are more likely to be abused for malicious intent. One big hiccup in the debate? There's no agreed-upon definition of what open source A.I. actually means. And some are accusing A.I. companies of "openwashing" -- using the "open source" term disingenuously to make themselves look good. (Accusations of openwashing have previously been aimed at coding projects that used the open source label too loosely.) In a blog post on Open Future, a European think tank supporting open sourcing, Alek Tarkowski wrote, "As the rules get written, one challenge is building sufficient guardrails against corporations' attempts at 'openwashing.'" Last month the Linux Foundation, a nonprofit that supports open-source software projects, cautioned that "this 'openwashing' trend threatens to undermine the very premise of openness -- the free sharing of knowledge to enable inspection, replication and collective advancement." Organizations that apply the label to their models may be taking very different approaches to openness. [...] The main reason is that while open source software allows anyone to replicate or modify it, building an A.I. model requires much more than code. Only a handful of companies can fund the computing power and data curation required. That's why some experts say labeling any A.I. as "open source" is at best misleading and at worst a marketing tool. "Even maximally open A.I. systems do not allow open access to the resources necessary to 'democratize' access to A.I., or enable full scrutiny," said David Gray Widder, a postdoctoral fellow at Cornell Tech who has studied use of the "open source" label by A.I. companies. Read more of this story at Slashdot.

Head over to our on-demand library to view sessions from VB Transform 2023. Register Here A coalition of a half-dozen open source AI stakeholders, — Hugging Face, GitHub, EleutherAI, Creative Commons, LAION and Open Future — are calling on EU policymakers to protect open source innovation as they finalize the EU AI Act, which will be the world’s first comprehensive AI law. In a policy paper released today, “Supporting Open Source and Open Science in the EU AI Act,” the open source AI leaders offered recommendations “for how to ensure the AI Act works for open source” — with the “aim to ensure that open AI development practices are not confronted with obligations that are structurally impractical to comply with or that would be otherwise counterproductive.” According to the paper, “overbroad obligations” that favor closed and proprietary AI development — like models from top AI companies such as OpenAI, Anthropic and Google — “threaten to disadvantage the open AI ecosystem.” The paper was released as the European Commission, Council and Parliament debate the final EU AI Act in what is known as the “trilogue,” which began after the European Parliament passed its version of the bill on June 14. The goal is to finish and pass the AI Act by the end of 2023 before the next European Parliament elections. Event VB Transform 2023 On-Demand Did you miss a session from VB Transform 2023? Register to access the on-demand library for all of our featured sessions.   Register Now Open source AI innovation is at stake Yacine Jernite, ML and society lead at Hugging Face, a popular hub for open-source code and models, told VentureBeat that while the policy paper is detailed, the first main point the coalition wants to make is around innovation. “We think that it is important for people to be able to choose between base models, between components, to mix and match as they need,” he said. In addition, the coalition seeks to emphasize that open source AI is necessary — and that regulation should not hinder open source AI innovation. “Openness by itself does not guarantee responsible development,” Jacine explained. “But openness and transparency is necessary to responsible governance — so it is not that openness [should be] exempt from requirements, but requirements should not preclude open development.” The EU AI Act is focused on application risk Since April 2021, when the European Commission proposed the first EU regulatory framework for AI, it has worked to focus on analyzing and classifying AI systems according to the risk they pose to users. The higher the risk level, the more regulation. Peter Cihon, senior policy manager at GitHub, pointed out that as the EU Council, and subsequently the EU Parliament developed their drafts of the AI Act, the policy makers began to look up the value chain to how mitigate some of these risks

'Openwashing': An anonymous reader quotes a report from The New York Times: There's a big debate in the tech world over whether artificial intelligence models should be "open source." Elon Musk, who helped found OpenAI in 2015, sued the startup and its chief executive, Sam Altman, on claims that the company had diverged from its mission of openness. The Biden administration is investigating the risks and benefits of open source models. Proponents of open source A.I. models say they're more equitable and safer for society, while detractors say they are more likely to be abused for malicious intent. One big hiccup in the debate? There's no agreed-upon definition of what open source A.I. actually means. And some are accusing A.I. companies of "openwashing" -- using the "open source" term disingenuously to make themselves look good. (Accusations of openwashing have previously been aimed at coding projects that used the open source label too loosely.) In a blog post on Open Future, a European think tank supporting open sourcing, Alek Tarkowski wrote, "As the rules get written, one challenge is building sufficient guardrails against corporations' attempts at 'openwashing.'" Last month the Linux Foundation, a nonprofit that supports open-source software projects, cautioned that "this 'openwashing' trend threatens to undermine the very premise of openness -- the free sharing of knowledge to enable inspection, replication and collective advancement." Organizations that apply the label to their models may be taking very different approaches to openness. [...] The main reason is that while open source software allows anyone to replicate or modify it, building an A.I. model requires much more than code. Only a handful of companies can fund the computing power and data curation required. That's why some experts say labeling any A.I. as "open source" is at best misleading and at worst a marketing tool. "Even maximally open A.I. systems do not allow open access to the resources necessary to 'democratize' access to A.I., or enable full scrutiny," said David Gray Widder, a postdoctoral fellow at Cornell Tech who has studied use of the "open source" label by A.I. companies. Read more of this story at Slashdot.

'Openwashing': An anonymous reader quotes a report from The New York Times: There's a big debate in the tech world over whether artificial intelligence models should be "open source." Elon Musk, who helped found OpenAI in 2015, sued the startup and its chief executive, Sam Altman, on claims that the company had diverged from its mission of openness. The Biden administration is investigating the risks and benefits of open source models. Proponents of open source A.I. models say they're more equitable and safer for society, while detractors say they are more likely to be abused for malicious intent. One big hiccup in the debate? There's no agreed-upon definition of what open source A.I. actually means. And some are accusing A.I. companies of "openwashing" -- using the "open source" term disingenuously to make themselves look good. (Accusations of openwashing have previously been aimed at coding projects that used the open source label too loosely.) In a blog post on Open Future, a European think tank supporting open sourcing, Alek Tarkowski wrote, "As the rules get written, one challenge is building sufficient guardrails against corporations' attempts at 'openwashing.'" Last month the Linux Foundation, a nonprofit that supports open-source software projects, cautioned that "this 'openwashing' trend threatens to undermine the very premise of openness -- the free sharing of knowledge to enable inspection, replication and collective advancement." Organizations that apply the label to their models may be taking very different approaches to openness. [...] The main reason is that while open source software allows anyone to replicate or modify it, building an A.I. model requires much more than code. Only a handful of companies can fund the computing power and data curation required. That's why some experts say labeling any A.I. as "open source" is at best misleading and at worst a marketing tool. "Even maximally open A.I. systems do not allow open access to the resources necessary to 'democratize' access to A.I., or enable full scrutiny," said David Gray Widder, a postdoctoral fellow at Cornell Tech who has studied use of the "open source" label by A.I. companies. Read more of this story at Slashdot.

Charities are at the core of the #OpenSource community mindset! If you have worked in the cyber security industry there is no way the common individual or organization could even come near to affording enterprise security. #SMB organizations were left out of cutting edge cyber security solutions. Hopefully, we can fix this.

Opensource LLM or OpenDownload LLM⁉️ Dear community, I recently decided to abandon my latest work (article) on the definition of open, open-open and open-closed in the era of AI (previously posted) - the work was based on my observations made on confusion in the system (industry wide) about Opensource LLM - where I decided to demystify the topic. Reason is shared below (2nd point). 🛑 I have personally been unable to accept it, as a technologist and thinker, when anyone said the word “Opensource LLM”. According to me, no LLM (famous ones) as of now qualified to satisfy the traditional working definition of Opensource Software. Just because some LLMs are freely downloadable - are they Opensource? Opensource is more than just sharing some code or research. To be truly open source is to offer free redistribution, access to the source code, allow modifications, place no restrictions and must not be tied to a specific product (of a company). There should be no restrictions based on the number of active users or dictating the terms of improvements tied to a product of any company. It is also about how you develop the model, which datasets you leverage or even sharing all those assets with the community. It is developed in a decentralised and collaborative way, relying on peer review and community production. On the other hand, there may be a perspective which sees AI models as fundamentally different from Software (is it though?). And, as the risk involved is higher, Opensource for AI may need a new definition (different from non-AI Software). What is becoming clearer is that, Opensource AI needs to be debated, agreed upon and well defined. 💡This MIT Technology Review article reflects my personal thought process 💯(reason of me abandoning the said work - I was late in publishing by a week due to other priorities). 💎 Good news is, OSI has now taken up the matter more seriously - involving several industry players to define what it means. Now, the organisation has assembled a 70-strong group of researchers, lawyers, policymakers, activists, and representatives from big tech companies to come up with a working definition of Opensource AI. 💎 Defining whole Opensource AI needs a pragmatic-selfless-democratic approach and ingenuity. I would be delighted to contribute and lead in this space for the industry. Reach out to collaborate. I have a draft ready already anyway. 💡💡 💙 Delighted to know that I was not alone with my thinking all this while on this complex topic. Glad to discover and e-meet more like minded thought leaders on this AI topic. 💡The big questions I personally have are: Can LLMs ever be built by the Opensource communities in true Software sense? If yes, who provides the GPUs, training datasets etc. to the Opensource communities? If no, will OSI bend the definition of Opensource to accommodate human-made evolution and realities of AI? Disclaimer: Personal post. Personal thought process. Opensource contribution.

➡️ AI4C (AI for Charities) Community #OpenSource #AI The Open Source Initiative (OSI) has announced plans to further clarify the definition of open source AI by embarking on a global workshop series aimed at garnering input from experts. The OSI said it will engage with a range of stakeholders in the open source space, using their contributions to further develop the draft definition of open source AI it has been working on. These workshops will be held in five continents including North America, Europe, Africa, Asia, and Latin America, with the intention of presenting a “stable version” of the definition at the ‘All Things Open’ event in North Carolina. “AI is different from regular software and forces all stakeholders to review how the Open Source principles apply to this space,” Stefano Maffulli executive director of the OSI, said. “After spending almost two years gathering voices from all over the world to identify the principles of Open Source suitable for AI systems, we’re embarking on a worldwide roadshow to refine and validate the release candidate version of the Open Source AI Definition.” According to the OSI, the complete definition will provide a framework for AI developers to determine whether an AI platform is open source or not, acting as an accepted standard for open source software specifically in the AI space. Despite the OSI’s mission to create a clear cut definition of open source AI, questions remain over the extent to which current AI models can be defined as open source, with many big name models criticized over their supposed alignment with the community. Companies like Meta have defined their models as open, but experts in the field such as OpenUK CEO Amanda Brock have noted that these are not “truly, 100% open source” due to certain stipulations in their terms and conditions. The Linux Foundation recently made a move similar to that of the OSI to address this problem, unveiling the Open Platform or Enterprise AI (OPEA) as a graded approach to open source AI. The OPEA breaks down AI platforms into their constituent parts, granting open source licenses where possible and different licenses where not, so as to better integrate open source into the complex technology of AI. https://lnkd.in/eB76pwM7

Someone asked me recently why I'd stopped posting about Open Source and AI. It's not because my feelings have changed (they have not), but because it felt pointless to keep saying the same things over and over. I do think this will end up being a flashpoint. Up until now, we've had a shared understanding of what it means for anything to be Open Source. Yes, the Open Source Definition defined what it meant for a _software license_ to be considered Open Source, but Open Source stopped meaning just "software" a long time ago. Fundamentally, open source means that you have _everything_ you need to, without restriction, use, study, modify, and share, a thing. That thing could be software, images, hardware, curriculum, seeds, whatever. Now, the OSI wants to change that, and say that it's okay to not have _everything_ you need to study and modify an AI system, but still call it open source. We, the Open Source community, know better. The OSI has been a good steward of the Open Source Definition for years (though, they didn't write it), and despite not having any legal mechanism to protect Open Source, they were trusted. Now, they're going to lose our trust. We know what Open Source means. If the OSI has lost sight of that, it doesn't change it. Their definition depends on trust, and they don't have it. Everything you need to use, study, modify, and share, without restriction.