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On Fri, 24 Jan, 12:02 AM UTC
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[1]
This new framework aims to finally set the standard for open-source AI models
Open-source and artificial intelligence (AI) developers and leaders agree that open-source AI is important. Despite the best efforts of the Open Source Initiative (OSI) to create an open-source AI definition (OSAID), there is still much disagreement on what should and shouldn't be included in an OSAID. Springing from this disagreement, the newly formed Open Source Alliance (OSA) has released its take on OSAID: the Open Weight Definition (OWD). The OWD is a new framework that balances closed and open-source AI integrity. The framework is designed, its creators say, to address the complexities and challenges posed by the rapid development of AI technology. It aims to provide a clear standard for what constitutes "open source" in AI models, particularly large language models (LLMs). Also: DeepSeek's new open-source AI model can outperform o1 for a fraction of the cost Weights are fundamental components in AI. Based on the raw data, weights are the numerical values associated with the connections between nodes across different layers of an AI program. These values are determined during the machine learning training process. Specifically, the OWD includes: Amanda Brock, OpenUK's CEO, said she supports the OWD: "The Alliance is being driven to broaden the engagement across multiple organizations currently competing to ensure better global collaboration. This first step of sharing an approach to defining open weights is in line with the disaggregation of AI and defining the level of openness of the disaggregated but critical component, whether that be data, weight, or model. ... It certainly seems to be more practical and workable than a small group creating a definition that isn't fit for purpose." This final comment was in reference to the OSI's OSAID, which Brock has opposed. Indeed, the OSA has seized upon the open-source AI issue to attempt to replace the OSI. In January, its founder Sam Johnston, said in a press release: "Data has tested the boundaries of the Open Source Definition (OSD), which is proven on openness but lacking on completeness beyond source code components." By adding OWD to the OSD, Johnston wants to create an Open Source 2.0. Also: OpenAI's o1 lies more than any major AI model. Why that matters Brock added that despite the publication of the OSAID definition last October, "the OSI is 'at the start of the journey' with the definition. In my mind, this shows that the approach of trying to define 'open source AI' is wrong. Rather we should follow this disaggregated approach to the challenge and look at the underlying 'technology,' including the training data, and what it means to be open. Open source doesn't define law, and it should not. It's about what enables anyone to use the technology's 'source', including data for any purpose." Brock concluded: "The reality and accuracy of this must be understood in assessing risk and liability. So for today, The Alliance announcement of a definition of open weight is a welcome one." In response to the OWD announcement, Stefano Maffulli, the OSI's executive director, said: "Communities build standards and definitions. The Linux Foundation community already has a definition of open weights in the Model Openness Framework." The Linux Foundation isn't the only party that's addressed open-weight standardization. Prominent open-source lawyer Heather Meeker also addressed them. Meeker wrote: "In the realm of AI, there's a fundamental misunderstanding that needs to be addressed -- the assumption that the principles of open source software licensing can directly apply to Neural Net Weights (NNWs). The misconception stems from conflating two different artifacts -- software source code and NNWs." Also: I spent hours testing ChatGPT Tasks - and its refusal to follow directions was mildly terrifying She continued: "NNWs are different. They represent the 'knowledge' an artificial neural network has learned and are often stored as large matrices of numbers. Unlike source code, NNWs are not human-readable or debuggable. [...] Open source's foundational freedoms -- to run, study, redistribute, and modify software -- do not translate easily to NNWs. While you can run and distribute NNWs, studying and modifying them is non-trivial, or functionally impossible." You can share NWWs under an open-source-style license, Meeker's proposed Open Weights Permissive License. But, as she noted: "This definition focuses instead on the original idea of openness, and preserving the original goals of Freedom Zero of free software and open source." Mafflli said: "TheOSI is watching to see what AI practitioners actually do. Like the LF's work, OSI's definitions are developed by and with the community. This was the case with the original Open Source Definition that was developed on top of 20+ years of free software communities building and releasing software. It's what we've done with AI: the community has led the process to define Open Source AI." In an interview, Meeker added: "I hope the various definitional efforts (the OSI's Open Source AI definition, The Open Weights Definition I first published in 2022, and this new definition) can converge. Unfortunately, though, it seems likely none of these definitions will become a de facto standard like the Open Source definition -- they have all been eclipsed by disparate regulatory frameworks and privacy regulations and vendors who are setting practices in a highly concentrated market." What this debate boils down to is we're still debating what precisely open-source AI looks like. True, open-source leaders can agree that simply saying an AI program or data is open-source doesn't mean that it is, which is what Meta did with Llama. But we're still nowhere close to finding unity in an open-source AI definition.
[2]
The Open Weight Definition offers another take on the OSAID debate
Open-source and artificial intelligence (AI) developers and leaders agree that open-source AI is important. Despite the best efforts of the Open Source Initiative (OSI) to create an open-source AI definition (OSAID), there is still much disagreement on what should and shouldn't be included in an OSAID. Springing from this disagreement, the newly formed Open Source Alliance (OSA) has released its take on OSAID: the Open Weight Definition (OWD). The OWD is a new framework that balances closed and open-source AI integrity. The framework is designed, its creators say, to address the complexities and challenges posed by the rapid development of AI technology. It aims to provide a clear standard for what constitutes "open source" in AI models, particularly large language models (LLMs). Also: DeepSeek's new open-source AI model can outperform o1 for a fraction of the cost Weights are fundamental components in AI. Based on the raw data, weights are the numerical values associated with the connections between nodes across different layers of an AI program. These values are determined during the machine learning training process. Specifically, the OWD includes: Amanda Brock, OpenUK's CEO, said she supports the OWD: "The Alliance is being driven to broaden the engagement across multiple organizations currently competing to ensure better global collaboration. This first step of sharing an approach to defining open weights is in line with the disaggregation of AI and defining the level of openness of the disaggregated but critical component, whether that be data, weight, or model. ... It certainly seems to be more practical and workable than a small group creating a definition that isn't fit for purpose." This final comment was in reference to the OSI's OSAID, which Brock has opposed. Indeed, the OSA has seized upon the open-source AI issue to attempt to replace the OSI. In January, its founder Sam Johnston, said in a press release: "Data has tested the boundaries of the Open Source Definition (OSD), which is proven on openness but lacking on completeness beyond source code components." By adding OWD to the OSD, Johnston wants to create an Open Source 2.0. Also: OpenAI's o1 lies more than any major AI model. Why that matters Brock added that despite the publication of the OSAID definition last October, "the OSI is 'at the start of the journey' with the definition. In my mind, this shows that the approach of trying to define 'open source AI' is wrong. Rather we should follow this disaggregated approach to the challenge and look at the underlying 'technology,' including the training data, and what it means to be open. Open source doesn't define law, and it should not. It's about what enables anyone to use the technology's 'source', including data for any purpose." Brock concluded: "The reality and accuracy of this must be understood in assessing risk and liability. So for today, The Alliance announcement of a definition of open weight is a welcome one." In response to the OWD announcement, Stefano Maffulli, the OSI's executive director, said: "Communities build standards and definitions. The Linux Foundation community already has a definition of open weights in the Model Openness Framework." The Linux Foundation isn't the only party that's addressed open-weight standardization. Prominent open-source lawyer Heather Meeker also addressed them. Meeker wrote: "In the realm of AI, there's a fundamental misunderstanding that needs to be addressed -- the assumption that the principles of open source software licensing can directly apply to Neural Net Weights (NNWs). The misconception stems from conflating two different artifacts -- software source code and NNWs." Also: I spent hours testing ChatGPT Tasks - and its refusal to follow directions was mildly terrifying She continued: "NNWs are different. They represent the 'knowledge' an artificial neural network has learned and are often stored as large matrices of numbers. Unlike source code, NNWs are not human-readable or debuggable. [...] Open source's foundational freedoms -- to run, study, redistribute, and modify software -- do not translate easily to NNWs. While you can run and distribute NNWs, studying and modifying them is non-trivial, or functionally impossible." You can share NWWs under an open-source-style license, Meeker's proposed Open Weights Permissive License. But, as she noted: "This definition focuses instead on the original idea of openness, and preserving the original goals of Freedom Zero of free software and open source." Mafflli said: "TheOSI is watching to see what AI practitioners actually do. Like the LF's work, OSI's definitions are developed by and with the community. This was the case with the original Open Source Definition that was developed on top of 20+ years of free software communities building and releasing software. It's what we've done with AI: the community has led the process to define Open Source AI." In an interview, Meeker added: "I hope the various definitional efforts (the OSI's Open Source AI definition, The Open Weights Definition I first published in 2022, and this new definition) can converge. Unfortunately, though, it seems likely none of these definitions will become a de facto standard like the Open Source definition -- they have all been eclipsed by disparate regulatory frameworks and privacy regulations and vendors who are setting practices in a highly concentrated market." What this debate boils down to is we're still debating what precisely open-source AI looks like. True, open-source leaders can agree that simply saying an AI program or data is open-source doesn't mean that it is, which is what Meta did with Llama. But we're still nowhere close to finding unity in an open-source AI definition.
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The Open Source Alliance introduces the Open Weight Definition, a new framework for open-source AI models, sparking debate among industry leaders about the future of open-source AI standards.
The Open Source Alliance (OSA) has unveiled the Open Weight Definition (OWD), a new framework aimed at setting standards for open-source AI models, particularly large language models (LLMs). This initiative comes in response to ongoing debates about what constitutes "open source" in the rapidly evolving field of artificial intelligence 12.
The OWD focuses on weights, which are fundamental components in AI systems. These weights represent the numerical values associated with connections between nodes in different layers of an AI program, determined during the machine learning training process 12.
Amanda Brock, CEO of OpenUK, expressed support for the OWD, stating that it aligns with the need to define openness in disaggregated AI components, including data, weights, and models. She emphasized that this approach seems more practical than previous attempts to create a comprehensive open-source AI definition 12.
Heather Meeker, a prominent open-source lawyer, highlighted the difficulties in directly applying open-source software licensing principles to Neural Net Weights (NNWs). She explained that NNWs, unlike source code, are not human-readable or easily modifiable, making it challenging to apply traditional open-source freedoms to these AI components 12.
The introduction of the OWD has sparked discussions among various stakeholders in the AI and open-source communities:
The Open Source Initiative (OSI) previously released its own Open Source AI Definition (OSAID), which has faced criticism for its approach 12.
The Linux Foundation has already established a definition of open weights in its Model Openness Framework, as noted by Stefano Maffulli, OSI's executive director 12.
Heather Meeker proposed an Open Weights Permissive License, focusing on preserving the original goals of free software and open source 12.
Sam Johnston, founder of the OSA, aims to create an "Open Source 2.0" by combining the OWD with the existing Open Source Definition (OSD) 12.
Heather Meeker expressed hope for convergence among various definitional efforts but acknowledged the challenges posed by regulatory frameworks, privacy regulations, and market practices set by dominant vendors 12.
The introduction of the OWD highlights the ongoing debate about the nature of open-source AI. While industry leaders agree that simply labeling an AI program or dataset as open-source does not make it so, there is still no unified definition or standard for open-source AI 12.
As the AI industry continues to evolve rapidly, the quest for a universally accepted open-source AI definition remains an important challenge for developers, researchers, and policymakers alike.
The Open Source Initiative (OSI) has released the Open Source AI Definition (OSAID) 1.0, establishing criteria for what qualifies as open-source AI. This definition has sparked debate and disagreement among tech companies and AI developers.
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The open-source AI community has reached a consensus on a definition for open-source AI, marking a significant milestone in the field. However, the new definition has sparked debates and raised concerns among various stakeholders.
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Tech giants like Google and Meta face scrutiny over their 'open-source' AI models. The Open Source Initiative questions whether these models truly meet open-source criteria, sparking a debate in the tech community.
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Meta has released Llama 3.1, its largest and most advanced open-source AI model to date. This 405 billion parameter model is being hailed as a significant advancement in generative AI, potentially rivaling closed-source models like GPT-4.
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