The News: On November 29, IBM and Meta announced the launch of the AI Alliance. More than 50 other organizations, including the Linux Foundation, Partnership on AI, University of California Berkeley, AMD, Oracle, and Dell Technologies are founding members. Here are the key details:
- The mission is to support open innovation and open science in AI. Focused on fostering an open community and enabling developers and researchers to accelerate responsible innovation while ensuring “economic competitiveness.”
- Collaborators will pool resources and knowledge and provide a platform for sharing and developing solutions.
- They will “start or enhance” projects that meet the following objectives:
- Develop and deploy benchmarks and evaluation standards and tools for development and use of AI systems, including the creation of a catalog of vetted safety, security, and trust tools.
- Advance the ecosystem of open foundation models.
- Foster an AI hardware accelerator ecosystem.
- Support global AI skills building.
- Develop education content and resources for “informing the public discourse on benefits, risks, solutions, and precision regulation for AI.”
- Working groups will be formed for all major topical areas.
Read the announcement on the launch of the AI Alliance on the website.
The Push for Open Systems: IBM Launches AI Alliance
Analyst Take: The AI Alliance is an industry advocacy group that has a policy agenda? A standards body? A multilateral collaborative? It might be all of those things. One thing is for sure, the focus is on open source and open innovation ecosystems. What will the impact of the AI Alliance be? Here are my thoughts.
Community for Multilateral Collaboration
With 50 members at launch, the AI Alliance will likely be an excellent opportunity to build a community where multilateral collaboration, particularly in the development and integration of open source software and open middleware and hardware for the AI tech stack will take place. There have been lots of examples of bilateral collaborations in this regard: Hugging Face and AMD, Hugging Face and NVIDIA, Hugging Face and Intel, Meta and Qualcomm, etc. The AI Alliance presents the opportunity to move these mostly bilateral collaborations to multilateral ones that might include a much wider range of participants. The concept could significantly accelerate open integration through the entire AI stack.
Standards and the Pace of Working Groups
The AI Alliance mentions they will “develop and deploy benchmarks and evaluation standards.” There are several groups developing AI standards, including the National Institute of Standards and Technology (NIST) and International Organization for Standards (ISO). Standards work is a very collaborative and therefore a very lengthy process. It will be interesting to see how much emphasis the AI Alliance places on this type of work, as the outcomes could literally take years. It could be that the Alliance’s focus will be very narrow to, say, the evaluation standards for open ecosystem integrations only.
Please note that technology working groups in general do not move swiftly. This reality could create anxiety in the generative AI frenzy, particularly at the torrid pace of innovation/mutation.
Advocacy for Policy
Joshua New, Senior Fellow for the IBM Policy Lab, wrote a post that was published December 5 that folds the news of the launch of the AI Alliance into an IBM policy position on AI. It is probably no surprise that much of the language and themes IBM has individually expressed are reflected in the AI Alliance’s goals as well. From New’s post:
Policymakers need not reinvent the wheel to ensure the future of AI remains open as well. To preserve an open innovation ecosystem for AI and capture its benefits, the IBM Policy Lab recommends policymakers:
1. Support precision regulation to address AI risk, reject policies that would sacrifice openness. Policymakers are right to take steps to mitigate the risks of new technologies, and IBM has long advocated for “precision regulation” to address these risks. But certain proposals to address safety risks of AI – such as regulating technology rather than its application or creating an AI licensing regime – are not helpful. These proposals would impose significant constraints on open innovation in AI, limit competition and innovation, democratization and skills, and even safety and security. Instead, policymakers should focus on regulating the application of AI, regardless of whether it is open or closed.
2. Enable open innovation ecosystems. While open innovation ecosystems are largely decentralized and self-directed, policymakers can still take steps to ensure they can flourish. Government efforts to facilitate the development of AI standards and advance the science of AI – such as through the UK and U.S. AI Safety Institutes – should encourage the adoption of openly developed and licensed standards, prioritize open access to AI safety research, and share technical resources and other inputs that enable broad collaboration in AI.
There has not been a de facto advocacy group for AI heading into what will clearly be a few years of AI policy and regulations. The AI Alliance might be placing a stake in the ground for certain views.
Impact, Conclusions
AI innovation is clearly not limited to open source. We would not be at the place we are today with generative AI without proprietary products and systems. Note the absence of the major hyperscalers in this organization as well as other heavyweights such as NVIDIA. There are certainly conflicting opinions about an open source-only approach to AI advocacy, lest we forget the Frontier Model Forum.
Open source and open innovation ecosystem options are good for the market, but they also have their drawbacks—open collaboration from public sources makes security of the systems challenging; organizations that leverage open source are in the do-it-yourself mode; expertise for managing and updating systems is typically handled in-house; when something breaks, there are no vendors to swoop in and save the day with their expert support. The reality is that open source/open innovation ecosystems will share the AI market with private/proprietary options.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other Insights from The Futurum Group:
Two Trends in AI Regulations and a Look at Microsoft Copilot – The AI Moment, Episode 2
Mr. Benioff Goes to Washington
Adults in the Generative AI Rumpus Room: Cohere, IBM, Frontier Model Forum
Author Information
Mark comes to The Futurum Group from Omdia’s Artificial Intelligence practice, where his focus was on natural language and AI use cases.
Previously, Mark worked as a consultant and analyst providing custom and syndicated qualitative market analysis with an emphasis on mobile technology and identifying trends and opportunities for companies like Syniverse and ABI Research. He has been cited by international media outlets including CNBC, The Wall Street Journal, Bloomberg Businessweek, and CNET. Based in Tampa, Florida, Mark is a veteran market research analyst with 25 years of experience interpreting technology business and holds a Bachelor of Science from the University of Florida.
