An old proverb famously states, “If you want to go fast, go alone. If you want to go far, go together.”
This is especially true when it comes to artificial intelligence, where breakneck advances happen seemingly every day. And while individual companies are rapidly fielding their own AI-powered chatbots and analysis tools, real long-term improvement and innovation in this new scientific frontier often requires broad collaboration in developing open and trusted AI systems that produce accurate, reliable, and safe outputs.
Early conventional wisdom held that only so-called ‘closed’ AI systems controlled by one company could be safe and trusted. Some argued that open models would inevitably undermine safety or lead to misuse. But experience is quickly showing that open source models and the collaboration they bring are a powerful tool for promoting security and trust.
The power of collaboration
Collaboration is a powerful force for AI advancement because it fosters diverse perspectives and capabilities. When it comes to AI, collaboration can, in many cases, be optimized by leveraging open source to reduce bias, increase transparency, gain greater control over our data, and ultimately, accelerate time to innovation.
According to McKinsey, organizations that view AI as essential to their competitive advantage are far more likely to use open source AI models and tools than organizations that do not. Open source AI models, tools, and frameworks enable developers and researchers to build upon existing work, rather than starting from scratch, to achieve higher-quality outputs more quickly.
The open source software approach thrives on community contributions, bringing together individuals, companies, and organizations from around the globe to collaborate on shared goals. This is where organizations like the AI Alliance—which was spearheaded by IBM and others, and is comprised of technology creators, developers, and adopters collaborating to advance safe and responsible AI—play a crucial role.
By pooling resources and knowledge, the AI Alliance provides a platform for sharing and developing AI innovations. This meritocracy yields immediate value, both for the broader technology ecosystem and the world at large.
Why the AI Alliance matters today
There are many practical and ethical reasons for such broad-based AI partnerships. AI research and development require substantial resources, including data, computing power, and expertise. The availability of open source models keeps costs down, broadening choices and helping to prevent the concentration of the AI industry in the hands of a few major players.
The AI Alliance also offers a forum to hold honest conversations among like-minded organizations about AI-related legislation and its impacts on greater innovation and adoption.
In a short time, the AI Alliance has blossomed into a vibrant ecosystem, bringing together a critical mass of data, tools, and talent. Today, more than 140 organizational members from 23 countries collaborate through the alliance to address some of the most pressing challenges in AI.
Open source is particularly critical to members of the alliance, including Databricks, which has long championed the democratization of AI. We’ve open sourced many critical big data processing and analytics projects, like the Delta Lake, MLflow, and Unity Catalog tools that underpin many large data and AI deployments today.
When it comes to today’s AI ecosystem, we need to ensure that everyone, including academics, researchers, non-profits, and beyond, can access and understand the best AI tools and models. The more we all understand these models and how to utilize them, the more we can share ideas on how to safely shape the future of AI and subsequently use it to solve today’s toughest challenges.
But we can’t do it alone.
Collaborate, code, and create the future of AI
We established a policy working group within the Alliance to focus not only on advocacy but also on developing responses to government requests that could impact open-source AI development. For example, last year, we contributed to the landmark National Telecommunications and Information Administration study examining potential benefits and risks of open weight frontier AI models.
The final NTIA report strongly underscored the valuable role of open models in today’s AI ecosystem, while also highlighting the need for vigilant monitoring and ongoing evaluation of policies to manage emerging risks in the future.
Our intention is to ensure that AI regulation is thoughtfully crafted so that open source AI thrives. Organizations like the AI Alliance have laid a solid foundation for international cooperation, but it’s just the beginning.
You can create and share your own open source projects, such as datasets, pre-trained models, or utilities, which build on a foundation of AI fairness, transparency, and accessibility to ensure the benefits of AI are widely distributed. Check out GitHub or Hugging Face to look for AI/ML projects that align with your skills and interests.
The advent of AI is a pivotal moment in our collective human history. Experience shows that collaboration will be key to our success in advancing AI innovation with safety and trust. We must move into this promising future with open arms and open software models and tools, adequately prepared for the challenges ahead. Let’s go far—together.
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