Steven Johnson, the acclaimed author of “Interface Culture,” brilliantly articulated the essence of collaborative innovation in an article wrote in 2012. He highlights the pervasive role of open-source software in our daily lives and prompts us to envision — in an announcer’s dramatic tone — a scenario where open source doesn’t exist. Johnson vividly describes this alternate reality：
“For starters, the Internet and the Web would instantly evaporate. Every Android smartphone, every iPad, iPhone and Mac would go dark. A massive section of our energy infrastructure would cease to function. The global stock markets would go offline for weeks, if not longer. Planes would drop out of the sky. It would be an event on the scale of a world war or a pandemic.”
The core principles of open source are straightforward and familiar, but why has open source risen to prominence? Why has Linux been so successful and why has it become such a powerful force in technology?
The essential reason for this is largely due to the advent of the Internet and the constraint of intellectual property rights.
The Internet acts as a catalyst for open source, facilitating large-scale, decentralized collaboration. Conversely, the restrictive nature of intellectual property laws has driven many innovative minds, including programmers, scientists, and engineers, to seek alternative methods for creation.
Part of the success of open source is the success of the software, and the other part is the success of the talented engineers.
The success of open source in software development is attributable to the precise nature of programming, where quality is directly linked to the code’s efficacy. This has facilitated the establishment of meritocratic, inclusive open source software projects. However, the principles of open source extend beyond software. Programmers may have been the pioneers of open source, largely due to their proximity to the Internet, but its potential applications are far broader.
Incorporating this perspective into generative Artificial Intelligence, the need for open source becomes even more pronounced. AI’s complexity and impact demand a collaborative approach to ensure ethical development, diverse input, and equitable access. Just as the Internet and open source revolutionized software, they hold the key to unlocking AI’s full potential through open, inclusive, and democratized innovation.
One of the best known cases is LAION.
What is LAION’s Impact and the Significance of Open Source in the Realm of Artificial Intelligence?
LAION, the Large-Scale Artificial Intelligence Open Network, is a vast community dedicated to open-source AI models, research, and data sharing. It started with Christoph Schuhmann, a teacher involved in machine learning and reform-oriented education, who was inspired by AI advancements like DALL-E. LAION’s journey began with Schuhmann’s engagement in Discord communities, leading to the creation of the LAION-400M dataset, which surpassed existing datasets in size and scope. Supported by companies like Hugging Face and StabilityAI, LAION expanded its efforts, contributing significantly to AI development.
The organization emphasizes open source’s importance in AI, likening AI technologies to “superpowers” that should be democratically accessible rather than controlled by a few entities. Schuhmann argues for open-source AI to foster creativity, transparency, and ethical development. LAION’s projects, including LAION-5B and LAION-Aesthetics datasets, have been instrumental in AI advancements like Stable Diffusion. They promote open collaboration, inviting contributions and participation from diverse backgrounds.
Schuhmann’s vision extends beyond AI development to societal applications, advocating for open-source AI as a tool for global educational access and innovation. He suggests that AI, like ChatGPT, could revolutionize education, especially in underprivileged areas, by providing high-quality learning resources. LAION’s commitment to open source in AI reflects a broader vision of technology as a democratic tool for societal betterment and innovation.
Christoph Schuhmann said in an interview:
“Let’s take the sentence: AI should be open source so that it is available to the general public. Now let’s take that sentence and replace ‘AI’ with ‘superpower’:‘Superpowers’ should be open source and available to the public. In this case, it becomes much more obvious what I’m actually getting at.
Imagine if there was such a thing as superpowers, and only the big companies have control over it and can decide what to do with it.
If you have a very dark view of the world, you might say that there are a lot of bad people out there, and if everyone had superpowers now, there would certainly be 10,20, or 30 percent of all people who would do really bad things. That’s why we have to control such things, for example through the state. But if you have a rather positive and optimistic view of the world, like me, for example, then you could say that most people are relatively nice. No angels, no do-gooders, but most people don’t want to actively do something bad, or destroy something, but simply live their lives. There are some people who are do-gooders and also people who have something bad in mind. But the latter are probably clearly in the minority.
If we assume that everyone has superpowers, then everyone would also have the opportunity to take action against destructive behaviour and limit its effects. In such a world, there would be a lot of positive things. Things like superpower art, superpower music, superpower computer games, and superpower productivity of companies that simply produce goods for the public. If you now ask yourself what kind of world you would like to live in and assume that you have a rather positive worldview, then you will probably decide that it would be good to make superpowers available to the general public as open source. And once you understand that, it’s very easy to understand that AI should also be open source.”
In 2003, Thomas Goetznov published an article in Wired titled “Open Source Everywhere.”
Open source, despite its contemporary novelty, isn’t a new concept. Reflecting on Isaac Newton’s era in the late 1600s reveals similar ideals of sharing scientific methods and results, with roots traceable to Ptolemy around AD 150. This ethos is also mirrored in traditional practices like the Amish barn raising from the early 18th century and the creation of the Oxford English Dictionary in the 19th century, a monumental effort by a wide network of etymologists communicating by mail. The Human Genome Project, a distributed gene-mapping initiative that started a year before Torvalds began his operating system, also embodies the principles of open source.
Thousands of programmers, hackers, and developers responded to Linus Torvalds’ call, contributing to the development of a robust system that continues to gain momentum. However, the true marvel of Linux lies not in its market success, but in its creation process.
Open source is characterized by extensive collaboration, often from volunteers, where each contribution adds to the previous ones. Crucially, the resulting product is freely accessible to everyone. It’s important to note, though, that not everything collaborative and free is open source , and some projects may not be broadly collaborative or have elements of propriety but still align with the open source ethos. The term “open source” is sometimes used loosely, so it’s better to think of it on a spectrum, with openness and collaboration as its axes. The more a project embodies these two aspects, the more it aligns with true open source principles.
20 years have passed, with generative AI, everyone is facing a new era of technological transformation.
However，What needs to be made clear is that open source initiatives thrive when diverse minds unite around a common challenge, agreeing on solutions. Linux empowered developers to create a streamlined, superior operating system. In the realm of artificial intelligence, this principle becomes even more crucial. AI’s vast potential can only be fully realized through collective ingenuity, ensuring that these powerful tools evolve in a way that serves humanity broadly, rather than being confined to the proprietary interests of a few.
Open source projects can be deconstructed into smaller tasks, allowing a global community of volunteers to contribute. Tim O’Reilly’s concept of the “architecture of participation” exemplifies open source’s unique strength: harnessing a diverse range of expertise and perspectives that no single corporation can match. This is especially pertinent in AI, where the complexity and ethical implications of the technology demand a wide range of expertise and oversight. However, to maintain coherence and quality, a structured review process is essential, preventing the project from fragmenting into less effective offshoots.
The ethos of open source dictates that contributions should be accessible for all to refine and that enhancements benefit the entire community. This principle is particularly vital in AI, where advancements could have profound societal impacts. By prioritizing shared progress over proprietary ownership, AI development can be a collective achievement, harnessing the power of many to ensure technologies are developed ethically, responsibly, and for the greater good.
The true measure and promise of open source extend far beyond minor improvements or tweaks. It’s about pioneering new paths and discovering superior methods. Open source transcends the realm of software development; it’s a philosophy that advocates for excellence in all domains. It’s not just about creating better software; it’s about enhancing every aspect of how we create, collaborate, and innovate.
Reference:
https://www.nytimes.com/2012/09/23/magazine/the-internet-we-built-that.html?pagewanted=all&_r=2&http://
https://www.wired.com/insights/2013/07/in-a-world-without-open-source/#:~:text=%E2%80%9CFor%20starters%2C%20the%20Internet%20and,for%20weeks%2C%20if%20not%20longer.
https://www.wired.com/2003/11/opensource/
https://mlconference.ai/blog/ai-as-a-superpower-laion-and-the-role-of-open-source-in-artificial-intelligence/
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