User-Owned AI: The Future of AI in the Decentralized Era with NEAR, Masa and Compute Labs
This week, Masa’s Co-founders, Brendan Playford and Calanthia Mei, and Compute Labs’ Founder Albert Z, joined NEAR’s Co-founders, Illia Polosukhin and Alex Skidanov, on their AI Office Hours broadcast, doing a deep dive into the evolving landscape of artificial intelligence. In this engaging broadcast, which had over 5,000 live viewers and 11,600 total views in the first 24 hours, they covered the cutting edge topic of, “Building a new User-Owned AI Economy.”
In this blog we highlight and summarize the transformational conversation on the quest for user-owned AI.
> Watch the broadcast here on X
Centralized AI vs. Decentralized AI
The recent announcement from Apple’s WWDC24 event about the partnership with OpenAI to boost its Siri voice assistant, as well as its operating systems with OpenAI’s ChatGPT, caused a storm on social media.
Even Elon Musk voiced his concerns about data privacy: “Apple has no clue what’s actually going on once they hand your data over to OpenAI.”
Illia prompted the panel to discuss this latest development, and the privacy concerns it raises. Brendan, Co-founder of Masa, voiced strong opinions about the issue of major corporations like Apple and OpenAI gathering data from users. “We need to push back and fight for decentralized AI,” he argued passionately. “Decentralized AI is about creating equal opportunities and aligning incentives for the greater good.”
Calanthia, Co-founder of Masa, added, “We see the entire human race at the crossroads of Centralized AI versus Decentralized AI. The good thing is that we are building in parallel.”
Illia introduced the concept of “user-owned AI.” He explained, “The difference is user-owned AI focuses on the user’s success and well-being, not just generating revenue for companies.” He also highlighted how this vision aligns perfectly with Masa’s new slogan, “Fair AI, powered by the people.”
Illia elaborated on how this approach shifts the focus from corporate profits to individual empowerment. “It’s not about decentralization for its own sake,” he said. “It’s about making AI work for the user, enhancing their financial well-being and overall success.”
Why Does AI Need Decentralization?
Web3 economics present a unique incentive mechanism which can be radically change the development of AI.
Brendan highlighted the importance of shared-economics in Decentralized AI, and how leading with economic opportunity has the ability to drive user adoption. Based on his upbringing, he knows the power of a few dollars to have an impact on people all over the world. By being able to share your bandwidth and receive economic benefit has the potential to change lives.
Decentralization also means more open, democratic access to critical resources in an AI economy, such as compute and data. Albert, Founder of Compute Labs, explained how they are leveraging blockchain to create financial products based on compute assets. “We’re using blockchain to provide transparency and security in the financialization of compute,” he said. “This approach not only makes compute resources more accessible but also ensures that transactions are secure and transparent.”
Brendan added how Masa is using blockchain to democratize access to data. How data is the lifeblood of AI. And that by leveraging blockchain, Masa is making it possible for anyone, anywhere to access the data they need to build AI. He shared, “By making data accessible to everyone, we’re enabling the development of fair, effective AI solutions.”
Illia summed it up succinctly and perfectly: “User-owned AI is the future. It’s about making AI work for the user, not just for corporate profits.”
The Decentralized AI Stack: Compute, Data, and Inference
With the AI sector of the crypto industry projected to reach $10.2 billion in revenue by 2030, according to a research report from VanEck, the potential of a decentralized AI world has attracted many bright minds who are building different parts of the decentralized AI stack.
Brendan shared Masa’s vision of building a decentralized AI network that democratizes access to data, allowing builders anywhere to access any data through Masa’s decentralized scraping network. By creating a seamless, decentralized ecosystem, data can be accessed and utilized by anyone, anywhere.
Albert articulated Compute Labs’ vision for the financialization of compute assets. “We’re focused on using AI to optimize compute assets,” he explained. Their goal is ambitious: to establish derivative markets for compute, thereby revolutionizing how these resources are traded and utilized.
Illia teased NEAR’s exciting AI product roadmap. “We are working on something we call the ‘AI Inference Router’, which is a way for many applications to actually plug in into this and get routed to whatever provides inference and compute.”
Real-World Applications of Decentralized AI
While decentralized AI is still in its early days, the panel was optimistic about its real-world applications. The practical applications of decentralized AI and data are set to change the way AI models and agents are trained forever.
Brendan detailed how Masa’s data scraping capabilities are unlocking new possibilities, referencing Masa’s innovative tool that bypasses expensive APIs to access data freely. This capability is crucial for developing AI models that require vast amounts of data. Meanwhile, users who contribute data get fairly rewarded.
“We’ve developed tools that allow users to scrape data from platforms like Twitter, Discord, and Telegram,” Brendan shared. “This capability is crucial for developing AI models that require vast amounts of data, enabling more accurate and effective AI solutions.”
Calanthia noted the rise of AI companions is a significant trend to watch. “Loneliness is a major issue among Millennials and Gen Z, and AI companions are emerging as a solution.” This trend is a testament to AI’s broader societal impact, offering innovative solutions to real-world problems affecting people beyond just technological advancement.
Albert discussed how Compute Labs is making strides in financializing compute assets. “We’re creating financial products that offer direct exposure to compute, much like how ETFs provide exposure to stocks,” he explained. This innovative approach aims to make compute resources more accessible and investable, unlocking new financial opportunities.
In Conclusion
The NEAR AI Office Hour broadcast showcased the transformative potential of decentralized AI. With builders like Masa, NEAR, and Compute Labs driving innovation, the future looks bright for a world where AI is not just a tool for corporations but a resource owned and leveraged by individuals worldwide.
As Brendan aptly put it, “We are building these different systems to fight for a future where AI benefits everyone, not just a select few.” As we move forward, the principles of user-owned AI and democratized data will undoubtedly play a crucial role in shaping the future of AI.
