The intersection of artificial intelligence and decentralized technologies has emerged as one of the most transformative frontiers in modern technology.
As AI continues to reshape industries and challenge traditional computational paradigms, innovative approaches to infrastructure, data management, and computational resources are becoming increasingly critical.
Decentralized AI represents a promising pathway to democratize access to advanced computational capabilities, addressing challenges of cost, scalability, and data privacy that have long constrained technological innovation.
At the forefront of this technological revolution is Dr. Max Li, a visionary researcher and entrepreneur who has been pioneering groundbreaking solutions in the decentralized AI landscape.
In this exclusive interview, Dr. Li will share his unique insights, revealing the intricate dynamics and potential of this emerging technological domain.
Invezz: Tell us about yourself and your background.
I have a background in Electrical and Computer Engineering and began my career working in Qualcomm’s R&D department, focusing on the development of 5G chipsets.
For this interview, I’d like to share the serendipitous encounters that led me to the blockchain industry and where I am today.
It all started in 2012 during Qualcomm research department’s weekly “Free Thinking Hour” on Fridays—a time set aside for brainstorming and exploring innovative ideas.
On one of these Fridays, a colleague introduced the topic of Bitcoin and blockchain technology.
They explained the concept of Proof of Work (PoW) and the underlying infrastructure. Intrigued, our group of researchers delved into the technological details and algorithms, and decided it was some lousy tech that was going nowhere.
Then, we forgot about it and I did not have any interest in blockchain and crypto. Back then, BTC was around $10.
Fast forward to 2017: the 2nd year of my time at Columbia University as a faculty member, teaching classes in engineering and computer science. Outside the academic sphere, the ICO boom was in full swing.
At Columbia, we began receiving an overwhelming number of student inquiries and requests for a course on blockchain and cryptocurrency. Such a course with university credits didn’t exist anywhere in the United States at that time.
I was tasked with creating this course from scratch—there was no syllabus, no materials, and no roadmap. To prepare, I pieced together knowledge from scattered online resources and deepened my understanding of the subject.
That same year, Columbia’s first blockchain course was launched, one of the earliest of its kind in the US, alongside similar courses being introduced at Duke and Princeton.
Invezz: Walk us through your personal journey of starting OORT. How did it begin and why?
It all began with more serendipity.
The idea for the decentralized AI platform “OORT” emerged during an AI course I taught in 2018.
Columbia postgraduates were struggling to complete a project that required training AI agents because traditional cloud services, like those offered by Amazon and Google, were far too expensive for student budgets.
This prompted us to explore leveraging blockchain as an incentive layer to create a more cost-effective decentralized cloud solution.
What we did was utilize underutilized nodes globally and connect them through blockchain. Students could then access these resources and pay via PayPal, with a certain amount of credits allocated for student use.
These credits became the “embryo” of what would later evolve into OORT’s native token.
While this sounded exciting, it came with significant technological challenges.
The concept was entirely new, and we were navigating uncharted territory, exploring and solving problems bit by bit.
By the way, the course I’m referring to is Reinforcement Learning in AI. It’s based on the textbook I authored, Reinforcement Learning for Cyber-Physical Systems, published by Taylor & Francis CRC Press.
Along the way, I published a few academic papers and US patents, for example, the development of the Proof of Honesty (PoH) system that OORT DataHub relies on. PoH is a human-in-the-loop auto-quality control mechanism.
This system ensures immediate verification of the accuracy of collected data points, unlike traditional companies that take time to manually verify results, often missing errors.
Invezz: OORT received a grant from Microsoft, can you give us more information about this? How did OORT stand out?
The grant from Microsoft significantly supports our efforts in developing decentralized AI infrastructure. It also represents a mutually beneficial partnership.
OORT stood out because our model is both practical and scalable.
While there is a lot of hype and narratives around decentralized AI (DeAI), many are not practical for business use.
This is where OORT has a strong advantage—we are a for-profit business with real-world solutions that deliver tangible results.
Our solutions, such as OORT Storage and OORT AI, have already been adopted by over 10,000 clients, demonstrating their applicability and demand.
Additionally, our ability to deliver viable products at scale played a key role in being selected for this grant.
As a startup, gaining access to critical resources is essential for scaling our infrastructure.
For example, through this grant, OORT receives free Azure server access to run key components of our infrastructure, which significantly enhances our operational capacity. In addition, we receive OpenAI technical support for our AI agent development.
Invezz: OORT recently signed a 3-year contract with Githon Technology for customized AI solutions. Could you share insights on what this partnership means, and how it aligns with your vision of integrating AI into how we do business?
The partnership with Githon Technology (formerly Lenovo Image) is an important milestone for OORT and the decentralized AI space.
It highlights the growing demand for practical AI solutions in the Customer Support vertical—a vast market with significant untapped potential.
Through this collaboration, we aim to pilot and implement a proof of concept that demonstrates how decentralized AI can enhance customer support operations with greater efficiency, privacy, and scalability.
This partnership also validates OORT’s business viability, scalability, and the operational efficiency our solutions bring to clients.
These qualities not only benefit Githon Technology but also set a standard for the broader industry, showcasing the real-world applicability of AI in business settings.
For OORT, this partnership is a significant step toward integrating decentralized AI into core business processes in a way that is both impactful and scalable.
It opens the door for future innovations while building a strong pipeline of opportunities in the customer support space and beyond.
Invezz: We’ve seen a surge in funding for decentralized AI startups. How do you see this funding trend shaping the landscape of AI innovation, particularly in areas like infrastructure?
The increase in funding for decentralized AI startups is exciting, but it also comes with challenges.
One common issue is that many projects tend to chase hype rather than focus on solving real-world problems.
This is something we’ve observed in other tech trends as well, such as drones, VR glasses, or purely feature-driven innovations.
While the technology in these fields has advanced significantly, the critical question remains: What’s the business model? How does this generate sustainable revenue?
In the decentralized AI space, we see a similar dynamic.
The Web3 ecosystem often leans into hype and hot-money funding, while Web2 tends to focus on serious, business-driven strategies.
For decentralized AI to truly shape the landscape of innovation, startups need to adopt a more thoughtful and practical approach—one that prioritizes problem-solving over buzzwords.
At OORT, we continually ask ourselves how our solutions can address real market needs.
This mindset ensures that we build scalable infrastructure and applications that are not just technologically innovative but also commercially viable.
Looking ahead, we hope to see more startups applying this approach, focusing on creating value through practical and sustainable use cases rather than simply riding the wave of hype.
Invezz: The crypto industry has shown growing interest in combining crypto and AI, with examples like Bitcoin miners repurposing rigs for AI tasks. How do you view this intersection, and do you see a viable pathway for profitable collaboration between these sectors?
The intersection of crypto and AI presents significant potential for innovation and new business models.
However, as I recently discussed in my Forbes column, while the pathway is promising, we should expect a fair share of failures in the near term as the sector experiences rapid growth and experimentation.
The convergence of crypto and AI could indeed unlock possibilities for an unimaginable future.
But the key question remains: “Where’s the real business?”
For example, in decentralized AI (DeAI) cloud computing, success will depend less on the cost savings or access to massive processing power (which are the pitch points of most DeAI projects) and, instead, more on factors like the service reliability, scalability, and addressing real-world concerns that some are currently overlooking.
For instance, rigs from the repurposed Bitcoin mining machines always have reliability and scalability concerns.
At OORT, we’re committed to building solutions that address these practical needs. With OORT Storage and OORT DataHub, we’ve already established integral components for decentralized AI use cases.
Soon, we’ll launch OORT Compute, which will further position us as a viable and competitive alternative to traditional Web2 cloud providers.
This comprehensive approach not only supports the promise of DeAI but also ensures a sustainable and profitable trajectory for the sector.
I’m genuinely excited about this direction, as it highlights the importance of focusing on meaningful applications and long-term value creation rather than simply riding the wave of hype.
By addressing real business needs, the crypto-AI intersection can achieve its true potential.
Invezz: As someone deeply involved in the decentralized AI space, where do you see the industry heading in the next five years? What role do you envision OORT playing in shaping the future of AI through decentralized networks?
Let’s approach this from two perspectives.
1. AI as a Technology
AI is set to enjoy significant longevity over the next five to 20 years. Much like smartphones, which have evolved over nearly a decade, AI will continue to advance, introducing new capabilities and features.
While it may not always be on the cutting edge of public attention, it will remain a vibrant and integral part of technology and innovation.
The longer the timeline, the more powerful and autonomous AI systems—such as advanced AI agents—we can expect to see.
2. Decentralized AI (DeAI)
The future of DeAI is less certain, particularly when viewed over a 20-year horizon. Many factors could influence its trajectory, including technological advancements, evolving regulations, and geopolitical considerations.
For instance, the challenge of managing truly global datasets that cross jurisdictions raises national security concerns and regulatory complexities.
In five years, DeAI could either solidify its position or fade into the background as a passing trend. However, AI itself will undoubtedly persist and continue to shape industries.
At OORT, we embrace the uncertainties of this space with excitement and determination. Navigating the DeAI landscape is like embarking on a grand voyage—there are unknowns, but the potential rewards are immense.
As a first mover in this sector, OORT has a unique opportunity to lead the way.
With solutions like OORT Storage, OORT DataHub, and the soon-to-be-launched OORT Compute, we aim to build the foundational infrastructure for decentralized AI, addressing real-world challenges and creating a viable path forward.
While the journey ahead may be unpredictable, we’re committed to pushing the boundaries of what decentralized AI can achieve and shaping the future of AI through decentralized networks.
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