The Good Tech Companies - How Kite AI is Building the Foundation Layer for Global AI Development
Episode Date: December 13, 2024This story was originally published on HackerNoon at: https://hackernoon.com/how-kite-ai-is-building-the-foundation-layer-for-global-ai-development. Kite AI is building ...what they call the "coordination layer" for AI development. Founder Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #kiteai-news, #kiteai, #kiteai-interview, #ai, #automation, #good-company, #web3, #decentralization, and more. This story was written by: @ishanpandey. Learn more about this writer by checking @ishanpandey's about page, and for more stories, please visit hackernoon.com. Kite AI is building what they call the "coordination layer" for AI development. Founder Chi Zhang worked on big data at Databricks and AI automation at dotData. Zhang: "The intersection of big data and AI will move toward seamless, real-time systems powered by a decentralized infrastructure"
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How Kite AI is building the foundation layer for global AI development, by Ashan Pandey.
In an era where artificial intelligence is reshaping industries at breakneck speed,
few companies are tackling the fundamental infrastructure challenges that could either
accelerate or bottleneck AI's global adoption. Kite AI, led by former professional speedskater turned tech innovator
Kai Zhang, which is building what they call the coordination layer for AI development.
In this exclusive interview, Zhang shares how his unique journey from sports to tech influenced his
vision for democratizing AI resources and ensuring fair attribution in the rapidly evolving AI
landscape. Ashant Pandey. Hi Kai Zhang. It's a pleasure to
welcome you to our Behind the Startup series. Please tell us about yourself and what inspired
you to create Zeta Block and Kite AI. Kai Zhang. Thank you, Ashan. It's great to be here.
My journey started at the intersection of big data and AI, working on scalable infrastructure
at Databricks and advancing ai automation at dot
data these experiences gave me afferent row seat to both the immense possibilities and the
bottlenecks in leveraging data and ai at scale zeta block was born out of a need to bring
transparency reliability and accessibility to blockchain data we built zeta block as a scalable
developer first solution that addresses the
complexity of working with blockchain and AI datasets, making them more usable and actionable.
While ZetaBlock focused on empowering developers and businesses with tools for data infrastructure,
we recognized an even broader challenge, the lack of fair and open access to essential AI
resources like data, models, and agents. This realization led to Kite AI.
Kite AI takes Zetablock's expertise in infrastructure and expands it into the AI
space by building the coordination layer for global AI development.
Our goal is to democratize access to AI resources while ensuring contributors,
whether data providers, model developers, or end-users, are fairly attributed and rewarded.
Kite AI isn't just a platform, it's a foundational layer that fosters collaboration and drives the next wave of AI innovation. Ashant Pandey. Could you elaborate on what it means to build the
foundation layer for AI and how this layer impacts the broader AI ecosystem? Kai Zhang.
Building the foundation layer for AI is about establishing the essential
infrastructure that powers the global AI economy, just as the internet provided a foundational layer
for the digital age. At Kite AI, this means creating a coordination layer that connects data,
models, and agents in a centralized and transparent way, ensuring all participants can share,
contribute, and monetize AI resources
fairly. This coordination layer solves two major challenges. Fragmentation. The AI ecosystem today
is siloed, with resources scattered across platforms, institutions, and private entities.
Kite AI provides a unifying framework for collaboration. Fair attribution. Contributors
often lack mechanisms to receive
credit or compensation for their work. By embedding transparent attribution and reward systems,
Kite AI ensures fairness and incentivizes innovation. In essence, this foundation layer
creates a shared infrastructure that enables the broader AI ecosystem to thrive by lowering
barriers and fostering collaboration. Ashant Pandey. With your experience in big data at Databricks and AI automation at.data,
how do you see the intersection of these fields evolving in the next decade?
Kai Zhang. The intersection of big data and AI will move towards seamless,
real-time systems powered by a decentralized infrastructure.
In the past, the focus was on collecting and processing massive
datasets. Now, it's shifting to curating, sharing, and utilizing these datasets collaboratively.
AI automation, including AutoML, will play a critical role in making these processes more
accessible to a wider audience. Kite AI is positioned at this intersection, building the
coordination layer that enables these systems to operate transparently and collaboratively. In the next decade, we foresee an ecosystem where
AI and big data are no longer confined to individual organizations but are part of a shared,
decentralized infrastructure that drives innovation globally.
Ashan Pandey. How do you view the role of AutoML in democratizing AI and empowering
non-technical users?
Kai Zhang. AutoML is a transformative technology that simplifies the complexities of AI development,
enabling non-technical users to create and deploy models. However, its effectiveness depends on access to high-quality, diverse datasets, something that is often limited today.
This is where Kite AI comes in. By providing a
decentralized coordination layer, we facilitate access to a broader pool of AI resources,
including data and models. This not only empowers non-technical users but also enables AutoML tools
to deliver more accurate and inclusive outcomes. Ashant Pandey. How does Kite AI ensure fairness
and inclusivity in access to AI assets,
and what ethical considerations guide your work?
Kai Zhang. Fairness and inclusivity are at the core of Kite AI's mission.
Oort's centralized architecture ensures that everyone, whether a data provider,
developer, or user, has access to AI resources and is fairly rewarded for their contributions.
The coordination layer we've built ensures that attribution is transparent and automated, reducing the potential for
exploitation or bias. Ethically, we prioritize transparency, privacy, and accountability.
For example, our systems allow contributors to define how their data or models are used,
ensuring that they retain control over their intellectual property.
By embedding these
principles into our design, we aim to set a new standard for fairness and inclusivity in the AI
ecosystem. Ashon Pondi. How has mentoring early stage founders at StartX influenced your leadership
style and the way you approach building startups like Kite AI? Kai Zhang. Mentoring founders at
StartX taught me the importance of adaptability, empathy, and clarity of vision. Every founder brings unique challenges and perspectives,
and understanding their needs helped me refine my approach to problem-solving and leadership.
At Kite AI, I apply these lessons by fostering a culture of ownership and collaboration.
Our team operates with a shared vision, but everyone has the freedom to innovate within
their domain. This balance of structure and creativity is something I've carried forward
from my time at Stardex. Ashant Pandey. With increasing global focus on AI regulation,
how is Kite AI preparing to navigate compliance while ensuring innovation,
and what role do you think regulatory frameworks should play in shaping the future of AI?
Kai Zhang. AI regulation is both a challenge and an opportunity. While it's essential to
protect users and ensure ethical practices, overly restrictive frameworks can stifle innovation.
At Kite AI, our decentralized and transparent coordination layer is designed to align with
global compliance standards while fostering open collaboration. We believe regulatory
frameworks should focus on promoting transparency, accountability, and inclusivity. By creating
environments where innovation can flourish within ethical boundaries, we can unlock AI's full
potential without compromising on safety or fairness. Ashan Pandey. In your opinion, how will
AI continue to reshape industries in the next five years,
and what specific role do you envision Kite AI playing in this transformation?
Kai Zhang. AI will transform industries by automating processes,
enabling smarter decision-making, and personalizing user experiences.
In the next five years, we'll see more industries leveraging AI not just for efficiency but also for
entirely new business models, from AI-driven marketplaces to autonomous systems. Kite AI will play a pivotal role as the
coordination layer that democratizes access to AI tools and resources, making this transformation
accessible to a wider range of participants. By providing the foundation for fair and
transparent collaboration, we aim to accelerate the adoption and impact of
AI across industries. Ashon Pondy, you have a unique background as a professional inline
speedskater. How did this experience shape your leadership style or influence your approach to
building a tech startup like Kite AI? Kai Zhang, speedskating taught me the value of discipline,
precision, and resilience. In racing, success depends on
preparation, strategy, and the ability to adapt to changing conditions, qualities that are equally
important in building a startup. At Kite.ai, I've carried these lessons forward by fostering a team
culture that emphasizes adaptability and long-term vision. Like in skating, building a successful
company isn't just about speed, it's about endurance, focus, and the ability to navigate challenges with confidence.
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