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AI Progress Is More Complex Than It Seems, Exabits Is Helping Researchers Break New Ground

AI isn’t going anywhere anytime soon. Just this past week, NVIDIA reported that its revenues had doubled in Q3, reinforcing its position as a leader in manufacturing AI chips and continuing the dominance of AI across the tech and business landscape.

That being said, while the building blocks fundamental for the AI era to proliferate are going strong, research-fuelled progress is a little more precarious.

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It’s no secret that developing AI is an expensive endeavor. It requires countless hours of research, testing, and computational strength to build an even usable model. Of course, the rise of consumer-ready Large Language Models (LLMs) like GPT or Claude has created a good baseline for AI researchers to continue from, but it’s still not so simple. Likewise, the needs of AI researchers in fields like automotive or other large-scale applications need something a little stronger to power their research and testing.

Aside from more complex models, cutting-edge AI research also requires a massive amount of compute—the umbrella term for all the resources needed for AI systems to perform tasks, process data, train models, and make predictions. Compute is the lifeblood behind AI and is a big driver behind the massive growth NVIDIA and other chip manufacturers have experienced in the past few years.

However, compute is expensive. And despite the AI boom, it’s not so readily available to researchers who need it to push the boundaries of the technology.

To help provide leading AI research institutes with the computational power they need, Exabits, a compute-base layer platform transforming high-end GPU clusters into accessible investment assets, has continuously dedicated a portion of its platform to fuelling academic innovation. To date, Exabits has collaborated with Harvard University, Stanford University, and University of California, Berkeley to provide computational power to researchers at the cutting edge of AI progress.

Recently, Exabits expanded internationally to continue its line of academic collaboration, partnering with Seoul National University, South Korea’s leading research university. More specifically, Exabits is providing computation power to the university’s Intelligent Vehicle Research Team, a group dedicated to advancing autonomous driving capabilities.

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Led by Professor Seungwoo Seo, the Intelligent Vehicle Research Team will utilize Exabits’s compute power throughout its research and trial periods. By gaining access to compute critical to conducting experiments, the team can test out new technologies that will help advance the autonomous driving sector—an industry projected to reach $400 billion in revenue by 2035, according to McKinsey.

Dr. Hoansoo Lee, Co-Founder of Exabits, shared this about the collaboration: “Partnering with leading research institutions like those at Seoul National University are core tenets of our company’s goals and ambitions. Exabits is in championing innovation through rigorous research, so we’re proud to provide our technology and computational power to Professor Seo and the incredible Intelligent Vehicle Research Team.”

Through its academic collaborations around the world, Exabits highlights how private AI companies can lend a hand to advancing AI research across multiple emerging sectors. Not only does it help drive innovation, it puts companies at the forefront of the technology that makes their operations successful. It also emphasizes the importance of innovative research to transcend borders.

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Thanks to the support from Exabits, the team at Seoul National University can continue its research without fearing limits in computational power or strains in resource allocation. This enables the team to lead the charge in breaking new ground in autonomous driving technology.

These kinds of collaborations aren’t a one-off for Exabits either, as its team is also comprised of academic leaders and researchers from venerable academic institutions. As Exabits continues its commercial partnerships and develops its compute financialization products, its team also aims to continue contributing to the academic and research realm.

It’s easy for investors who got in early on the AI wave to celebrate their wins now. But to ensure the future of this transformative technological sector, initiatives like academic and research collaborations are fundamental to continue the push towards progress and sustainable growth.

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