ThirdAI raises $6M to democratize AI to any hardware

Houston-based ThirdAI, a company building tools to speed up deep learning technology without the need for specialized hardware like graphics processing units, brought in $6 million in seed funding.

Neotribe Ventures, Cervin Ventures and Firebolt Ventures co-led the investment, which will be used to hire additional employees and invest in computing resources, Anshumali Shrivastava, Third AI co-founder and CEO, told TechCrunch.

Shrivastava, who has a mathematics background, was always interested in artificial intelligence and machine learning, especially rethinking how AI could be developed in a more efficient manner. It was when he was at Rice University that he looked into how to make that work for deep learning. He started ThirdAI in April with some Rice graduate students.

ThirdAI’s technology is designed to be “a smarter approach to deep learning,” using its algorithm and software innovations to make general-purpose central processing units (CPU) faster than graphics processing units for training large neural networks, Shrivastava said. Companies abandoned CPUs years ago in favor of graphics processing units that could more quickly render high-resolution images and video concurrently. The downside is that there is not much memory in graphics processing units, and users often hit a bottleneck while trying to develop AI, he added.

“When we looked at the landscape of deep learning, we saw that much of the technology was from the 1980s, and a majority of the market, some 80%, were using graphics processing units, but were investing in expensive hardware and expensive engineers and then waiting for the magic of AI to happen,” he said.

He and his team looked at how AI was likely to be developed in the future and wanted to create a cost-saving alternative to graphics processing units. Their algorithm, “sub-linear deep learning engine,” instead uses CPUs that don’t require specialized acceleration hardware.

Swaroop “Kittu” Kolluri, founder and managing partner at Neotribe, said this type of technology is still early. Current methods are laborious, expensive and slow, and for example, if a company is running language models that require more memory, it will run into problems, he added.

“That’s where ThirdAI comes in, where you can have your cake and eat it, too,” Kolluri said. “It is also why we wanted to invest. It is not just the computing, but the memory, and ThirdAI will enable anyone to do it, which is going to be a game changer. As technology around deep learning starts to get more sophisticated, there is no limit to what is possible.”

AI is already at a stage where it has the capability to solve some of the hardest problems, like those in healthcare and seismic processing, but he notes there is also a question about climate implications of running AI models.

“Training deep learning models can be more expensive than having five cars in a lifetime,” Shrivastava said. “As we move on to scale AI, we need to think about those.”


By Christine Hall

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