Imagine a future where AI transforms not just customer service but the very core of industries like healthcare, defense, and automotive manufacturing. In this CNBC Money Movers segment, SandboxAQ CEO Jack Hidary discusses the evolving role of AI, including how Large Quantitative Models (LQMs) are reshaping product development and innovation.
Jack highlights why the U.S. is likely to take a light regulatory stance on AI, focusing on transparency and disclosure to avoid misuse while encouraging widespread adoption. He emphasizes that the biggest danger isn’t runaway AI—it’s underutilized AI. From developing new drugs to creating lightweight materials for cars and aerospace, AI has the potential to solve society’s biggest challenges.
This conversation also explores the critical shift from Large Language Models (LLMs) to Large Quantitative Models —AI systems capable of advancing core product development in biopharma, materials science, and beyond. Jack discusses global trends in AI adoption, including initiatives in the Gulf region and the growing demand for sovereign data centers.
If you’re interested in the future of AI policy, innovation, and its real-world applications, tune in now to hear Jack’s insights.
Learn more about SandboxAQ’s groundbreaking work in AI:
date 2024-11-24 23:02:03
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How LQMs (quantitative AI) are transforming industries beyond LLMs | Jack Hidary on CNBC
In a recent interview on CNBC, Jack Hidary, CEO of SandboxAQ, discussed the future of AI and its applications in various industries. Hidary emphasized the importance of transparency and disclosure in the development and implementation of AI technologies, particularly in sectors like defense, healthcare, and finance.
He highlighted the need for a shift from large language models (LLMs) to large quantities models (LQMs), which can create new products and drive innovation. LQMs have the potential to transform industries beyond language processing, such as medicine, materials science, and automotive.
Hidary also discussed the importance of sovereign entities, like countries, adopting AI technologies to build their own data centers and drive innovation. He cited examples of countries like Japan and the United Arab Emirates making significant investments in AI.
The CEO also touched on the concept of a "wall" in scaling AI, where companies struggle to differentiate themselves due to the abundance of language data. He believes that the next big leap in AI will come from numerical data, which can be obtained from sensors, engineering, and equations.
SandboxAQ, a company that focuses on quantitative AI, has been working with chip companies like Nvidia to develop new use cases for their technology. Hidary believes that Nvidia’s Cuda software is a key differentiator and that the company’s focus on software will be critical to its success.
Overall, the interview highlights the potential of LQMs to transform industries and drive innovation, as well as the importance of transparency, disclosure, and sovereign adoption of AI technologies.
