Large Numerical Models - The Next Intelligence with Sriya.AI
Wed Feb 04 2026
How Large Numerical Models Are Redefining the Future of AI Analytics
“The future is a combination of an LLM and an LNM.” – Dr. Srinivas Kalimbi
Most AI conversations today focus on large language models. However, language alone is not enough.
In this episode of the Rebellious Times Podcast, host Chris Januszewski sits down with Srinivas Kilambi, CEO of Sriya.AI, to explore a powerful but under-discussed frontier in artificial intelligence: Large Numerical Models (LNMs).
Srinivas brings a rare perspective. He combines deep academic rigor with real-world startup experience. Over his career, he has built and exited multiple companies across AI, finance, and green technology. As a result, his view of AI is grounded in both theory and execution.
Why Numbers Still Break AI
Large language models are impressive. They write, summarize, and converse well. However, they often struggle with numbers. In many business scenarios, that limitation becomes costly. During the conversation, Srinivas explains why structured numerical data behaves differently from text. He then introduces LNMs as a parallel AI system. These models focus on prediction, optimization, and accuracy rather than language generation. Because of this, LNMs can deliver far lower error rates. They are also better suited for finance, operations, and analytics.
AI, Sustainability, and Green Technology
Beyond AI, Srinivas shares his work in green technology. He highlights how industrial processes, including cement production, contribute heavily to climate change. More importantly, he explains how technology can reduce emissions without sacrificing growth. This blend of sustainability and AI makes Sriya.AI especially relevant. It shows how advanced models can drive both profit and impact.
What This Means for the Future of AI
Looking ahead, Srinivas believes the future is not LLM or LNM. Instead, it is both. By combining language models with numerical models, businesses can reason, predict, and explain outcomes with confidence. That shift could unlock a new wave of AI adoption across industries. For founders, operators, and curious learners, this episode offers a clear takeaway: understanding numbers still matters. And AI is finally catching up.
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How Large Numerical Models Are Redefining the Future of AI Analytics “The future is a combination of an LLM and an LNM.” – Dr. Srinivas Kalimbi Most AI conversations today focus on large language models. However, language alone is not enough. In this episode of the Rebellious Times Podcast, host Chris Januszewski sits down with Srinivas Kilambi, CEO of Sriya.AI, to explore a powerful but under-discussed frontier in artificial intelligence: Large Numerical Models (LNMs). Srinivas brings a rare perspective. He combines deep academic rigor with real-world startup experience. Over his career, he has built and exited multiple companies across AI, finance, and green technology. As a result, his view of AI is grounded in both theory and execution. Why Numbers Still Break AI Large language models are impressive. They write, summarize, and converse well. However, they often struggle with numbers. In many business scenarios, that limitation becomes costly. During the conversation, Srinivas explains why structured numerical data behaves differently from text. He then introduces LNMs as a parallel AI system. These models focus on prediction, optimization, and accuracy rather than language generation. Because of this, LNMs can deliver far lower error rates. They are also better suited for finance, operations, and analytics. AI, Sustainability, and Green Technology Beyond AI, Srinivas shares his work in green technology. He highlights how industrial processes, including cement production, contribute heavily to climate change. More importantly, he explains how technology can reduce emissions without sacrificing growth. This blend of sustainability and AI makes Sriya.AI especially relevant. It shows how advanced models can drive both profit and impact. What This Means for the Future of AI Looking ahead, Srinivas believes the future is not LLM or LNM. Instead, it is both. By combining language models with numerical models, businesses can reason, predict, and explain outcomes with confidence. That shift could unlock a new wave of AI adoption across industries. For founders, operators, and curious learners, this episode offers a clear takeaway: understanding numbers still matters. And AI is finally catching up. Sriya.AI links: sriya.ai LinkedIn