The 80-Year Bet: Why Naveen Rao Is Rebuilding the Computer from Scratch
Naveen Rao is cofounder and CEO of Unconventional AI, an AI chip startup building analog computing systems designed specifically for intelligence. Previously, Naveen led AI at Databricks and founded two successful companies: Mosaic (cloud computing) and Nervana (AI accelerators, acquired by Intel).
In this episode, a16z’s Matt Bornstein sits down with Naveen at NeurIPS to discuss why 80 years of digital computing may be the wrong substrate for AI, how the brain runs on 20 watts while data centers consume 4% of the US energy grid, the physics of causality and what it might mean for AGI, and why now is the moment to take this unconventional bet.
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Databricks VP: Don’t Try to Speed AI Evolution through Brute Force
In the latest episode ofThe New Stack Agents, Naveen Rao, VP of AI at Databricks and a former neuroscientist, reflects on the evolution of AI, neural networks, and the energy constraints that define both biological and artificial intelligence. Rao, who once built circuit systems as a child and later studied the brain’s 20-watt efficiency at Duke and Brown, argues that current AI development—relying on massive energy-intensive data centers—is unsustainable. He believes true intelligence should emerge from low-power, efficient systems, more aligned with biological computing.
Rao warns that the industry is headed toward “model collapse,” where large language models (LLMs) begin training on AI-generated content instead of real-world data, leading to compounding inaccuracies and hallucinations. He stresses the importance of grounding AI in reality and moving beyond brute-force scaling. Rao sees intelligence not just as a function of computing power, but as a distributed, observational system—“life is a learning machine,” he says—hinting at a need to fundamentally rethink how we build AI.
Learn more from The New Stack about the latest insights about the evolution of AI and neural networks:
The 50-Year Story of the Rise, Fall, and Rebirth of Neural Networks
The Evolution of the AI Stack: From Foundation to Agents
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Highlighting Data Intelligence with Databricks & Bonbon’s Reward Innovation | E2020
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(0:00) Databricks’ Naveen Rao joins Alex Wilhelm
(8:54) Regulatory challenges and open-source AI
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(13:57) Meta's Llama models and reinforcement learning
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(20:55) Open vs. closed source AI models and advances
(28:09) Precision in AI and enterprise applications
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(52:08) Tech incumbents' evolution and AI competition
(54:55) AI model sizes and synthetic data quality
(57:29) AI inspiration from biology and future innovation
(1:03:06) Databricks' growth trajectory and potential IPO
(1:04:25) Elliot Easterling of bonbon joins TWIST for a Jam with JCal.
(1:05:16) Bonbon.tech and the rewards platform overview
(1:14:44) Gamification strategies and user engagement
(1:22:18) Exploring growth opportunities and market expansion
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Link to Newsom vetoes SB 1047 article: https://www.bbc.com/news/articles/cj9jwyr3kgeo
The short guide to understanding data intelligence from Databricks: https://www.databricks.com/blog/short-guide-understanding-data-intelligence
Mosaic AI Agent Framework post: https://www.databricks.com/blog/announcing-mosaic-ai-agent-framework-and-agent-evaluation
Data Intelligence Platform product tour: https://www.databricks.com/resources/demos/tours/horizontal/introducing-databricks-intelligence-platform?itm_data=demo_center
Mosaic AI new features and demo: https://www.youtube.com/watch?v=acIBdCOj88E
Unity Catalog GitHub: https://github.com/unitycatalog/unitycatalog
“Thinking Fast and Slow” by Daniel Kahneman summary on Medium - https://www.penguinrandomhouse.ca/books/89308/thinking-fast-and-slow-by-daniel-kahneman/9780385676533
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MosaicML's Naveen Rao on Making Custom LLMs More Accessible - Ep. 199
Startup MosaicML is on a mission to help the AI community enhance prediction accuracy, decrease costs, and save time by providing tools for easy training and deployment of large AI models.
In this episode of NVIDIA's AI Podcast, host Noah Kravitz speaks with MosaicML CEO and co-founder Naveen Rao, about how the company aims to democratize access to large language models.
MosaicML, a member of NVIDIA's Inception program, has identified two key barriers to widespread adoption: the difficulty of coordinating a large number of GPUs to train a model and the costs associated with this process.
Making training of models accessible is key for many companies who need to control over model behavior, respect data privacy, and iterate fast to develop new products based on AI.
How open-source & distributed models can win AI with MosaicML’s Naveen Rao | E1754
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Todays show:
MosaicML Co-Founder and CEO Naveen Rao joins Jason to discuss the open-source vs closed AI debate, the profound impact of AI on society (41:06) AI’s rapid pace of change, and its implications for the future of employment and education (40:42). They wrap the show by breaking down the potential problems with centralized regulation (54:37).
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(2:54) MosaicML and its purpose
(5:10) Obtaining datasets and incentivizing creators
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(9:37) The process of using your data with MosaicML
(11:55) Defining tokens and prompts
(16:53) Fine-tuning the AI model and reinforcement learning
(19:27) The competition with open-source models
(24:26) The cost of running AI models
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(27:35) How the GPU crunch has affected cloud models
(32:13) Why demand will not cease
(34:21) Specialized models vs. general models
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(40:42) The impact AI will have on employment
(48:49) The impact AI will have on education
(54:37) Thoughts on OpenAI becoming ClosedAI
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Intel Nervana Devcloud with Naveen Rao & Scott Apeland - TWiML Talk #51
In this episode, I talk to Naveen Rao, VP and GM of Intel’s AI Products Group, and Scott Apeland, director of Intel’s Developer Network. It's been a few months since we last spoke to Naveen, so he gives us a quick update on what Intel’s been up to and we discuss his perspective on some recent developments in the AI ecosystem. Scott and I dig into Intel Nervana’s new DevCloud offering, which was announced at the conference. We also discuss the Intel Nervana AI Academy, a new portal offering hands-on learning tools and other resources for various aspects of machine learning and AI. The notes for this show can be found at twimlai.com/talk/51
Intel Nervana Update + Productizing AI Research with Naveen Rao And Hanlin Tang - TWiML Talk #31
I talked about Intel’s acquisition of Nervana Systems on the podcast when it happened almost a year ago, so I was super excited to have an opportunity to sit down with Nervana co-founder Naveen Rao, who now leads Intel’s newly formed AI Products Group, for the first show in our O'Reilly AI series. We talked about how Intel plans to extend its leadership position in general purpose compute into the AI realm by delivering silicon designed specifically for AI, end-to-end solutions including the cloud, enterprise data center, and the edge; and tools that let customers quickly productize and scale AI-based solutions. I also spoke with Hanlin Tang, an algorithms engineer at Intel’s AIPG, about two tools announced at the conference: version 2.0 of Intel Nervana’s deep learning framework Neon and Nervana Graph, a new toolset for expressing and running deep learning applications as framework and hardware-independent computational graphs. Nervana Graph in particular sounds like a very interesting project, not to mention a smart move for Intel, and I’d encourage folks to take a look at their Github repo. The show notes for this page can be found at https://twimlai.com/talk/31