Moore's Lobby · 18 Mar 2025 · 48m · Episode 3
KS Venkatraman, Nvidia's senior director of AI computing, discusses his journey from building radios with smuggled parts in India to leading AI adoption efforts at Nvidia. He details the transition from CPU architecture at Intel to GPU-based accelerated computing, explaining how hardware-software co-design and the availability of massive datasets fueled the AI revolution. Venkatraman emphasizes the critical need for AI literacy in education, advocating for infusing AI tools into K-12 and university curricula to solve complex problems like weather prediction and climate change.
Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.
Engineering & simulationAI models / agentic AIs
AI is used to generate test plans and test vectors for processor validation, helping to identify corner cases and bugs more effectively than manual methods.
“if you had the technology to be able to go generate the different kinds of tech effects … In the validation environment, AI can be immensely helpful, generating test plans and test vectors to do a high quality product in a short amount of time.”
Speaker 2 · Hear it at 38:11
Engineering & simulationEDA tools with AI
Electronic Design Automation tools use AI to remove repetitive tasks in circuit design, such as place and route algorithms, to improve engineer productivity.
“there is, uh, A lot of design tools, place and route algorithms, EDA tools that are starting to use AI. So, um, Removing anything that is repetitive in nature and it's going to make us a lot more productive…”
Speaker 2 · Hear it at 24:00
Engineering & simulationLanguage models
Engineers use language models to debug code snippets and generate test factors for corner cases, acting as a co-pilot for hardware description language verification.
“you can say, here's my piece of code and put paste a snippet in there and say, I'm worried about corner cases and what kind of test factors should I generate? So the tool can help you do that.”
Speaker 2 · Hear it at 26:51
Engineering & simulation$150,000,000,000 in climate-related fatalities over the past year
AI models are used to improve weather prediction accuracy by narrowing down national scale predictions to kilometer scale, mitigating costs associated with climate-related fatalities.
“with the help of AI models, we are able to narrow down the night scale weather predictions down to kilometer scale. So, um, that is incredibly helpful to find uh, micro climate events. And and it can save lives and be very accurate.”
Speaker 2 · Hear it at 38:11
large enterprises
Other shows on the same ground, closest first.
John Watson, Altium's technical engineer in education and a professor at Palomar Community College, discusses the integration of AI into PCB design education and the industry's shift toward cross-disciplinary mechatronics. He details a major partnership with Mouser to train one million students in India via an expanded Altium Education platform and highlights the critical need to address the 'massive sucking sound' of retiring PCB designers by training the next generation. Watson also previews his upcoming PCB West talk on Design for X (DFX), emphasizing how AI is transforming verification and design rules.
Vince Jesaitis, Head of Global Government Affairs at Arm, explains how AI is shifting from cloud-based inference to local edge processing on devices like smartphones, earbuds, and cars. He details Arm's strategy of providing efficient CPU building blocks that enable high performance-per-watt, addressing energy and water constraints in data centers while enhancing user privacy and security. Jesaitis also discusses the critical role of government relations, including workforce development initiatives, the US Chips Act, and navigating divergent global regulations like the EU AI Act and GDPR.
Jensen Huang, co-founder and CEO of NVIDIA, recounts the company's near-collapse in the mid-1990s following the catastrophic failure of the NV1 chip, which forced a strategic pivot to the Riva 128 and the development of CUDA. He explains how NVIDIA invested billions into the CUDA platform for general-purpose computing long before it found commercial viability, eventually enabling the AI revolution through gaming GPUs. Huang also discusses his leadership philosophy, his dismissal of AI extinction fears, and the personal sacrifices required to build the world's most valuable company.
Nandan Nayampally, CMO at BrainChip, discusses the evolution of AIoT and the shift of AI processing from the cloud to the edge. He explains how neuromorphic computing enables real-time, private, and efficient inference on billions of devices, citing PwC's $15 trillion GDP impact estimate. Nayampally highlights key adoption markets like healthcare, agriculture, and infrastructure, and advises companies to focus on solving acute pain points ('headaches') rather than nice-to-have features ('vitamins') to gain traction.
Hosts Chris Gammell and Dave Jones return to the podcast to discuss a wide range of topics, including Gammell's new Contextual Electronics course and Jones's hiring of a full-time employee. They analyze the rising costs of engineering education, the technical details of Nvidia's new Volta GPU for AI, and the shift in robotics from reverse kinematics to visual feedback. The conversation also covers the sale of the MIPS architecture, the success of RISC-V startup SiFive, and upcoming events like Maker Faire.
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