The Evolution of AI in IoT | BrainChip's Nandan Nayampally | Internet of Things Podcast

IoT For All Podcast · 13 Apr 2023 · 19m

What this episode covers

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.

Other shows on the same ground, closest first.

  • The Next Byte Podcast · 46m

    235. Arm’s Vince Jesaitis on How AI Is Moving from the Cloud to Your Pocket

    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.

  • EE Times Current · 45m

    From Data Centers to Devices – The Ongoing [R]Evolution of AI Computing

    Matt Gutierrez, Senior Director of Marketing at Synopsys, discusses the migration of AI computing from centralized data centers to the network edge. He explains that this shift is driven by the need for low latency, data privacy, and power efficiency, enabled by smaller neural networks and specialized hardware like NPUs and TPUs. Gutierrez details how Synopsys supports this through its ARC processor IP portfolio and EDA tools, helping engineers manage the complexity of heterogeneous processing platforms for edge devices.

  • The Circuit · 34m

    Episode 26: A Thesis on AI's Impact on Semi Segments

    Ben Bajarin and Jay Goldberg discuss Jay's thesis on how AI impacts various semiconductor segments, focusing on the shift from training to inference and the competitive landscape. They analyze NVIDIA's dominance in training via CUDA and its 'accelerated computing' stack, while arguing that inference will become the majority of spend, driving growth in edge devices like PCs and phones. The hosts conclude that AI is additive to the total addressable market (TAM) for semiconductors, driven by new data center capacity and on-device processing, rather than simply cannibalizing existing CPU sales.

  • EE Times Current · 49m

    Can the Nvidia Monopoly on AI Chips Be Broken?

    Sally Ward-Foxton of EE Times discusses the AI chip market with hosts Dr. Sunny Bains and Dr. Giulia D’Angelo, analyzing the dominance of Nvidia and the potential for neuromorphic and specialized inference chips to break its monopoly. The conversation covers the spectrum of AI hardware from data center GPUs to ultra-low-power edge devices, highlighting the critical role of software stacks and latency in determining adoption. Professor Ralph Etienne-Cummings joins to critique the industry's focus on power versus learning capabilities and to discuss the future of neuromorphic computing, including memristors and photonic integration.

  • Over the Air · 20m

    The Future of IoT Revealed: Inside Samsara's Data Revolution with Evan Welbourne

    Evan Welbourne, Head of AI and Data at Samsara, discusses the evolution of IoT from a distinct technology to an invisible infrastructure, emphasizing that the real value lies in data analytics and edge computing. He details Samsara's pivot from a temperature sensor to a vehicle gateway, highlighting how thermal constraints in AI dash cams drive hardware design decisions. The conversation explores the future of neuromorphic computing, data ownership in connected devices, and the rise of edge AI for real-time safety insights.

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by IoT For All Podcast. The episode itself belongs to its publisher.