Hardware Podcasts

The Trends Driving Edge Computing | Nubix's Jason Shepherd | Internet of Things Podcast

IoT For All Podcast · 18 Apr 2023 · 24m

What this episode covers

Jason Shepherd, CEO of Nubix, discusses the macro trends driving edge computing, emphasizing the shift from centralized cloud to multicloud strategies and data control. He explains how TinyML enables machine learning on constrained microcontrollers by using containerization to protect IP and simplify development. Shepherd also analyzes the IoT platform landscape, noting a consolidation toward vertical, outcome-focused solutions rather than horizontal platforms, and highlights the critical role of computer vision at the edge.

Most relevant to

companies scaling up

Topics

Mentioned

Companies
Nubix, Dell, HPE, AWS, Azure, Google Cloud, VMware, Red Hat, Microsoft
Products
Alexa, Echo, ChatGPT
Chips
ARM
Tools
Docker
Also
Linux

Related episodes from other shows

Other shows on the same ground, closest first.

  • 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.

    AI & machine learningMicrocontrollers & dev platforms
    7 chapters

  • Over the Air · 43m

    IoT Trends: A Year in Review and 2023 Predictions with Rob Tiffany and Bill Flaherty

    Rob Tiffany, Founder of Sustainable Logix, and Bill Flaherty, Director of Hardware Engineering at Very, review 2022 IoT trends and predict 2023 developments. They discuss how the chip shortage forced a shift from locking in specific microcontrollers to using abstraction layers like Zephyr, and highlight the democratization of technology in Ukraine through commercial drones and Starlink. The guests argue that major IoT platform shutdowns (Ericsson, SAP, Google) signal a pivot toward vertical-specific solutions, while predicting that falling sensor prices, edge AI processors like the NXP i.MX 95, and the rise of generative AI will define the coming year.

    Sourcing & supply chainConnected products & IoT
    8 chapters

  • EE Times Current · 22m

    Embedded World 2023 Recap

    Nitin Dahad, Francoise Pelle, and Sally Ward Foxton of EE Times recap Embedded World 2023, highlighting the shift toward edge AI, tiny ML, and software-defined vehicles. They discuss specific implementations from companies like Renaissance, STMicroelectronics, and Silicon Labs, focusing on running AI models on Cortex-M85 and STM32 microcontrollers with low power consumption. The episode also covers security initiatives from Kudosip and Trust In Software, as well as neuromorphic computing demos from InnerTense and Brain Chip.

    Embedded firmwareSecurity & privacy
    8 chapters

  • EE Times Current · 38m

    Taming the Wild Edge

    Chris Catterton, head of solution engineering at Micro AI (formerly OneTech), explains how their Adam ML technology enables lightweight AI training and inference on resource-constrained microcontrollers at the extreme edge of IoT. He details how this approach solves high data transmission costs by processing data locally and only sending insights to the cloud, using examples from oil rigs and manufacturing lines. Catterton also describes how the same behavioral profiling technology provides endpoint security by detecting anomalies in CPU and memory usage to prevent ransomware attacks and other threats.

    Embedded firmwareSecurity & privacy
    6 chapters

  • Embedded.fm · 1h 24m

    497: Everyone Likes Tiny

    Kwabena Agyeman, President and Co-Founder of OpenMV, discusses the launch of two new programmable camera systems, the OpenMV Cam N6 and the OpenMV AE3, via a Kickstarter campaign. He explains how integrating Neural Processing Units (NPUs) and Arm Helium SIMD instructions enables high-performance computer vision and edge AI on microcontrollers, achieving significant speedups while maintaining ultra-low power consumption. Agyeman details the software ecosystem, including MicroPython, TensorFlow Lite for Microcontrollers, and partnerships with Edge Impulse and Roboflow, which simplify model training and deployment for embedded developers.

    Embedded firmwareMicrocontrollers & dev platforms
    8 chapters

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.