The Robot Report Podcast · 11 Oct 2023 · 59m
Amir Bousani, co-founder and CEO of RGO Robotics, and Simon Jensen-Fellows from Verizon discuss how 5G mobile edge compute (MEC) and AI enable 'generative autonomy' in mobile robots, allowing them to adapt behaviors in real-time rather than following pre-programmed paths. They explain that offloading heavy AI workloads to the network edge via 5G solves latency and compute constraints, enabling complex perception and collaborative operations. The episode also features Formant CEO Jeff Linnell, who details his company's $21 million funding round led by BMW i Ventures and its platform for remote robot management and data analytics.
Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.
Engineering & simulationFormant Theopolis
Formant integrated large language models into its platform to allow users to query robot data using natural language instead of writing SQL queries.
“earlier this year, you guys released a product called Theopolis, which integrates with the data capture that you guys are selling and the customers can use chat GPT and large language models to essentially pull out data points from that…”
Speaker 1 · Hear it at 18:52
early-stage companies and companies scaling up
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Dev Singh, Senior Director of Business Development and Head of Autonomous Robotics at Qualcomm, discusses the convergence of 5G, AI, and heterogeneous computing in autonomous robotics. He explains how Qualcomm diversified from mobile to robotics by identifying the need for edge intelligence and connectivity in sectors like industrial automation and delivery drones. Singh details the technical requirements for reliable edge AI, including power efficiency, thermal management, and functional safety, while highlighting the role of 5G in enabling low-latency communication for mission-critical applications.
Renesas Electronics EVP Silas Chitapetti explains how the convergence of AI, IoT, and 5G creates 'intelligent' devices through AIoT, shifting processing from the cloud to the edge. He details Renesas' strategy of embedding AI acceleration in microcontrollers and microprocessors, supported by the acquisition of Reality AI to handle industrial machine learning workloads. Chitapetti highlights specific use cases like predictive maintenance using current sensing, vision-based authentication, and robotic food preparation, noting that these edge AI applications reduce hardware costs and improve response times.
Adil Kidwai, VP and Head of Product Management at EdgeQ, explains how the company built a software-defined base station-on-a-chip that combines 5G and AI capabilities using RISC-V processors. He details the mathematical similarities between information theory and AI, allowing EdgeQ to offer customizable features like low latency or high bandwidth to reduce power consumption and cost compared to traditional multi-chip solutions. Kidwai also reflects on his career transition from Intel's wireless division to a startup environment, highlighting the challenges of scaling during the pandemic and the shift in cellular networks from human-centric to machine-centric communication.
Nan Li, Managing Director at Obvious Ventures, explains how next-generation robots are shifting from fixed, pre-programmed tasks to hyper-intelligent, adaptable systems capable of real-time environmental awareness. He details how advancements in computer vision and perception, largely driven by autonomous vehicle R&D from companies like Tesla and Waymo, have lowered costs and accelerated deployment for industrial robotics. Li highlights that these new systems, such as those from Dexterity, are becoming financially accessible through robotics-as-a-service models and can achieve production-ready speeds of 1,000 to 2,000 picks per hour in mixed-bin scenarios.
Anthony Jules, CEO and co-founder of Robust.AI, discusses the design and deployment of Carter, an AI-driven collaborative mobile robot for warehouses. Jules explains how Carter uses cameras instead of LIDAR to achieve semantic understanding, allowing it to navigate safely alongside humans and empower floor associates rather than replace them. He details the company's 'fleet learning' strategy, where data from individual robots is aggregated in the cloud to improve AI models offline, ensuring consistent productivity for clients like DHL without disrupting live operations.
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