EDGE AI POD
This podcast explores the cutting-edge field of energy-efficient machine learning and edge AI, covering hardware accelerators, software algorithms, and real-world applications. It features content from the EDGE AI Foundation community, including EDGE AI Talks, EDGE AI Blueprints, and event presentations. Episodes span research, product development, and business topics related to edge AI. The show aims to keep listeners informed and inspired about the latest developments in this growing field.
Episodes
How Edge AI Moves From Cloud Hype To Real-World Impact
What if the next great leap in AI isn’t bigger models in bigger clouds, but millions of small, smart systems making decisions where the data is born? Guy Tamir of Intel connects the dots from steam and electricity to today’s language-driven AI, then map the pattern that keeps repeating: parallelism, mobility, autonomy, and finally distributed swarms. Once machines learned our language with tokeniz
Edge AI, Energy, And Autonomy
What if the next big jump in productivity isn’t a single breakthrough but a flywheel—AI that runs on the edge, energy systems that adapt in real time, and autonomy that safely acts in the physical world? Professor Winston Hsu of NPU in Taiwan brings academic perspective and industry experience together to map where the value actually lands over the next few years.We start by reframing AI’s progres
Why The Next Wave Of AI Lives At The Edge
AI’s center of gravity is moving—from monolithic cloud models to a living fabric that connects devices, senses the world, and infers on the spot. We walk through how agentic systems coordinate models across earbuds, phones, gateways, cars, and the cloud to deliver speed, privacy, and lower costs without sacrificing capability.We unpack the practical stack behind this shift: connect, sense, and inf
Why Hardware, Software, And Developers Must Unite To Bring AI To The Real World
The hype fades fast when your cloud bill spikes and your devices still lag. We sat down with leaders from Qualcomm, Renesas, Enerzai, Kudrat AI, and Advantech to trace how edge AI finally delivers real-world value—by uniting silicon, software, and developer experience into one coherent pipeline. From cost predictability to privacy and power, the economic and technical case for running models on-de
Your Earbuds Might Be Smarter Than Your Car - A talk with Iri Trashanski of Ceva
Join Iri Trashanski, Chief Strategy Officer of Ceva, as we explore how intelligence is shifting into a distributed fabric where devices connect, sense, and infer in concert with the cloud. From phones and PCs to earbuds, cars, and medical wearables, we break down why latency, privacy, cost, and power are driving a new architecture—and how agentic AI coordinates models across endpoints to deliver s
Cans, Defects, And Synthetic Vision
What if the best training data for your model never existed in the real world? We walk through a practical, high-stakes use case—defect detection on aluminum cans—and show how synthetic images, perfect annotations, and smart scene design can outperform slow, manual pipelines.First, we explain why traditional data collection and labeling bog down computer vision projects: rare defects are hard to c
Bridging the Research-Reality Divide in Edge AI
Ever wondered why so many groundbreaking AI innovations never make it to market? The answer lies in the treacherous gap between research and reality – a challenge that's costing companies millions and delaying critical technologies from reaching consumers.This riveting panel discussion brings together seasoned experts from Intel, Wind River, Advantech, EmbedUR, and The Things Industries who&a
Synthetic Data For Smarter Vision
You shouldn’t need a warehouse full of broken products to build a reliable vision model. We dig into how synthetic data flips the script for manufacturing and quality control, showing why controlled scenes, perfect labels, and rapid iteration can outrun old pipelines of manual collection and error-prone annotation. With Sherry List and Goran from Synthetic AI Data, we walk through the strategy beh
Cloud Can’t Keep Up, So Your Toaster Gets A Brain
The cloud can’t carry the weight of billions of sensors forever, and we’re proving why. We walk through a new class of ultra‑low‑power, heterogeneous neuromorphic microcontrollers that bring real intelligence to the edge, where timing, latency, and privacy matter most. From raw IMU streams to on‑device actions, you’ll hear how spiking neural networks, tiny CNNs, and a RISC‑V core team up to decode
Edge AI That Cuts Chemical Waste
What if a lab test that takes 12 to 24 hours could be replaced by a live estimate that guides dosing in real time? We walk through a high-stakes water story where boron control in desalination demanded more than a clever model—it needed a secure, local-first AI system that works across wildly different plants.Our journey with Acciona started with a simple idea: a virtual sensor to predict boron an
The Skinny Transformer: Squeezing Gen AI into Tiny Devices
The future of artificial intelligence isn't just in massive cloud data centers—it's happening right now on the devices all around us. This insightful panel discussion brings together leading experts from major semiconductor companies and academia to explore how Generative AI is transforming edge computing.What makes this conversation particularly valuable is the panelists' emphasis
How Microsecond AI Control Transforms Power Systems And Cuts Errors
What if the control loop could think ahead and correct itself before errors take hold? We dive into a practical leap for motors, inverters, and energy storage: ultra-low-latency edge AI that predicts error trajectories at startup and intervenes inside the loop in about 100 microseconds. Instead of piling on sensors and pushing raw signals to the cloud, we work directly from existing operational da
Edge of Tomorrow: How NXP is Revolutionizing On-Device AI
The AI landscape is transforming rapidly, and NXP Semiconductors is at the forefront of bringing these capabilities where they matter most—directly to edge devices. Alberto Alvarez delivers a compelling overview of how NXP is enabling sophisticated generative AI to run locally on microprocessors, without relying on cloud connectivity.Unlike companies focused on massive cloud-based AI training, NXP
Hardware-Aware AI, Not Just Bigger Models
What if the obstacle to fast, reliable AI isn’t your dataset or your optimizer—but the silicon under your model? We dig into why performance collapses when architecture and hardware don’t align, and we lay out a clear path to ship models that actually fly on the devices your users own. Starting with the Ferrari-and-hummingbird metaphor, we show how theoretical efficiency—FLOPs, parameters, even TO
What If A Pair Of Glasses Could Read Intent?
Imagine steering a game with nothing but a blink and a glance. That’s the spark behind our latest build: a noninvasive brain-computer interface that runs entirely on a tiny edge microcontroller, translating eye movements into reliable, real-time commands without a laptop or cloud.We start with the human why. Millions live with neurological conditions that constrain movement but preserve eye contro
Got Fake Chips? Our AI Doesn't Fall For That
Semiconductor counterfeiting has grown into a $200 billion annual problem threatening the integrity of global electronics supply chains. As both chip shortages and sophisticated counterfeiting techniques persist, traditional detection methods fall short—requiring complex setups, hardware modifications, or extensive data labeling.Two machine learning engineers from Analog Devices' advanced R&a
Smarter AI, Faster Hardware
Your phone, watch, and even your fridge want real-time intelligence—but power and latency won’t tolerate bloated models or generic compute. We walk through a practical path from Python to custom hardware using high-level synthesis, then invite you to prove it in our Efficient Inferencing Hackathon. With a ready-to-run RISC‑V Rocket Core baseline for MNIST, a full Siemens EDA toolchain, and on-dema
Village OS: AI For Sustainable Living
What if a neighborhood could think, heal, and feed itself? We sit down with James Ehrlich of Stanford to unpack Village OS, a generative AI platform that designs resilient communities by starting with a simple question: what does the land want? From the urban edge of Riyadh to peri-urban sites worldwide, James shows how geospatial data, climate histories, hydrology, and cultural patterns come toge
When Edge AI Meets Hearing Loss, Access Gets Real
Crowded cafés, clinking plates, and echoey halls make conversations exhausting. We set out to change that by fitting real deep learning into an ear-sized device and proving it can separate speech from noise with almost no delay or battery hit. The result isn’t louder sound; it’s clearer lives and less fatigue.We walk through the full Clara enhancement path: transforming raw mic input into log-mel
Cows Chewed Our Sensors And Still Taught Us About Edge AI
A failed 5G rollout in a legendary forest forced us to rethink everything we knew about AI infrastructure. Instead of pushing data to distant servers, we turned wearables, sensors, and tiny controllers into a cooperative network that can sense, decide, and act without the cloud. The result is a hands-on tour of decentralized AI: how to split models across devices, why feature fusion matters more t
How AI Compensates for PID Controller Limitations in Electric Vehicles with STMicroelectronics
How can artificial intelligence transform electric vehicle performance? Discover the groundbreaking application of neural networks to motor control challenges that even Formula 1 legend Michael Schumacher helped identify.The automotive industry's electrification demands increasingly sophisticated silicon solutions, particularly for traction inverters controlling electric motors. Traditional c
How to simplify and securely maintain up-to-date AI Models in the Edge
Ever shipped a smart device and worried what happens after it leaves the lab? We dig into the hard parts of edge security—where models live on-device, firmware updates are routine, and attackers treat your fleet as a supply chain—then break them down into moves any team can adopt. From secure boot that blocks untrusted code at power-on to verified boot with discrete secure elements, we show how to
AI-Driven Brain-Computer Interface (BCI) Unlocking the Minds Potential
Imagine steering a game or selecting a letter with nothing but a blink or a glance. We set out to make that feel normal, not magical, by building a non-invasive brain–computer interface that runs entirely on a low-power microcontroller and fits into everyday wearables like glasses. No surgery, no cloud dependency—just smart sensing, tight signal processing, and a tiny neural net that turns eye mov
An Embedded Transformer- base face recognition system in the STM32N6
What if transformer-level face recognition could run on a microcontroller without giving up speed or accuracy? We set out to make that real on the STM32N6 by pairing its neural processing unit with a hybrid model that blends convolutional efficiency and attention-like global context. Along the way, we rewired core assumptions about attention, reworked unsupported operators, and delivered a full on
Verification, Validation & Certification of AI in Safety-Critical Applications
A cyclist disappears to the model, not to your eyes—and that mismatch is the heart of safety-critical AI. We open with the “vanishing cyclist” to show how tiny, imperceptible perturbations can flip life-or-death decisions, then walk through a practical path to trust that spans data, verification, and deployment. Along the way, we share real stories from BMW, Airbus, and Madrid Metro to ground the
Aptos: Creating ML models that fit your edge device like a glove
Shipping edge AI shouldn’t feel like a marathon through model zoos, missing ops, and latency ceilings. We lay out a practical path to get from your data and constraints to a hardware-ready model—measured on real boards—without the endless back-and-forth between data science and firmware teams. If you’ve wrestled with quantization loss, unsupported kernels, or picking the “right” NPU, this walkthro
Neural-ART: ST’s New NPU Architecture at the Edge
What if the fastest path to efficient edge AI isn’t a bigger CPU, but a smarter stream of data? We pull back the curtain on NeuralArt—the flexible, stream‑based accelerator inside the STM32N6—and show how a decade of prototypes led us to rethink how tensors move, how layers are scheduled, and how much work a compiler can save when memory is the real bottleneck. Instead of shuttling activations bac
A Unified Neuromorphic Platform for Sparse, Low Power Computation
Sensors are flooding the edge with data while CPUs juggle denoising, formatting, and inference. We built ADA to flip that script: a Turing-complete neuromorphic processor that computes with time-encoded spikes, slashing power, latency, and memory movement by keeping work inside an event-driven pipeline.We start by unpacking why conventional embedded architectures stall under modern workloads, from
From Fragments to Foundation: The Sound of Progress in Edge Audio AI
What if your printer didn’t just spit out pages, but actually understood them? We walk through a hands-on look at multimodal AI on the edge—how visual-language models read layouts, extract tables, translate content, and reformat documents right where data lives, without shipping sensitive files to the cloud. It’s a practical tour from passive peripherals to active intelligence, with real workflows
Empowering at the Edge: the "Arduino way" to AI
What if AI felt like a door you could open, not a wall you had to climb? We dig into how Arduino’s approach—accessibility first, power when you need it—turns the edge AI buzz into a concrete path you can follow, whether you’re a student with a starter kit or an engineer shipping to a fleet.We walk through a practical four-step journey: try AI through no-code experiments, understand it with pre-tra
Faster Edge AI, Fewer Headaches
If you’ve ever shipped a model that flew in the cloud and crawled on a device, this conversation is a relief valve. We bring on Andreas from Embedl to unpack why edge AI breaks in the real world—unsupported ops, fragile conversion chains, misleading TOPS—and how to fix the loop with a unified, device-first workflow that gets you from trained model to trustworthy, on-device numbers in minutes.We st
TinyML Implementation for a Textile-Integrated Breath Rate Sensor
Clothes that quietly listen to your breath might be the missing link between hospital‑grade vigilance and everyday comfort. We walk through how our team built a textile‑integrated breath sensor that actually works in the wild—embroidered interconnects, 3D‑printed dielectric islands, and a carbonized‑silicon yarn strain gauge stitched into a belt—then taught it to estimate breathing at the edge wit
From Lab to Low-Power: Building EMASS, a Tiny AI Chip That Runs on Milliwatts
What if the only way to get real gains at the edge is to redesign everything—from the silicon atoms to the app you deploy? That’s the bet Professor-Founder Mohammed Ali made with EMAS, and the results are striking: continuous inference at milliwatts, microsecond wake/sleep cycles, and real benchmarks that hold up against the best in class while burning a fraction of the energy.We walk through how
What happens when AI learns from the fire hose—and tests itself on silicon
What if your model pipeline started with a simple goal—your dataset, your target chip, and your latency or energy budget—and ended with measured results on real hardware? We sit down with Model Cat CEO Evan Petritis to explore how AI can build on-device AI through a closed loop that’s grounded in silicon, not estimates or hopeful benchmarks. From a live demo to a tour of their “chip farm,” we dig
Survey Data Shows How AI Will Reshape Cars And Why It Belongs On The Edge
We share new data showing why drivers see generative AI as a defining force in mobility and how edge inference makes cars faster, safer, and more personal. We map the use cases, hardware shifts, and the move to software-first procurement with clear guidance for builders.• survey highlights on generative AI as a mobility megatrend• definitions and examples of circular economy in vehicles• priority
What happens when you use AI to optimize AI and make AI models run fast anywhere?
Tired of choosing between performance and freedom? We sit down with Stefan Crossin, CEO and co‑founder of YASP, to unpack how a hardware‑aware AI compiler can speed up training, simplify deployment, and finally make model portability real. The story starts with a distributed team in Freiburg and Montreal and moves straight into the heart of the problem: most AI groups burn time on infrastructure a
2026 and Beyond - The Edge AI Transformation
What if the smartest part of AI isn’t in the cloud at all—but right next to the sensor where data is born? We pull back the curtain on the rapid rise of edge AI and explain why speed, privacy, and resilience are pushing intelligence onto devices themselves. From self‑driving safety and zero‑lag user experiences to battery‑friendly wearables, we map the forces reshaping how AI is built, deployed, a
Edge Computing Revolutionized: MemryX's New AI Accelerator
Ready to revolutionize your approach to edge AI? Keith Kressin, a veteran with 13 years at Qualcomm before joining MemoryX, shares a breakthrough technology that's transforming how AI operates in resource-constrained environments.MemoryX has developed an architecture that defies conventional wisdom about AI acceleration. Unlike traditional systems dependent on memory buses and controllers, th
Atym and WASM is revolutionizing edge AI computing for resource-constrained devices.
Most conversations about edge computing gloss over the enormous challenge of actually deploying and managing software on constrained devices in the field. As Jason Shepherd, Atym's founder, puts it: "I've seen so many architecture diagrams with data lakes and cloud hubs, and then this tiny little box at the bottom labeled 'sensors and gateways' - which means you've ne
Honey, I Shrunk the LLMs: Edge-Deployed AI Agents
The landscape of artificial intelligence is experiencing a profound transformation, with AI capabilities moving from distant cloud servers directly to edge devices where your data lives. This pivotal shift isn't just about running small models locally—it represents a fundamental reimagining of how we interact with AI systems.In this fascinating exploration, Dell Technologies' Aruna Kollu
Ambient Scientific's Journey: From Personal Tragedy to Ultra-Low Power AI Innovation
When personal tragedy strikes, some find a way to transform pain into purpose. Such is the remarkable story behind Ambient Scientific, where founder GP Singh's mission to prevent falls after losing a family member evolved into groundbreaking semiconductor technology enabling AI at the ultra-low power edge.The journey wasn't simple. Creating chips that could run sophisticated deep learnin
How EMASS is Revolutionizing Battery-Powered AI Applications
Power efficiency has become the new currency in AI, and no company exemplifies this shift better than EMAS. Founded by Professor Mohamed Ali as a spinoff from his groundbreaking research at NTU Singapore, this innovative startup is revolutionizing edge AI with semiconductor technology that delivers unprecedented power efficiency for battery-constrained devices.The story begins in 2018 when Ali and
Beyond the Cloud: The Hidden Security Challenges of Edge AI
"Do you trust your AI models? Honestly, I don't trust them. We should not trust them." These powerful words from STMicroelectronics' Mounia Kharbouche perfectly capture the security challenge facing the edge AI world today.As organizations rush to deploy AI workloads at the edge, a complex security landscape emerges that demands careful navigation. This fascinating panel discus
Real World Deployment and Industry Applications
The humble printer - that device gathering dust in the corner of your office - is about to undergo a remarkable transformation. Thanks to advancements in generative AI, printers and scanners are evolving from passive endpoints into intelligent document processing powerhouses.Arniban from Wipro Limited unveils how visual language models (VLMs) like QN 2.5 VL and LayoutLMv3 are being deployed direct
Bridging the Digital Divide by Generative AI through the Edge
The technological revolution sparked by generative AI threatens to create the deepest digital divide we've ever seen. In this illuminating talk, Danilo Pau from STMicroelectronics reveals how only a handful of companies worldwide possess the resources to fully harness large-scale generative AI, while the rest of humanity risks being left behind.Pau takes us through the sobering reality of tod
Networked AI Agents Decentralized Architecture
What happens when trillions of AI agents can discover, communicate, and collaborate across organizational boundaries? Pradyumna Shari from MIT Media Lab unveils NANDA (Networked AI Agents in a Decentralized Architecture), a groundbreaking open protocol that could fundamentally transform how we interact with artificial intelligence.Drawing a fascinating parallel between computing history and our AI
Generative AI on NXP Microprocessors
Stepping into a future where AI doesn't require the cloud, NXP is revolutionizing edge computing by bringing generative AI directly to microprocessors. Alberto Alvarez offers an illuminating journey through NXP's approach to private, secure, and efficient AI inference that operates entirely at the edge.The heart of NXP's innovation is their EAQ GenAI Flow, a comprehensive software p
Transforming Human-Computer Interaction with OpenVINO
The boundary between humans and computers is blurring as AI capabilities advance, creating opportunities for more natural, conversational interactions with our devices. Raymond Lowe from Intel takes us on a journey through the evolution of human-computer interaction, from simple mouse clicks to sophisticated chatbots that understand context, process images, and engage in meaningful dialogue.At the
Support for Novel Models for Ahead of Time Compiled Edge AI Deployment
The growing gap between rapidly evolving AI models and lagging deployment frameworks creates a significant challenge for edge AI developers. Maurice Sersiff, CEO and co-founder of Germany-based Roofline AI, presents a compelling solution to this problem through innovative compiler technology designed to make edge AI deployment simple and efficient.At the heart of Roofline's approach is a reta
Comparative Analysis of NPU Optimized Software Framework
The future of AI isn't just in massive cloud servers—it's already sitting in your pocket. In this eye-opening presentation, Yeon-seok, CEO and co-founder of JTIC AI, reveals how his company is revolutionizing the AI landscape by tapping into the underutilized Mobile Processing Units (MPUs) that have been standard in smartphones since 2017.While tech giants pour billions into cloud infras
Powering Intelligence: Anaflash's Revolutionary AI Microcontroller with Embedded Flash Memory
Memory bottlenecks, not computational limitations, are the true barrier holding back Edge AI. This revelation lies at the heart of Anaflash's revolutionary approach to intelligent edge computing – a breakthrough AI microcontroller with embedded flash memory that transforms how we think about power efficiency and cost in smart devices.The team has engineered a solution that addresses the two f
Enhancing Field Oriented Control of Electric Drives with tiny Neural Network
Ever wondered how the electric vehicles of tomorrow will squeeze every last drop of efficiency from their batteries? The answer lies at the fascinating intersection of artificial intelligence and motor control.The electrification revolution in automotive technology demands increasingly sophisticated control systems for permanent magnet synchronous motors - the beating heart of electric vehicle pro
Transforming Human-Computer Interaction with OpenVINO
The gap between science fiction and reality is closing rapidly. Remember when talking to computers was just a fantasy in movies? Raymond Lo's presentation on building chatbots with OpenVINO reveals how Intel is transforming ordinary PCs into extraordinary AI companions.Imagine generating a photorealistic teddy bear image in just eight seconds on your laptop's integrated GPU. Or having a
Energy Efficient and high throughput inference using compressed tsetlin machine
Logic beats arithmetic in the machine learning revolution happening at Newcastle University. From a forgotten Soviet mathematician's work in the 1960s to modern embedded systems, Settle Machine represents a paradigm shift in how we approach artificial intelligence.Unlike traditional neural networks that rely on complex mathematical operations, Settle Machine harnesses Boolean logic - simple y
Applying GenAI to Mice Monitoring
The AI revolution isn't just for tech giants with unlimited computing resources. Small and medium enterprises represent a crucial frontier for edge generative AI adoption, but they face unique challenges when implementing these technologies. This fascinating exploration takes us into an unexpected application: smart laboratory mouse cages enhanced with generative AI.Laboratory mice represent
Simple Cost Effective Vision AI Solutions at the edge
Sony's revolutionary IMX500 stands at the forefront of a quiet revolution in edge computing and smart city technology. This isn't just another image sensor—it's the first to integrate AI processing directly on the chip, transforming how visual data becomes actionable intelligence while preserving privacy and minimizing infrastructure requirements.The power of this innovation lies in
Low Code No Code Platform for Developing AI algorithms
Revolutionizing edge computing just got easier. This eye-opening exploration of ST Microelectronics' ST-IoT Craft platform reveals how everyday developers can now harness the power of artificial general intelligence without writing a single line of code.The modern IoT landscape presents a paradox: billions of devices generate zettabytes of valuable data, yet transforming that raw information
Stochastic Training for Side-Channel Resilient AI
Protecting valuable AI models from theft is becoming a critical concern as more computation moves to edge devices. This fascinating exploration reveals how sophisticated attackers can extract proprietary neural networks directly from hardware through side-channel attacks - not as theoretical possibilities, but as practical demonstrations on devices from major manufacturers including Nvidia, ARM, N
Beyond TOPS: A Holistic Framework for Edge AI Metrics
Beyond raw computational power lies the true measure of AI system effectiveness. Austin Lyons, founder of ChipStrat and analyst at Creative Strategies, challenges us to rethink how we evaluate Edge AI technologies in this thought-provoking talk on metrics that truly matter.For too long, the industry has obsessed over Trillion Operations Per Second (TOPs) as the gold standard measurement. Lyons exp
How AI Zip Is Shrinking Models for a Device-First Future
What if we could put powerful AI anywhere—from underwater cameras monitoring fish to the phone in your pocket? That's the vision driving AI Zip, a company building ultra-efficient AI models that can run on virtually any device.During this fascinating conversation, we explore how AI Zip is pioneering a different path in artificial intelligence by focusing on extreme compression and efficiency.
How Innatera is Revolutionizing Low-Power AI with Neuromorphic Chips
What happens when we redesign computing hardware to work more like the human brain? The results are transformative for edge AI.Sumit Kumar from Inatera takes us inside the world of neuromorphic computing – a revolutionary approach that's bringing brain-like intelligence directly to sensors. Born from research at Delft University of Technology, Inatera is tackling one of the most significant c
How Edge Matrix is Transforming Video Monitoring Through AI
Smart cities face an impossible challenge - monitoring countless security cameras 24/7 with human operators alone. Edge Matrix is solving this problem with innovative AI technology that transforms how urban environments approach security and monitoring.Founded in 2019 as a Cloudian spin-off, Edge Matrix has developed sophisticated video AI solutions designed specifically for smart city application
From Stanford Labs to Edge AI Pioneers: FemtoSense's Journey
The quest to create artificial intelligence as efficient as the human brain is one of computing's most fascinating challenges. While today's AI systems consume megawatts of power in massive data centers, your brain accomplishes far more complex tasks on roughly 20 watts—about the same as a dim light bulb. This efficiency gap is what FemtoSense is determined to close.In this illuminating
Smart Sampling Unlocks Edge AI Capabilities You Never Thought Possible
What if everything we assumed about AI and data was wrong? In a world obsessed with collecting more and more sensor data, LightScline has discovered something remarkable: we might only need 10% of it.Drawing inspiration from the human brain's selective attention mechanism, LightScline co-founders Ankur and Ayush Goel have developed an approach that trains AI models to identify only the most i
The future belongs to greasy machines that think for themselves - Anoop Balachandran of Tinkerblox
From cloud dependency to edge autonomy – we explore the frontier of intelligent edge computing with TinkerBlocks co-founder Anoop.Imagine a world where your machines don't need to phone home to make decisions. That's the vision driving TinkerBlox, a startup founded by former Bosch Digital executives who saw firsthand how IoT implementations were hamstrung by excessive reliance on cloud p
How embedUR is bridging the gap between embedded development and AI with Rajesh Subramanian
The technological pendulum has swung dramatically over the last two decades. From desktop computing to cloud dominance and now back to the critical importance of edge devices, we're witnessing a renaissance in embedded systems. But this time, they're getting smart.Rajesh, founder of embedUR, takes us on a journey through this evolution, explaining how his company transformed from connect
How Weeteq is Revolutionizing Microcontroller Technology for Industrial Automation
What happens when you push AI to the absolute edge of networks? Meet Weeteq, a Scottish startup revolutionizing system optimization by bringing intelligence directly into microcontroller control loops.In this fascinating conversation with Martin from Weeteq, we explore the concept of "Ultra Edge" - technology that operates beyond what we typically consider Edge AI. Unlike conventional ap
From Cloud to Edge: NXP's AI Journey with Ali Ors
The line between cloud and edge AI is blurring, and NXP Semiconductors stands at the forefront of this transformation. In this illuminating conversation, Ali Ors, Head of AI Strategy and Technologies at NXP, unveils how the semiconductor giant is embedding dedicated AI acceleration across their entire product portfolio—from basic microcontrollers to sophisticated application processors.With nearly
From Arduino to AI: A 20-Year Journey with David Cuartielles
Twenty years after its founding in a small Italian café, Arduino has transformed from a simple open-source project into a global technology enabler that's educated an entire generation of makers, developers, and engineers. In this fascinating conversation with Arduino co-founder David Cuartielles, we explore the evolution of this groundbreaking platform and its growing role in the edge AI rev
From Sensors to Solutions: The Future of Edge AI with Chad Lucien of Ceva
At the crossroads of cutting-edge technology and practical innovation stands Ceva, a semiconductor IP powerhouse with a remarkable two-decade legacy. Powering nearly 20 billion devices worldwide and shipping over 2 billion annually, SIVA has emerged as a crucial enabler in the burgeoning edge AI ecosystem.What distinguishes Ceva in this competitive landscape is their holistic approach to edge comp
EDGE AI Partner: David Aronchick of Expanso
The digital landscape is rapidly evolving beyond centralized cloud computing. In this illuminating conversation with David Aronchik, co-founder of Expanso, we explore the growing necessity of processing data right where it's generated—at the edge.Drawing from his impressive background as the first non-founding PM for Kubernetes at Google and his leadership in open AI strategy at Microsoft, Da
Bringing Generative AI to Your Pocket: The Future of Edge Computing
A technological revolution is quietly unfolding in your pocket. Imagine your phone creating stunning images, understanding what its camera sees, and responding to complex questions—all without sending a single byte of data to the cloud. This isn't science fiction; it's Generative EDGE AI, and it's already here.We dive deep into this transformative trend that's bringing AI'
Audio AI on the Edge with Ceva
Audio processing at the edge is undergoing a revolution as deep learning transforms what's possible on tiny, power-constrained devices. Daniel from SIVA takes us on a fascinating journey through the complete lifecycle of audio AI models—from initial development to real-world deployment on microcontrollers.We explore two groundbreaking applications that demonstrate the power of audio machine l
Garbage In, Garbage Out - High-Quality Datasets for Edge ML Research
The EDGE AI FOUNDATION's Datasets & Benchmarks Working Group highlights the rapid progress in neural networks, particularly in cloud-based applications like image recognition and NLP, which benefited greatly from large, high-quality datasets. However, the constrained nature of edge AI devices necessitates smaller, more efficient models, yet a lack of suitable datasets hinders progress and
Edge AI Investing Essentials
The path to successful investment in edge AI requires far more than technical brilliance. In this revealing panel discussion, venture capitalists and corporate investors share what truly matters when deciding where to place their bets in the evolving edge computing landscape.At the heart of every investment decision lies a deceptively simple question: who is your customer? As Hans from Momentum Ve
Beyond the Edge: Cloud and AI Convergence
Beyond the Edge, from the EDGE AI FOUNDATION, explores the future of edge computing by advocating for a shift in perspective. It suggests moving beyond the limitations of traditional IoT deployments by integrating advancements in edge AI, semiconductors, and connectivity. The author argues that the cloud will serve as a crucial "binding agent," enabling unified management and orchestrati
Investing In The Edge: A VC Panel from AUSTIN 2025
Send us Fan MailSupport the showLearn more about the EDGE AI FOUNDATION - edgeaifoundation.org
The Pipeline Is Stalling: America's Declining Innovation Edge
America's innovation pipeline stands at a dangerous crossroads. Federal research funding has dropped 10% in real terms over the past decade, traditional public-private collaboration models are fragmenting, and barriers to international talent continue to rise. These challenges threaten the three-pillar foundation that has powered American technological leadership for generations.Our conversat
Beyond the Edge - Analyst Insights at AUSTIN 2025
What happens when four tech industry veterans sit down to dissect the future of Edge AI? A no-holds-barred conversation that cuts through the hype and delivers actionable insights for anyone working in this rapidly evolving field.The panelists tackle the burning question head-on: How can Edge AI avoid becoming the "box of cables in your garage" that IoT transformed into? Through candid d
Dan Cooley of Silicon Labs - The 30 Billion Dollar Question: Can AI Truly Live on the Edge?
Imagine a world where your smart glasses don't just identify objects but tell stories about what they see—all while running on a tiny battery without heating up. This cutting-edge vision is becoming reality as semiconductor companies tackle the monumental challenge of bringing generative AI capabilities from massive cloud data centers down to microcontroller-sized devices.The semiconductor in
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