EDGE AI POD
Discover the cutting-edge world of energy-efficient machine learning, edge AI, hardware accelerators, software algorithms, and real-world use cases with this podcast feed from all things in the world's largest EDGE AI community.
These are shows like EDGE AI Talks, EDGE AI Blueprints as well as EDGE AI FOUNDATION event talks on a range of research, product and business topics.
Join us to stay informed and inspired!
Episodes
101 episodes
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 f...
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 ...
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?...
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. ...
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,...
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 ...
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 the...
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...
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 effic...
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 p...
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-...
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 rethin...
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 memo...
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...
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 ...
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, misle...
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 interc...
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 milli...
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 ...
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 c...
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 ...
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 device...
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.Memory...
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...
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 ...