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
108 episodes
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,...
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 secur...
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 academ...
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...
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 sophistic...
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 a...
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-tim...
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...