Bringing Generative AI to Your Pocket: The Future of Edge Computing

EDGE AI POD

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محتوای ارائه شده توسط EDGE AI FOUNDATION. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط EDGE AI FOUNDATION یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

NerdWallet's Smart Money Podcast

1
The Right Way to Dodge Scams, Plus Learn How Robo-Investing Works 29:56

۵ weeks پیش29:56

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دوست داشته شد

29:56

Learn how to dodge scams to protect your money, then understand how to compare robo vs. traditional investment risks. What should you do if your credit card is compromised in a scam? Are robo-advisors riskier than traditional brokerage accounts? Hosts Sean Pyles and Elizabeth Ayoola discuss how to spot and respond to identity theft and dig into how robo-advisors stack up to traditional investing platforms to help you protect your financial life. They kick off Smart Money’s new Scam Stories series by welcoming guest Scramble Hughes, a circus performer and scam victim, who shares a real-life experience with credit card fraud. They discuss tips and tricks on recognizing red flags like mass spam messages, acting fast by calling the number on your card (not clicking links), and filing credit freezes with all three credit bureaus. Then, investing Nerd Bella Avila joins Sean and Elizabeth to discuss how robo-advisors compare to traditional brokerage accounts. They discuss risk levels in automated portfolios, SIPC insurance protections, and key factors to consider when choosing a platform like account minimums, platform stability, and user experience. See NerdWallet’s top picks for the best robo-advisors of 2025 here: https://www.nerdwallet.com/best/investing/robo-advisors Want us to review your budget? Fill out this form — completely anonymously if you want — and we might feature your budget in a future segment! https://docs.google.com/forms/d/e/1FAIpQLScK53yAufsc4v5UpghhVfxtk2MoyooHzlSIRBnRxUPl3hKBig/viewform?usp=header In their conversation, the Nerds discuss: credit card fraud, how to report identity theft, robo advisor vs brokerage account, SIPC insurance limits, credit freeze Experian, how to freeze your credit, credit card scams TikTok, how to know if a text is a scam, what is a robo advisor, tax loss harvesting robo advisor, ETF risk robo advisor, ETF diversification, FDIC vs SIPC, how to block spam texts, freeze credit TransUnion, safest robo advisors 2025, best robo advisor for ETFs, hacked credit card reader, RFID credit card theft, how to recover from identity theft, difference between SIPC and FDIC, scams targeting small business owners, how to secure your investment accounts, how to protect credit card information, email spam after identity theft, what to do after credit card theft, how long do fraud refunds take, when to freeze credit, best practices after identity theft, and comparing investment platform safety. To send the Nerds your money questions, call or text the Nerd hotline at 901-730-6373 or email podcast@nerdwallet.com . Like what you hear? Please leave us a review and tell a friend. Learn more about your ad choices. Visit megaphone.fm/adchoices…

حدود یک سال پیش 27:10

MP3•خانه قسمت

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's creative powers directly to our devices. Building on the foundation laid by the tiny ML movement, Generative EDGE AI represents a fundamental shift in how we'll interact with technology. The benefits are compelling: complete privacy as your data never leaves your device, lightning-fast responses without internet latency, independence from network connections, and significant cost savings from reduced cloud computing needs.
The applications span far beyond convenience. For people with disabilities, it means having image captioning that works anywhere, even without internet. For photographers, it's like having a professional editor built right into your camera. In healthcare, it enables diagnostics while keeping sensitive patient data secure and accessible even in areas with poor connectivity.
The technical achievements making this possible are equally impressive. Researchers have shrunk massive AI models to run efficiently on everyday devices, from visual question answering systems that respond in milliseconds to text-to-speech engines that sound remarkably natural. They're even making progress bringing text-to-image generation and small language models directly to smartphones.
As we explore these breakthroughs, we consider the profound implications of truly intelligent devices that can learn, adapt, and make decisions autonomously. What happens when our technology not only understands but creates and acts independently? The silent AI revolution happening in our hands is set to transform our relationship with technology in ways we're just beginning to comprehend.
Ready to understand the future that's already arriving? Listen now and glimpse the world where intelligence lives at your fingertips, not in distant server farms.

Send us a text

Support the show

Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

فصل ها

1. Introduction to Edge Gen AI (00:00:00)

2. Why Bring AI to Edge Devices? (00:01:42)

3. Real-World Applications (00:03:45)

4. Visual Question Answering Breakthroughs (00:06:11)

5. Image and Video Captioning (00:10:28)

6. Text-to-Speech and Audio Enhancement (00:12:46)

7. Language Processing and Privacy Tools (00:15:56)

8. Challenges and Future Directions (00:22:39)

9. The Bigger Picture and Conclusion (00:25:55)

56 قسمت

#Tech #tinyML Foundation #TinyML #IoT #Edge #Genai #Semiconductors #Device #Edgeai #Communities

Bringing Generative AI to Your Pocket: The Future of Edge Computing

EDGE AI POD

published حدود یک سال پیش

اشتراک گذاری

MP3•خانه قسمت

Send us a text

Support the show

Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

فصل ها

1. Introduction to Edge Gen AI (00:00:00)

2. Why Bring AI to Edge Devices? (00:01:42)

3. Real-World Applications (00:03:45)

4. Visual Question Answering Breakthroughs (00:06:11)

5. Image and Video Captioning (00:10:28)

6. Text-to-Speech and Audio Enhancement (00:12:46)

7. Language Processing and Privacy Tools (00:15:56)

8. Challenges and Future Directions (00:22:39)

9. The Bigger Picture and Conclusion (00:25:55)

56 قسمت

#Tech #tinyML Foundation #TinyML #IoT #Edge #Genai #Semiconductors #Device #Edgeai #Communities

همه قسمت ها

EDGE AI POD

1
How Innatera is Revolutionizing Low-Power AI with Neuromorphic Chips 16:28

1 hour پیش16:28

16:28

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 challenges in modern technology: how to perform complex AI tasks on battery-powered devices without draining power. The key lies in spiking neural networks that are fundamentally different from conventional AI approaches. These event-driven networks operate with computational dynamics that mimic brain function, resulting in models 100 times smaller than traditional AI while consuming just a fraction of the power. For applications like video doorbells, acoustic scene classification, and wearable healthcare, this means continuous monitoring with millisecond latency at just a few milliwatts – outperforming traditional microcontrollers by at least 10x. Beyond current applications, neuromorphic computing opens entirely new possibilities. The technology excels not just with conventional vision but with radar sensors and other modalities, particularly in privacy-sensitive situations. Robotics represents another frontier, where neuromorphic systems can enhance environmental perception, process complex sensor fusion, and enable low-latency control. Through academic partnerships and industry collaboration via the Edge AI Foundation, Inatera is helping build the ecosystem that will make neuromorphic computing as ubiquitous as neural networks are today. The future of edge AI may indeed be neuromorphic. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
How Edge Matrix is Transforming Video Monitoring Through AI 28:32

۷ روز پیش28:32

28:32

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 applications. Their systems can continuously monitor multiple camera feeds, instantly detect anomalies, and alert security personnel when issues arise. What makes their approach unique is the comprehensive nature of their offering - they don't just provide software, but build the rugged hardware needed for outdoor deployment in challenging environments like roadways and public spaces. The team at Edge Matrix has engineered remarkably resilient systems built around NVIDIA's Jetson platform, incorporating features like supercapacitor backups and secondary control systems that can perform complete power cycles remotely when needed. This ensures their equipment maintains continuous operation without manual intervention. Their newest product, Edge AI Station, bundles ready-made AI applications for common use cases like traffic analysis, people counting, and fire detection, making advanced AI monitoring accessible to organizations without extensive technical resources. Edge Matrix represents the future of urban security - intelligent, always-vigilant systems that transform ordinary cameras into powerful monitoring tools. As cities continue growing smarter, solutions like these will become essential infrastructure for maintaining safety and security at scale. Want to see how AI is revolutionizing urban monitoring? Visit edgematrix.com to learn more about their innovative approach to smart city technology. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
From Stanford Labs to Edge AI Pioneers: FemtoSense's Journey 20:11

14 روز پیش20:11

20:11

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 conversation with Sam from FemtoSense, we dive into the journey of this Stanford spin-off that's revolutionizing edge AI with neuromorphic-inspired computing. The company's very name speaks to their mission—"femto" references the femtojoule, the incredibly tiny amount of energy required for a single neuron in your brain to communicate with another. Their goal? Create AI systems that approach this remarkable biological efficiency. What makes FemtoSense's approach unique is how they've evolved from pure academic research to commercial viability. Rather than pursuing neuromorphic computing in its purest form, they've distilled its key efficiency principles—sparse computing and spatial locality—into manufacturable, reliable systems. This pragmatic approach is already bearing fruit in consumer wearables like AI-powered hearing aids that maintain 24-hour battery life while delivering sophisticated audio processing, and in smart home devices that offer on-device intelligence without cloud dependence. For battery-powered devices, their technology extends runtime dramatically; for plugged-in devices, it slashes costs by reducing silicon footprint. As Sam puts it, "Efficiency is the new currency." The principles that make FemtoSense's technology possible aren't tied to any specific market or modality—they represent fundamental improvements in how computing can be done. With global operations spanning the US, Asia, and Europe, and active participation in industry groups like the Edge AI Foundation, FemtoSense isn't just building more efficient chips; they're helping shape a future where AI can be everywhere without consuming the planet's resources. Curious about the future of efficient AI? Join us at upcoming Edge AI Foundation events and discover how companies like FemtoSense are making AI that's not just smarter, but fundamentally more sustainable. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
Smart Sampling Unlocks Edge AI Capabilities You Never Thought Possible 20:15

21 روز پیش20:15

20:15

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 information-rich portions of sensor data streams. The results are staggering—models requiring 400x fewer computational operations while maintaining state-of-the-art accuracy across multiple domains. This revolutionary approach solves two critical problems facing organizations swimming in sensor data: spiraling infrastructure costs (cloud computing, storage, bandwidth) and mounting human capital expenses, where each additional hour of collected data traditionally requires 40+ hours of analysis. By focusing only on what matters, LightSkline's technology dramatically reduces both. The real-world impact is already evident. A Fortune 150 company monitoring high-value industrial equipment achieved exceptional accuracy using just 10% of their raw data. Another major software provider saw 381x fewer computational operations and 85x faster training times. Perhaps most impressive is the technology's ability to run on tiny edge devices with as little as 264KB of RAM—enabling applications previously considered impossible on resource-constrained hardware. This efficiency breakthrough isn't just incremental—it's transformative. It allows entirely new applications in wearables, industrial monitoring, and distributed fiber optic sensing (which can generate terabytes of daily data from monitoring kilometers of fiber cable). By bringing both training and inference to the edge, LightSkline is redefining what's possible in physical intelligence. Want to push more intelligence to the edge while dramatically reducing your computational footprint? Discover how LightSkline's approach could transform your sensing applications and unlock entirely new possibilities in edge AI. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
The future belongs to greasy machines that think for themselves - Anoop Balachandran of Tinkerblox 22:08

28 روز پیش22:08

22:08

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 processing. Their mission: bring intelligence to where the action happens – directly on devices at the edge. The realization that sparked TinkerBlox came from observing industrial OEMs struggling with cloud-dependent architectures for their "greasy machines." While cloud excels for cloud-native applications, forcing these technologies onto edge devices creates bottlenecks, latency issues, and unnecessary costs. As Anoop explains, "Edge is tomorrow" – not just because of technological evolution, but because practical applications demand localized intelligence that cloud architectures can't efficiently provide. What makes TinkerBlox unique is their approach to standardization and orchestration for the heterogeneous edge. Drawing inspiration from how cloud providers standardized server operations, they're creating reference architectures that respect edge constraints while enabling interoperability. We hear fascinating examples from automotive systems transitioning to vehicle-to-everything (V2X) communication and defense applications where drone swarms need resilient distributed leadership capabilities when individual units fail. Rather than selling directly to end customers, TinkerBlocks positions itself as the "secret ingredient" enabling system integrators and solution providers to deliver superior edge performance. Curious about how edge computing might transform your industry? This conversation illuminates how purpose-built edge intelligence can overcome the scalability challenges that have limited IoT adoption. Subscribe to our podcast for more insights on emerging technologies that are reshaping how we interact with the physical world. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
How embedUR is bridging the gap between embedded development and AI with Rajesh Subramanian 17:49

۵ weeks پیش17:49

17:49

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 connectivity specialists to edge AI innovators. Founded in 2004 to accelerate embedded product development, EmbedUR has positioned itself at the fascinating intersection where traditional embedded engineering meets artificial intelligence. This convergence creates unique challenges – embedded developers understand hardware constraints while AI engineers work in high-level abstractions. Bridging this gap requires careful training, collaboration, and a deep understanding of both worlds. The real magic happens when we see edge AI in action. Imagine headphones that filter background noise without cloud connectivity, privacy sensors that recognize you without capturing detailed facial images, or coffee machines that remember your preferences just by detecting your presence. These aren't futuristic concepts but working demonstrations EmbedUR has created with partners like STMicro, Synaptics, and NXP. What makes these implementations particularly valuable is their independence from cloud connectivity, enhancing both privacy and security. Yet commercializing edge AI presents significant hurdles. The journey from a 96% accurate demo to a 99% reliable product involves months of testing across diverse environments and user populations. As Rajesh points out, "Your model is only as good as your dataset," highlighting the critical importance of data curation. Through their Model Nova platform and global partnerships, EmbedUR is helping companies navigate this complex transition from prototype to market-ready product. Ready to explore how intelligence at the edge might transform your industry? The revolution is already underway. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
How Weeteq is Revolutionizing Microcontroller Technology for Industrial Automation 20:30

۶ weeks پیش20:30

20:30

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 approaches that process data at the device level, WeTech's innovation works within the microcontroller itself, detecting and responding to error signals in less than one-tenth of a millisecond. This isn't just incremental improvement; it's challenging fundamental assumptions about what's possible at the lowest levels of our technology stack. The implications are profound across multiple industries. For industrial automation, WeTech's technology optimizes motor performance without requiring expensive hardware replacements. In electric vehicles, it extends range by reducing energy consumption and minimizing stress on traction motors. Even safety-critical systems in autonomous vehicles benefit from their comprehensive monitoring capabilities. All this comes from a lightweight implementation that works with existing infrastructure - no ripping out and replacing required. Martin also shares insights into Scotland's vibrant technology ecosystem, tracing his journey from Honeywell to startup founder and highlighting how universities like Strathclyde are fueling innovation in everything from robotics to renewable energy. It's a reminder that groundbreaking technological advances aren't limited to Silicon Valley or other well-known tech hubs. Ready to discover how ultra-edge computing might transform your industry? Listen now and glimpse the future of real-time system optimization. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
From Cloud to Edge: NXP's AI Journey with Ali Ors 20:40

۷ weeks پیش20:40

20:40

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 a decade in the AI space, NXP has developed a comprehensive approach that doesn't position edge against cloud, but rather sees them as complementary forces. "We're not trying to make AI easy," Trescot explains, "we're trying to make it easier" for developers to harness AI capabilities in resource-constrained environments. This philosophy drives their hardware development and software enablement strategy, allowing customers across automotive, industrial, and IoT sectors to deploy sophisticated AI solutions where they're needed most. Perhaps most fascinating is NXP's advancement in bringing generative AI to the edge. Their imx9.5 processor now supports Large Language Models and Vision Language Models with up to 8 billion parameters, shifting the primary constraint from computation to memory limitations. This capability is already finding practical applications in conversational interfaces and scene understanding across industries, where hallucination-free, fact-based responses are non-negotiable. With their pending Kinara acquisition and active participation in the Edge AI Foundation, NXP continues to expand their ecosystem and push the boundaries of what's possible at the intelligent edge. Curious about how edge AI could transform your industry? Dive into this episode to discover the silicon that's making it happen. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
From Arduino to AI: A 20-Year Journey with David Cuartielles 22:57

۸ weeks پیش22:57

22:57

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 revolution. David takes us through Arduino's remarkable journey, sharing how a project named after an Italian king (and a local coffee shop) has grown to become the foundation of countless innovations worldwide. What began as an attempt to democratize basic electronics—making it less expensive and complicated "to just do something that would detect pressing a button and turning on a light"—has evolved into sophisticated platforms supporting edge AI and tiny machine learning applications. The conversation reveals how Arduino has kept pace with technological advancement, moving from basic microcontrollers to powerful Linux computers that can run complex applications and be updated over the air. We explore the practical applications of edge AI in industrial settings, where Arduino enables cost-effective, incremental improvements that deliver significant impacts. As David explains, sometimes the simplest implementations—like smart lamps or Roomba vacuum robots—prove most effective in the real world. Particularly inspiring is Arduino's commitment to global education, with David sharing insights from a recent DyniML workshop in Malawi that showcased the extraordinary talent and enthusiasm of participants. From manufacturing facilities in Italy and India to offices in Austin and educational initiatives across continents, Arduino continues to democratize technology access worldwide. Whether you're a longtime Arduino user, an AI enthusiast interested in edge computing, or simply curious about how small technologies can create massive impact, this episode offers valuable insights into the past, present, and future of one of technology's most influential platforms. Subscribe now and join us as we explore how Arduino continues to empower creators and innovators across the globe. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
From Sensors to Solutions: The Future of Edge AI with Chad Lucien of Ceva 17:06

۹ weeks پیش17:06

17:06

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 computing. Rather than focusing solely on neural processing, they've strategically built solutions around what Chad Lucien describes as the three pillars of edge AI: connectivity, sensing, and inference. This comprehensive vision has positioned them as the industry's leading Bluetooth IP licensor while developing sophisticated DSP solutions and a scalable NPU portfolio that ranges from modest GOPS to an impressive 400 TOPS. The secret to Ceva's effectiveness lies in their deep integration of hardware and software expertise. "The software is becoming the definition of the product," notes Lucien, explaining how their deep learning applications team directly influences hardware specifications. This software-first perspective has created solutions perfectly tailored for low-power, small form factor devices across diverse applications. From earbuds and health trackers to consumer robots and smart appliances, SIVA's fully programmable solutions handle everything from neural network computation to DSP workloads and control code. Most exciting is SIVA's leadership in the Audio ML renaissance through their work with the EDGE AI FOUNDATION's Audio Working Group. As audio applications shift from traditional DSP implementations to neural strategies, we're witnessing transformative capabilities in speech enhancement, anomaly detection, sound identification, and edge-based natural language processing. Discover how Ceva is providing the essential "picks and shovels" for the AI gold rush and why collaboration remains the key to unlocking the full potential of intelligence at the edge. Subscribe to hear more partner stories shaping the future of edge AI! Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
EDGE AI Partner: David Aronchick of Expanso 21:51

10 weeks پیش21:51

21:51

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, David reveals how these experiences led him to tackle a persistent challenge: how do you leverage container technologies and ML models outside traditional data centers? While cloud platforms excel at centralized workloads, businesses increasingly need computing power in retail locations, manufacturing facilities, and smart city infrastructure. Expanso's elegantly named Bacalhau project (Portuguese for cod, a clever nod to "Compute Over Data") offers a solution by providing reliable orchestration of workloads across distributed locations. Their lightweight Go binary runs on virtually anything from Raspberry Pis to sophisticated edge servers, managing the delivery and execution of jobs while gracefully handling connectivity disruptions that would cause traditional systems to fail. David makes a compelling case for edge computing with a simple physical reality: even 100,000 years from now, the speed of light will still impose a 45-millisecond latency between LA and Boston. This unchangeable constraint, combined with data transfer costs and regulatory requirements, makes local processing increasingly essential. For organizations struggling with high telemetry bills, Expanso confidently promises at least 25% cost reduction—or they work for free. Whether you're managing satellite networks, underwater cameras for aquaculture, or thousands of retail locations, this conversation illuminates how the future of computing involves bringing intelligence to where data lives rather than constantly shipping bytes across networks. Join us to discover how this paradigm shift is making AI more effective in the physical world. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
Bringing Generative AI to Your Pocket: The Future of Edge Computing 27:10

11 weeks پیش27:10

27:10

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's creative powers directly to our devices. Building on the foundation laid by the tiny ML movement, Generative EDGE AI represents a fundamental shift in how we'll interact with technology. The benefits are compelling: complete privacy as your data never leaves your device, lightning-fast responses without internet latency, independence from network connections, and significant cost savings from reduced cloud computing needs. The applications span far beyond convenience. For people with disabilities, it means having image captioning that works anywhere, even without internet. For photographers, it's like having a professional editor built right into your camera. In healthcare, it enables diagnostics while keeping sensitive patient data secure and accessible even in areas with poor connectivity. The technical achievements making this possible are equally impressive. Researchers have shrunk massive AI models to run efficiently on everyday devices, from visual question answering systems that respond in milliseconds to text-to-speech engines that sound remarkably natural. They're even making progress bringing text-to-image generation and small language models directly to smartphones. As we explore these breakthroughs, we consider the profound implications of truly intelligent devices that can learn, adapt, and make decisions autonomously. What happens when our technology not only understands but creates and acts independently? The silent AI revolution happening in our hands is set to transform our relationship with technology in ways we're just beginning to comprehend. Ready to understand the future that's already arriving? Listen now and glimpse the world where intelligence lives at your fingertips, not in distant server farms. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
Audio AI on the Edge with Ceva 59:47

12 weeks پیش59:47

59:47

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 learning on resource-limited hardware. First, Environmental Noise Cancellation (ENC) addresses the critical need for clear communication in noisy environments. Rather than accepting the limitations of traditional approaches that require multiple microphones, SIVA's single-microphone solution leverages deep neural networks to achieve superior noise reduction while preserving speech quality—all with a model eight times smaller than conventional alternatives. The conversation then shifts to voice interfaces, where Text-to-Model technology is eliminating months of development time by generating keyword spotting models directly from text input. This innovation allows manufacturers to create, modify, or rebrand voice commands instantly without costly data collection and retraining cycles. Each additional keyword requires merely one kilobyte of memory, making sophisticated voice interfaces accessible even on the smallest devices. Throughout the discussion, Daniel reveals the technical challenges and breakthroughs involved in optimizing these models for production environments. From quantization-aware training and SVD compression to knowledge distillation and framework conversion strategies, we gain practical insights into making AI work effectively within severe computational constraints. Whether you're developing embedded systems, designing voice-enabled products, or simply curious about the future of human-machine interaction, this episode offers valuable perspective on how audio AI is becoming both more powerful and more accessible. The era of intelligent listening devices is here—and they're smaller, more efficient, and more capable than ever before. Ready to explore audio AI for your next project? Check out SIVA's YouTube channel for demos of these technologies in action, or join the Edge AI Foundation's Audio Working Group to collaborate with industry experts on advancing this rapidly evolving field. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
Garbage In, Garbage Out - High-Quality Datasets for Edge ML Research 21:17

13 weeks پیش21:17

21:17

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 realistic evaluation in this area. To address this, the Foundation aims to create and maintain a repository of production-grade, diverse, and well-annotated datasets for tiny and edge ML use cases, enabling fair comparisons and the advancement of the field. They emphasize community involvement in contributing datasets, providing feedback, and establishing best practices for optimization. Ultimately, this initiative seeks to level the playing field for edge AI research by providing the necessary resources for accurate benchmarking and innovation. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

EDGE AI POD

1
Edge AI Investing Essentials 56:00

14 weeks پیش56:00

56:00

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 Ventures bluntly states, "The first thing we're looking for is customers, second is customers, and third is customers." While many founders obsess over technology, successful investments begin with understanding whose job is changed by your solution and who will pay for that change. The conversation shifts to efficiency as "the new currency" in edge computing. David Wyatt, formerly of NVIDIA, highlights technologies achieving 100x greater efficiency than traditional approaches, pointing to innovations that challenge conventional silicon-based computing. Meanwhile, Murata's corporate venture team emphasizes material science innovations that enable more efficient processing, sensing, and power management at the edge. What makes an ideal founding team? The panel describes the powerful combination of a "hacker" (technical expert) and a "hustler" (business-focused leader) who together can bridge the gap between technological innovation and market demands. This complementary expertise proves especially critical in edge AI, where technical constraints meet real-world implementation challenges. The most sobering insights emerge when discussing startup failures. Running out of cash tops the list, often resulting from scaling too quickly or misallocating resources. One panelist cuts through the hype with brutal clarity: "You're not in business when you're spending money. You're in business when you're making money." Whether you're building, investing in, or partnering with edge AI companies, this discussion offers a roadmap for navigating an increasingly complex landscape where efficiency, customer focus, and strategic vision determine which innovations will ultimately survive and thrive. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

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