From tinyML to the edge of AI: Introducing the EDGE AI FOUNDATION

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

How to Be a Better Human

1
How to make the most of a finite life (w/ Oliver Burkeman) 40:22

26 weeks پیش40:22

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40:22

There’s only so much you can do in a week – or, according to Oliver Burkeman, in the roughly 4,000 weeks the average human lives. Oliver is a journalist and author of the books Four Thousand Weeks: Time Management for Mortals, Meditations for Mortals, and the newsletter “The Imperfectionist.” Chris and Oliver discuss the paradox of why change can only occur once we accept that we might not be able to change. Oliver also shares how life’s mishaps can become our most treasured memories and why sharing your imperfections is an act of generosity. For the full text transcript, visit go.ted.com/BHTranscripts For the full text transcript, visit go.ted.com/BHTranscripts Want to help shape TED's shows going forward? Fill out our survey ! For a chance to give your own TED Talk, fill out the Idea Search Application: ted.com/ideasearch . Interested in learning more about upcoming TED events? Follow these links: TEDNext: ted.com/futureyou Hosted on Acast. See acast.com/privacy for more information.…

حدود یک سال پیش 14:09

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Discover how the EDGE AI FOUNDATION is evolving from its roots in the tinyML Foundation to becoming a central hub for innovation and collaboration. Learn how initiatives like EDGE AI Labs and the EDGE AIP program are bridging the gap between academia and industry, training future AI leaders while tackling the ethical challenges of responsible AI development.
Explore the transformative potential of generative AI on edge devices, from providing vital healthcare diagnostics in remote areas to enabling adaptive robotics in factories. We'll highlight compelling reasons for companies to engage with the Edge AI Foundation, offering unparalleled access to cutting-edge research, top talent, and a voice in shaping the industry's future. As we navigate through real-life scenarios and ethical considerations, you’ll see why the urgency and opportunity surrounding Edge AI is something you don't want to miss.
Join us on this journey to ensure the benefits of AI are shared widely and responsibly by visiting edgeaifoundation.org.

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Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

فصل ها

1. Unlocking the Potential of Edge AI (00:00:00)

2. Empowering Society With Edge AI (00:07:42)

3. Exploring Edge AI Foundation (00:18:35)

51 قسمت

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

From tinyML to the edge of AI: Introducing the EDGE AI FOUNDATION

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. Unlocking the Potential of Edge AI (00:00:00)

2. Empowering Society With Edge AI (00:07:42)

3. Exploring Edge AI Foundation (00:18:35)

51 قسمت

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

همه قسمت ها

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

۴ روز 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…

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

۹ روز 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…

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

16 روز 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…

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

23 روز 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…

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

30 روز 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…

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EDGE AI Partner: David Aronchick of Expanso 21:51

۵ 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…

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

۶ 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…

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Audio AI on the Edge with Ceva 59:47

۷ 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…

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

۸ 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…

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Edge AI Investing Essentials 56:00

۹ 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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Beyond the Edge: Cloud and AI Convergence 13:47

10 weeks پیش13:47

13:47

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 orchestration from the cloud down to edge devices. Instead of focusing on restrictive standards, the piece emphasizes the importance of developing best practices and fostering collaboration to accelerate the deployment and value of edge AI solutions. The ultimate vision is a future where AI-powered, connected silicon at the edge becomes the default, supported by cloud-based DevOps principles. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

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Investing In The Edge: A VC Panel from AUSTIN 2025 42:43

11 weeks پیش42:43

42:43

Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

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The Pipeline Is Stalling: America's Declining Innovation Edge 13:41

12 weeks پیش13:41

13:41

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 conversation dives deep into Harvard University Professor Vijay Janapa Reddi's compelling analysis of this critical situation. The statistics are striking: researchers have lost 26% of their purchasing power since 2014, forcing tough choices about graduate positions, equipment purchases, and research directions. Meanwhile, 79% of computer science graduate students are international, underscoring our reliance on global talent. When 55% of billion-dollar American startups have immigrant founders, restrictive immigration policies amount to what experts call "national self-sabotage." The impacts extend far beyond elite institutions. America's innovation ecosystem encompasses land-grant universities, HBCUs, community colleges, and state flagships - all dependent on stable federal support. The Edge AI Foundation, where Professor Reddy serves on the board, exemplifies one promising response: creating structured collaboration between universities and industry on emerging technologies like neuromorphic computing and edge-based AI. This approach helps bridge the crucial gap between academic research and commercial application. Revitalizing our innovation ecosystem demands a coordinated strategy: expanded industry consortia with federal matching funds, innovation co-labs on university campuses, dedicated STEM green cards, streamlined visa processes, and predictable research funding increases. The stakes couldn't be higher - our economic future and technological leadership hang in the balance. How might you contribute to rebuilding America's innovation pipeline? Explore more through the People's Pledge for American Higher Education and join the conversation about securing our innovative future. ➡️ Visit HERE to read The Pipeline Is Stalling whitepaper ➡️ Visit HERE to sign the pledge Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

43 weeks پیش30:37

30:37

Unlock the secrets of ultra-efficient AI with Julian Musman from ETH Zurich, as we explore the cutting-edge world of smart glasses. Discover how Julian and his team have mastered the art of deploying powerful AI algorithms on the tiniest of devices, tackling the monumental challenge of performing object detection on microcontrollers. Tainissimo YOLO, a breakthrough network, is not just a marvel of engineering but a testament to the balance between computational power, network size, and battery life, revolutionizing the way smart glasses operate without relying on the cloud. Join us as we unpack the hardware innovations behind these intelligent glasses, featuring components like the NRF53 microcontroller and the GAP9 neural engine, meticulously designed for energy efficiency and high-speed performance. With an astonishing end-to-end latency of 18 frames per second, these glasses promise all-day functionality on a single charge. Julian sheds light on the intricate harmony of PCB design and neural network architecture and explores the potential of advanced convolutional changes, all while emphasizing the strategic choice to remain loyal to traditional networks for unmatched performance with hardware accelerators. Get ready for an insightful journey into the future of AI-powered wearable technology! Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…

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