Africa-focused technology, digital and innovation ecosystem insight and commentary.
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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
مشابه EDGE AI POD
Show notes are at https://stevelitchfield.com/sshow/chat.html
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Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Rae Johnston and guests take a fun, deep dive into how technology is reshaping our lives.
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WSJ’s Bold Names brings you conversations with the leaders of the bold-named companies featured in the pages of The Wall Street Journal. Hosts Tim Higgins and Christopher Mims speak to CEOs and business leaders in interviews that challenge conventional wisdom and take you inside the decisions being made in the C-suite and beyond.
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Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
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The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
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We help founders make something people want.
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This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
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Redefining AI is the 2024 New York Digital Award winning tech podcast! Discover a whole new take on Artificial Intelligence in joining host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and ...
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Three nerds discussing tech, Apple, programming, and loosely related matters.
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Netflix Sports Club Podcast
America’s Sweethearts: Dallas Cowboys Cheerleaders is back for its second season! Kay Adams welcomes the women who assemble the squad, Kelli Finglass and Judy Trammell, to the Netflix Sports Club Podcast. They discuss the emotional rollercoaster of putting together the Dallas Cowboys Cheerleaders. Judy and Kelli open up about what it means to embrace flaws in the pursuit of perfection, how they identify that winning combo of stamina and wow factor, and what it’s like to see Thunderstruck go viral. Plus, the duo shares their hopes for the future of DCC beyond the field. Netflix Sports Club Podcast Correspondent Dani Klupenger also stops by to discuss the NBA Finals, basketball’s biggest moments with Michael Jordan and LeBron, and Kevin Durant’s international dominance. Dani and Kay detail the rise of Coco Gauff’s greatness and the most exciting storylines heading into Wimbledon. We want to hear from you! Leave us a voice message at www.speakpipe.com/NetflixSportsClub Find more from the Netflix Sports Club Podcast @NetflixSports on YouTube, TikTok, Instagram, Facebook, and X. You can catch Kay Adams @heykayadams and Dani Klupenger @daniklup on IG and X. Be sure to follow Kelli Finglass and Judy Trammel @kellifinglass and @dcc_judy on IG. Hosted by Kay Adams, the Netflix Sports Club Podcast is an all-access deep dive into the Netflix Sports universe! Each episode, Adams will speak with athletes, coaches, and a rotating cycle of familiar sports correspondents to talk about a recently released Netflix Sports series. The podcast will feature hot takes, deep analysis, games, and intimate conversations. Be sure to watch, listen, and subscribe to the Netflix Sports Club Podcast on YouTube, Spotify, Tudum, or wherever you get your podcasts. New episodes on Fridays every other week.…
Recap of the "Beyond Chatbots - The Journey of Generative AI to the Edge"
Manage episode 457626450 series 3574631
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
Get ready for the recap of the Beyond Chatbots - The Journey of Generative AI to the Edge - exploring the frontier of Generative AI and edge technology with Davis Sawyer, Danilo Pau and Pete Bernard as they discuss the dynamic innovations transforming these fields. We uncover the fascinating shift from cloud-based proof-of-concepts to the compelling reality of edge solutions. This conversation dives into the ever-evolving landscape of generative AI, particularly in edge environments where cost and power efficiency reign supreme. From automotive breakthroughs to advanced memory optimization techniques, discover how these innovations are redefining the role of AI in our world.
Listen in as we dissect the gravitational pull towards edge solutions with insights from recent industry research and captivating discussions. Dave shares intriguing observations on AI as crucial infrastructure, likening it to essential utilities that promise lasting impacts across sectors. As we look ahead, the conversation turns to the future of AI in manufacturing and the exciting potential for AGI-capable equipment. With Foundation partners like STMicroelectronics and NXP at the helm, the potential for edge AI advancements is limitless. Join us for an engaging exploration of the trends shaping the future of AI and edge computing.
Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org
49 قسمت
اشتراک گذاریManage episode 457626450 series 3574631
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
Get ready for the recap of the Beyond Chatbots - The Journey of Generative AI to the Edge - exploring the frontier of Generative AI and edge technology with Davis Sawyer, Danilo Pau and Pete Bernard as they discuss the dynamic innovations transforming these fields. We uncover the fascinating shift from cloud-based proof-of-concepts to the compelling reality of edge solutions. This conversation dives into the ever-evolving landscape of generative AI, particularly in edge environments where cost and power efficiency reign supreme. From automotive breakthroughs to advanced memory optimization techniques, discover how these innovations are redefining the role of AI in our world.
Listen in as we dissect the gravitational pull towards edge solutions with insights from recent industry research and captivating discussions. Dave shares intriguing observations on AI as crucial infrastructure, likening it to essential utilities that promise lasting impacts across sectors. As we look ahead, the conversation turns to the future of AI in manufacturing and the exciting potential for AGI-capable equipment. With Foundation partners like STMicroelectronics and NXP at the helm, the potential for edge AI advancements is limitless. Join us for an engaging exploration of the trends shaping the future of AI and edge computing.
Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org
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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…
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…
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…
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…
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…
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…
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…
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…
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…
Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org
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…
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 discussion, they reveal that success depends less on technical prowess and more on solving real business problems with clear ROI. As one panelist bluntly states, "The customer doesn't care about MQTT or AMQP protocols—nobody cared. They care about outcomes." The conversation weaves through crucial territory—the boundary between IT and OT systems, the evolving relationship between cloud and edge architectures, and the stark reality of skills shortages in the semiconductor industry. With semiconductor companies doubling in size over the next eight years while facing an aging workforce, the panel highlights urgent needs for reskilling and education initiatives. Perhaps most provocatively, the panel addresses the uncomfortable truth about AI adoption: "How many employees is your technology going to replace?" This question, frequently asked by VCs, underscores the economic drivers pushing Edge AI forward in an era of changing workforce demographics and productivity challenges. For small and medium businesses, there's both opportunity and risk as AI becomes embedded in SaaS offerings and purpose-built solutions emerge for specific industry problems. The panelists predict that Edge AI might actually benefit smaller players more than large enterprises by democratizing access to sophisticated capabilities through platform-based approaches. Whether you're developing Edge AI solutions, investing in the space, or considering adoption for your business, this discussion provides essential context for navigating the significant opportunities and challenges ahead. Subscribe to hear more industry experts cut through the noise and deliver practical wisdom for the intelligent edge. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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 industry stands at a fascinating crossroads where artificial intelligence capabilities are pushing beyond traditional cloud environments into battery-powered edge devices. As our podcast guest explains, this transition faces substantial hurdles: while cloud-based models expand from millions to trillions of parameters, embedded systems must dramatically reduce their footprint from terabytes to gigabytes while still delivering meaningful AI functionality. With projections showing IoT devices consuming over 30 terabit hours of power by 2030 and generating 300 zettabytes of data, the need for local processing has never been more urgent. For developers creating wearable technology like smart eyewear, constraints become particularly challenging. Weight distribution, battery life, and computing power must all be carefully balanced while maintaining comfort and style. The hardware architecture required for these applications demands innovative approaches: shared bus fabrics that enable different execution environments, strategic power management that activates high-performance cores only when needed, and neural processing units capable of handling transformer operations for generative AI workloads. Most impressively, current implementations demonstrate YOLO object detection running at just 60 milliamps—easily within battery operation parameters. The $30 billion embedded AI market represents a tremendous opportunity for innovation, but also requires robust software ecosystems that help traditional microcontroller customers without AI expertise navigate this complex landscape. As next-generation devices begin supporting generative capabilities alongside traditional CNN and RNN networks, we're witnessing the dawn of truly seamless human-machine interfaces. Ready to explore how these technologies might transform your industry? Listen now to understand the future of computing at the edge. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
1 The Future of Domain-Specific AI Search Lies in Targeted Agent Systems 1:00:46
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پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدImagine your edge device having the ability to search for exactly what you need, exactly when you need it, without hallucinations or irrelevant information. That's the promise of Snipe Search's agent orchestration system, presented by co-founder Wassim Kezai in this eye-opening EDGE AI TALKS session. Most organizations struggle when implementing RAG systems with their corporate data. The truth is, unstructured corporate knowledge is often messy and inconsistent, leading to unreliable AI responses. Semantic matching issues in traditional retrieval systems further compound these problems, especially when deployed at the edge where specific, accurate information is crucial. Wasim unveils an innovative approach that deploys specialized AI "detective" agents to search for information from authoritative sources. Unlike brute force search methods, these agents intelligently target reliable information based on hierarchical importance. Web agents crawl and cross-reference websites, image agents find relevant visuals, scholar agents specialize in academic information, and video agents can even pinpoint the exact timestamp in video content that answers your query. What sets this approach apart is its adaptability to domain-specific knowledge and verification frameworks. Companies can customize how information is validated based on their standards, ensuring relevance and accuracy. While traditional RAG systems respond in seconds, Snipe Search's 30-second average response time delivers significantly higher quality information – a worthwhile trade-off for mission-critical applications. The platform integrates easily with any LLM or chatbot through Docker, API, or direct integration, making it accessible for organizations of all sizes. As edge computing continues to grow, having efficient, accurate search capabilities becomes increasingly important for reducing cloud dependencies, enhancing privacy, and delivering better user experiences. Ready to transform how your edge devices access and utilize knowledge? Explore Snipe Search's platform launching in the coming weeks and discover how intelligent search can enhance your edge AI deployments. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
The crisis of ocean plastic pollution demands innovative solutions, and Brad's team at Ozone Technologies is answering the call with cutting-edge AI technology. Their collaboration with The Ocean Cleanup has yielded a remarkable system that's transforming how we detect and map marine debris. At the heart of this solution is ADIS (Autonomous Debris Imaging System) – a compact, rugged camera powered by edge AI that mounts to merchant vessels traveling across our oceans. Using sophisticated computer vision models running on NXP i.MX 8M Plus processors, these devices scan the water's surface, distinguishing tiny pieces of floating plastic from wave crests even in challenging marine conditions. What makes this approach revolutionary is its scalability. Rather than requiring dedicated research vessels, ADIS piggybacks on existing shipping routes, creating an expanding network of detection points across global waters. The system operates completely autonomously, requiring minimal power and no continuous internet connection. It stores detection data onboard, uploading it only when ships return to port. The technical challenges overcome by Brad's team are impressive – from waterproofing the hardware to withstand immersion and pressure spray to developing specialized tracking algorithms that can differentiate persistent floating debris from transient wave patterns. Perhaps most remarkable is how they've simplified deployment with fool-proof installation instructions that require no technical expertise from ship crews. This mapping data serves a critical purpose, helping The Ocean Cleanup optimize their System 3 recovery operations in the Great Pacific Garbage Patch. Their massive 2.2km floating barrier (nicknamed "Josh") funnels debris into collection zones, but knowing where to deploy is essential for efficiency. ADIS provides that critical intelligence. Beyond mapping, we're seeing the completion of a virtuous cycle as recovered plastic finds new life through creative recycling – including limited-edition Coldplay vinyl records made from ocean plastic. Want to see more innovations tackling our planet's pressing environmental challenges? Join us at the upcoming AJI Foundation Summit in Austin or explore edgifoundation.org/events for opportunities to connect with leaders in this space. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
The artificial intelligence landscape is undergoing a fundamental shift – moving away from simply compressing cloud models to fit edge devices toward developing AI that's truly "born at the edge." Davis Sawyer, AI Product Marketing Manager at NXP Semiconductors, guides us through this transformation and reveals how NXP is revolutionizing the way intelligence is built into our everyday devices. Sawyer begins by redefining what we mean by "the edge" – a vast spectrum ranging from network infrastructure handling millions of connections down to the dozens of microcontrollers in modern home appliances and vehicles. What makes edge AI unique isn't just about size constraints, but the fundamentally different operating environment. While cloud models enjoy virtually unlimited power and standardized computing environments, edge devices face strict limitations in form factor, power consumption, and thermal management. The heart of NXP's approach is their EIQ software stack – a comprehensive toolkit that spans their entire product range from low-power MCUs to high-performance MPUs. Two innovations stand out as particularly revolutionary: Time Series Studio brings AutoML capabilities to sensor data, enabling non-AI experts in manufacturing, energy, and other sectors to build powerful anomaly detection models without deep machine learning expertise. Meanwhile, their approach to generative AI uses "RAG on steroids" (Retrieval Augmented Generation) to create systems that are not only compact enough for edge deployment but also inherently more secure and private. The real-world impact is already evident in applications ranging from precision agriculture robots to healthcare systems that combine multimodal sensing for contact-free patient monitoring. Perhaps most impressive is the rapid pace of innovation – within just months, NXP's edge-optimized language models have seen response times drop from two seconds to less than half a second, making conversational interfaces truly viable on embedded devices. Looking ahead, Sawyer predicts we're moving toward a new era where edge AI becomes increasingly agentic – focusing not just on human-machine interfaces but on optimizing machine-to-machine workflows in factories, robotics, and automation. Join us to discover how the future of intelligence isn't trickling down from the cloud, but rising up from the edge where our data is born. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
When SoftBank's team was approached by Japanese fishermen struggling with declining catches and inefficient practices, they knew technology could offer a solution. Their response: an innovative Edge AI system that transforms traditional aquaculture through sophisticated computer vision running directly on smartphones. Japan's fishing challenges are emblematic of global food security concerns. With the country's self-sufficiency rate at just 38% and fish catches halved from peak levels, the stakes couldn't be higher. Traditional aquaculture has relied heavily on intuition rather than data, making it nearly impossible to optimize feeding (which represents 60-70% of operational costs) or accurately monitor fish populations. The SoftBank and AIZip collaboration tackles these challenges through a remarkable edge computing approach. What makes their solution particularly groundbreaking is how it functions in environments with zero infrastructure—no power supply, no connectivity, and corrosive saltwater everywhere. By developing density-based crowd counting AI models that run efficiently on edge devices, they've created a system that can count hundreds of fish with 96% accuracy in clear water and 86% accuracy in muddy conditions. Perhaps most fascinating is their development process. Unable to collect sufficient real-world training data underwater, the team developed a sophisticated Unity-based simulation that generates realistic fish behavior under various conditions. This simulator provided 65% of their training data, complemented by manual observation from divers who documented actual fish behavior at different depths and feeding stages. The result is an AI system that not only counts fish but can potentially detect hunger levels, health issues, and optimize feeding schedules. This CES 2024 Innovation Award-winning technology demonstrates how Edge AI can transform traditional industries without requiring massive infrastructure investments. By bringing intelligence directly to the point of data collection, even in the most challenging environments, we're witnessing the beginning of a new era in sustainable food production. Whether you're involved in agriculture, environmental monitoring, or any field requiring intelligent sensing in harsh conditions, the lessons from this underwater AI revolution could transform how you approach your next challenge. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Career EDGE: Navigating the Job Market in the Age of Edge AI 1:28:56
1:28:56 پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شد1:28:56
پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدFrom 5V Tech and the EDGE AI FOUNDATION, unlock the potential of Edge AI and transform your career path with insights from leaders in the field. Join our engaging conversation featuring Luke Perrins from 5V, Gregory from Infineon Technologies, and Professor Eiman Kanjo from Nottingham Trent University, as we uncover how Edge AI is revolutionizing industries with its unique ability to operate independently of cloud connectivity. Learn from seasoned professionals like Stephen Davis, an executive leadership coach, Kari, a corporate recruiter, and Martin MacDonald, COO at AI startup Weteeq, about the innovative applications and benefits of this technology, including improved latency and enhanced device autonomy. Explore the diverse and dynamic skill set essential for success in the Edge AI realm. Our experts discuss the importance of mastering embedded software, programming, and hardware understanding, while also emphasizing cross-disciplinary collaboration and soft skills like communication. Whether you're a graduate or a seasoned professional, discover actionable advice on crafting standout resumes and CVs tailored to this evolving field, as well as strategies to showcase your personal projects and achievements effectively. Prepare to stand out in your job applications and interviews with expert tips on leveraging networking opportunities and professional platforms like LinkedIn. Discover the critical role of personal branding and cultural understanding, and gain insights into future careers in Edge AI, where versatility and innovation are key. Tune in to this insightful episode packed with practical strategies to help you excel in the cutting-edge world of Edge AI. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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What if the future of Wi-Fi could pinpoint your location down to 30 centimeters? Join us as Joseph Chueh from National Tsinghua University unveils the astonishing potential of Wi-Fi sensing when integrated with machine learning. Joseph brings his wealth of experience in semiconductor research and business development to the table, discussing the revolutionary application of existing frequencies like 2.4G and 5G for tasks including human activity recognition and intruder detection. This episode unpacks how Channel State Information (CSI) is at the heart of extracting precise data for machine learning, while also addressing the technical hurdles of hardware optimization and interference management. Discover how increasing the degrees of freedom in Wi-Fi systems can be a game-changer for radio frequency technology. Joseph explains how adding more channels or phase coordination expands the sample space for channel information, paving the way for more efficient decision-making. We explore solutions like transmitter-side coding and the impact of transmission models like OFDM and OFDMA on Wi-Fi sensing capabilities. Joseph paints a vivid picture of a future where Wi-Fi sensing becomes not only more accurate but also more cost-effective and accessible, making it a promising feature in both today's Wi-Fi technologies and upcoming 6G systems. Whether for robotics or enhancing room-scale environments, the insights shared in this episode offer a glimpse into an exciting wireless frontier. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
How can we revolutionize everyday objects into smarter, more responsive entities? Join us in this exciting episode as we explore the cutting-edge world of Edge AI, fresh from the vibrant showcases at CES 2025. We promise an in-depth look at the future of technology deployment with our special guests Eric and John from EmbedUR. With their extensive expertise in embedded products, they bring a fascinating perspective on the importance of blueprints for tech commercialization in today's rapidly evolving landscape. Our conversation with Eric Smiley and John Marconi introduces the innovative ModelNova, a transformative tool designed to speed up the journey from ideation to proof of concept for tiny edge AI devices. Discover how ModelNova's curated model zoo and datasets can empower developers, ensuring efficient performance even under resource constraints. We dive into practical insights like community contributions, adapting large AI models for small devices, and how tools like Model Nova democratize access across various chip platforms, turning ambitious ideas into reality. This episode doesn't just stop at the technical nuances; it goes further into the realm of edge AI product development. We share a compelling story of transforming a bicycle helmet camera with object detection to enhance rider safety, illustrating the complexities of selecting the right hardware and the critical role of blueprints in this journey. From MLOps integration to cloud connectivity for continuous updates, our discussion emphasizes collaboration within the tech ecosystem to tackle the challenges of AI deployment. Tune in to learn how these advancements are not only reshaping technology but also enriching everyday life by making objects around us smarter and more responsive. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
NXP Semiconductors is revolutionizing the integration of AI within embedded systems, focusing on enhanced tools and dedicated acceleration. Their latest innovations like the EIQ Software Stack and EIQ Time Series Studio are designed to streamline AI deployment, bridging the gap for developers transitioning into AI methodologies. • Overview of NXP’s focus on automotive, industrial, and smart home markets • Introduction of new AI-accelerated MCUs and application processors • The importance of effective data management and compute efficiency • Discussion of the EIQ Software Stack and EIQ Toolkit for developers • Insights into the EIQ Time Series Studio for automated model generation • Highlights of challenges faced by developers in AI implementation • Key takeaways on NXP's commitment to enhancing edge AI capabilities Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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What if you could deploy AI solutions seamlessly across every platform with just a single stroke? Join us as we explore this intriguing possibility alongside our guest, Odin Chen of Arm, who brings a wealth of experience from his journey from Taiwan to Cambridge. Together, we embark on a journey through the vibrant landscape of Edge AI, tackling its transformative impact on both enterprises and startups. We shine a light on the mantra "write once, deploy everywhere," unraveling its significance in a world where AI's reach is rapidly expanding. Along the way, we confront the challenges of AI deployment, from soaring costs to energy demands, and celebrate the critical role of open-source projects. Discover how technologies spanning image classification to generative AI are revolutionizing industries, while open-source contributions, particularly in Arm architecture and Python optimizations, are paving the way for a more collaborative future. In the second segment, we traverse the vast potential of the AI ecosystem, shedding light on AI frameworks like MediaPipe and ESSEC torch that guide industries toward optimized AI solutions. With Google's AI offerings on the horizon, we introduce a cutting-edge context model for ESSEC torch and delve into key partnerships with Arm technology pioneers such as Alif and HiMAS. These collaborations aim to turbocharge scalable computing solutions and high-efficiency image processing. Excitingly, we unveil our developer program and open software stack, inviting listeners to engage actively and collaborate. Keep your calendars marked for upcoming live demos and panel discussions, promising a firsthand look at the immense potential of AI deployment across diverse sectors. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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Unlock the fascinating world of edge AI technology with insights from Karan Kapoor of Himax Technologies. Discover how Karan and his team are pioneering the development of ultra-low-power AI processors designed for resource-constrained devices. We'll explore their latest innovation, the WE2 processor, which optimizes the balance between model size, speed, energy efficiency, and accuracy. Karan shares the intricacies of integrating hardware and software systems, along with groundbreaking AI applications like facial recognition and keyword spotting, all while staying true to Hymax's mission of making AI cost-effective and accessible for all. In the second segment, we spotlight a transformative partnership that brings Wwiseit2 into Edge Impulse's AI ecosystem. This collaboration is a game-changer, introducing a no-code platform that simplifies data collection and synthetic data generation. We unravel the process from model design to testing, supported by an AutoML feature that ensures precision. With ARM's Ethos U55 powering the AI processor, the episode explores how partnerships with innovators like GrowVision AI are crafting an advanced ecosystem. Developers, stay ahead of the curve by following these cutting-edge developments on platforms like LinkedIn and GitHub. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Discover the cutting-edge world of TinyML and Edge AI with our special guest, Eldar Sido from Renesas. As a key figure in the AI Center of Excellence, Eldar unveils the fascinating challenges and breakthroughs in embedding AI into compact devices like microcontrollers and sensors that are rapidly spreading across the globe. This episode promises an exploration into the dynamic realm of TinyML, focusing on its three foundational pillars: real-time analytics, voice, and vision. Eldar discusses the anticipated double-digit growth of this sector over the next decade, making it a pivotal listen for tech enthusiasts and those curious about the future trajectory of AI technology. Eldar also shares how Renesas, through its acquisition of Reality AI, is enhancing its prowess in real-time analytics and tackling high-frequency sampling rates. With a focus on consultancy, data selection, and sensor placement, Eldar illustrates how only a sliver of the TinyML process is devoted to model development. By integrating Reality AI with the E-Square Studio IDE, Renesas is streamlining workflows to maximize the potential of TinyML. Tune in to understand how TinyML is reshaping industries and what lies ahead for Edge AI applications. This episode is packed with insights and strategies for anyone looking to leverage the power of TinyML in their projects. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Discover how the fusion of cutting-edge technology and human interaction is revolutionizing education and healthcare with Professor Stella Kuei-An Nguyen from National Yangming Chow Tung University. Join us as we explore her innovative work in Human-AI Interaction using Inertial Measurement Units (IMU), and witness the transition of Raboni IMU devices into the transformative Bony AI. Collaborating with giants like TSMC, MIT, and leading hospitals, Professor Nguyen showcases how these advancements are not only elevating coding education but also offering groundbreaking solutions for medical conditions such as Parkinson’s and dementia. These innovations are powered by tiny machine learning algorithms, seamlessly blending sensors and AI processors into user-friendly interfaces that redefine efficiency in educational and healthcare diagnostics. Delve into the world of advanced motion monitoring technology as we delve into the integration of Rabonit, IMU, and the YSI2 AI processor, designed to intelligently track movements. This sophisticated system promises to revolutionize the way we assess physical activity, especially for children in intermediate playing stages. With a specially designed app that extracts and analyzes movement curves, this technology offers invaluable insights that could enhance both educational environments and healthcare sectors. Join us for an insightful journey into how these tools are set to make a broader impact, aiming to enrich lives by providing effective and efficient information. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 EDGE AI BLUEPRINTS: Enhancing Urban Safety with Edge AI Approaches to Pedestrian and Traffic Management 1:00:29
1:00:29 پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شد1:00:29
پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدWhat do rising pedestrian fatalities and the challenges of implementing intelligent transportation systems have in common? In this episode, we’re joined by Davis Sawyer from NXP and Mike "Witt" Whitaker from the City of Lakewood, Colorado, to unpack the complexities of applying edge AI to enhance urban safety. As Witt recounts his pioneering work with autonomous vehicles since the 1990s, we explore the fast-paced evolution of AI technology and its critical role in addressing real-world problems, such as the increasing need for pedestrian safety and efficient traffic management. We take a hard look at the perplexing trend of fatal crashes involving impaired drivers despite a drop in overall traffic incidents. The conversation intensifies as we discuss the doubling of pedestrian fatalities, particularly at night, and the significant challenges posed by underreported impairment and the rise of fentanyl use. Our guests share insights into how collaborations with the police department and meticulous data analysis can reveal hidden patterns, driving the development of more effective municipal safety strategies. Our exploration doesn’t stop there. We also discuss the advancements in detection technologies and the iterative process of refining systems like LiDAR and video to predict pedestrian movements more accurately. This episode offers a deep dive into the complexities and costs of deploying AI models in urban environments, including the importance of ML Ops, the challenge of model retraining, and the role of existing infrastructure in supporting intelligent systems. Join us as we navigate the intricate world of smart city solutions, focusing on the shared goal of safer streets for everyone. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Panel Discussion - EDGE AI TAIPEI - Revolutionizing Edge Computing with AI-Driven Innovations 58:42
Discover the cutting-edge world of AI deployment on edge devices with insights from top experts, including Dr. KC Liu. This episode promises to unravel the complexities of optimizing AI models for devices where memory and computing power are limited. We explore the critical role of model compilers and the innovative strides being made in AIoT sensors, as Matteo Maravita from STMicroelectronics offers an exciting glimpse into the future of machine learning integration into MEMS sensors. Join us as we tackle the pressing need for standardization in the fragmented IoT development landscape. Our esteemed panel delves into the challenges developers face with diverse proprietary technologies from giants like STM, NXP, and Renesas. Hear about potential convergence through model zoos and frameworks, and the unique role of MLPerf Tiny ML in benchmarking AI applications specifically designed for edge devices. Our conversation shines a light on the balance between utilizing common tools and proprietary compilers for optimized performance on specific hardware. Lastly, explore the promising avenues of AI in the realm of robotics and the innovative strategies shaping the future of AI systems. Learn about the layered architecture approach dividing AI systems into sensor network, edge AI, and cloud computing layers, and the potential for a sustainable AI ecosystem through collaboration. With a focus on benchmarking advancements and MPU design strategies, discover how AI integration with numerous sensors could redefine possibilities in the robotics field. This episode is a compelling journey through the landscape of AI technologies, emphasizing collaboration and innovation for next-generation AI products. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Unlock the secrets of energy-efficient AI as we explore the groundbreaking fusion of Edge AI and generative AI in our latest episode. With expert insights from Victor Jung, a trailblazer in the field, discover how foundational models can be deployed on tiny and embedded systems to revolutionize devices like AR glasses and nanodrones. Listen as we unravel the complexities of deploying neural networks on microcontrollers, with a focus on powerful techniques like quantization, graph lowering, and innovative memory management strategies. Victor guides us through the nuanced process of deploying neural networks, highlighting critical stages like graph lowering and memory allocation. Traverse the intricate front-end and mid-end stages where neural network graphs are optimized, ensuring peak performance on specific hardware platforms. We'll illustrate the importance of efficient memory usage through a fascinating example involving a tiny language model on the Syracuse platform, showcasing the role of quantization and memory management tailored for hardware constraints. Dive into the future of AI deployment on edge devices with a focus on quantization and hardware support. From exploring the potential of foundation models like DenoV2 to discussing the emerging micro scaling format, we uncover the technologies that are making AI more energy-efficient and versatile. Our conversation underscores the importance of viewing memory as a compute asset and the need for ongoing research to enhance system efficiency for generative AI at the edge. Join us for an enlightening episode that highlights the vital steps needed to optimize memory and computing resources for meaningful applications on small platforms. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Join us for an insightful conversation with Dr. Vijay Janapa Reddi from Harvard, who takes us on a journey through the evolving world of edge computing and machine learning education. Discover how his family's affinity for East Coast seasons inspired his academic path, and learn about his groundbreaking open-source book on machine learning systems. This episode celebrates the rebranding of the tinyML Foundation to the Edge AI Foundation, reflecting an expanded focus that transcends embedded devices. We tackle the complexities of machine learning education, where excitement often masks the real challenges of developing robust AI systems. Dr. Janapa Reddi’s vision for his work-in-progress book draws from his teaching experiences at Harvard, aiming to universalize machine learning system principles akin to core concepts in operating systems. We explore the challenge of crafting educational materials that cater to both beginners and seasoned professionals, providing a roadmap to guide diverse audiences. The discussion highlights the importance of hands-on learning, especially in data collection and lab work, with contributions from notable figures like Marcelo Rovai in the tinyML space, emphasizing practical applications for edge AI systems. In a fascinating discussion on data science versus data engineering, Dr. Janapa Reddi elucidates the foundational role of data engineering in successful machine learning projects. We also delve into microcontroller programmability and the integration of frameworks like TensorFlow and PyTorch into curriculums. As we explore the role of AI tools like ChatGPT in programming, the conversation shifts to the exciting potential of AI-powered educational assistants, transforming the future of learning through interactive and personalized experiences. Whether you're a student, educator, or industry professional, this episode offers a wealth of insights into the intersection of AI, education, and the future of edge technologies. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Get ready for the recap of the Beyond Chatbots - The Journey of Generative AI to the Edge - exploring the frontier of Generative AI and edge technology with Davis Sawyer, Danilo Pau and Pete Bernard as they discuss the dynamic innovations transforming these fields. We uncover the fascinating shift from cloud-based proof-of-concepts to the compelling reality of edge solutions. This conversation dives into the ever-evolving landscape of generative AI, particularly in edge environments where cost and power efficiency reign supreme. From automotive breakthroughs to advanced memory optimization techniques, discover how these innovations are redefining the role of AI in our world. Listen in as we dissect the gravitational pull towards edge solutions with insights from recent industry research and captivating discussions. Dave shares intriguing observations on AI as crucial infrastructure, likening it to essential utilities that promise lasting impacts across sectors. As we look ahead, the conversation turns to the future of AI in manufacturing and the exciting potential for AGI-capable equipment. With Foundation partners like STMicroelectronics and NXP at the helm, the potential for edge AI advancements is limitless. Join us for an engaging exploration of the trends shaping the future of AI and edge computing. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Unlock the secrets of neural style transfer on microcontrollers with our special guest, Alberto Ancilotto of FBK, as he explores a groundbreaking approach to image generation on low-power devices. Discover how this innovative technique allows us to combine the content of one image with the artistic style of another, transforming simple visuals into unique masterpieces—like turning a regular cat photo into a Van Gogh-inspired work of art. Alberto introduces Xinet, a cutting-edge convolutional neural network designed to perform these creative tasks efficiently on embedded platforms. Gain insight into the process of optimizing performance by evaluating CNN operators for energy efficiency and adapting networks for a variety of devices, from the smallest microcontrollers to advanced TPUs and accelerators. We dive deep into the collaboration between Clip and style transfer networks, enhancing the precision of semantic representation in generated images. Witness the impressive capabilities of this technology through real-world examples, such as generating images in just 60 milliseconds on the STM32N6 microcontroller. Experience the advanced applications in video anonymization, where style transfer provides a superior alternative to traditional blurring methods, altering appearances while maintaining action consistency. Alberto also addresses the broader implications of anonymization technology in public spaces, including privacy protection and GDPR compliance, while maintaining artistic integrity. Join us as we tackle audience questions about model parameters, deployment flexibility, and the exciting potential of this technology across various sectors. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Revolutionizing Software Development with GenAI-Powered Edge Solutions with Anirban Bhattacharjee of Wipro 28:43
What if AI could transform the landscape of software development, making traditional methods seem like relics of the past? Join us as we sit down with a visionary guest from Wipro Engineering to uncover how GenAI-based custom code systems are revolutionizing the future of AI PCs. We promise a deep dive into how these intelligent tools are not just enhancing productivity but are redefining the very essence of software creation. Discover why the shift from cloud-based to edge-based solutions is imperative for enterprise developers dealing with proprietary codebases, and explore the power of open-source models like Code Llama, integrated through advanced frameworks such as LanChain and Lama Index. This episode promises to unravel the intricacies of an innovative web-based application designed to boost performance and user efficiency. Our conversation also shines a light on the tangible productivity gains brought by cutting-edge code assistance tools, effectively reducing weeks of work into days. We explore the vital role of hardware—like RAM and discrete GPUs—in maximizing these tools' potential. Discussions reveal varying levels of acceptance among developers, with younger professionals more readily embracing the shift. To bridge this gap, we recommend intensive training and boot camps as pathways to wider adoption. Furthermore, the potential of generative AI in deciphering and documenting legacy code is highlighted, offering a glimpse into how these advancements are reshaping the programming landscape. Engage with us to understand the profound impact of these innovations on the future of software development. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Tomorrow's Edge AI: Cutting-Edge Memory Optimization for Large Language Models with Seonyeong Heo of Kyung Hee University 30:29
Discover the cutting-edge techniques behind memory optimization for large language models with our guest, Seonyeong Heo from Kyung-Hee University. Join us as we promise to unlock the secrets of deploying 7-billion-parameter models on small devices with limited memory. This episode delves into the intricacies of key-value caching in decoder-only transformers, a crucial innovation that reduces computational overhead by efficiently storing and reusing outputs. Seon-young shares insightful strategies that tackle the high demands of memory management, offering a glimpse into how these models can be more feasible and energy-efficient. Our conversation also ventures into the world of dynamic compression methods essential for optimizing memory usage. We unpack the challenges of compressing key-value arrays and explore the merits of techniques like quantization, pruning, and dimensionality reduction with autoencoders. Weighted quantization is highlighted as a standout method for achieving remarkable compression rates with minimal errors, provided it's fine-tuned effectively. This episode is a must-listen for those interested in the future of on-device LLMs, as we underscore the significance of efficient memory management in enhancing their performance, especially in resource-constrained settings. Tune in for this enlightening discussion paving the way for innovative advancements in the field. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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Unlock the future of automotive AI with insights from Ashutosh and Guru Prashad of BOSS India, as they unravel the transformative potential of Small Language Models (SLMs) in vehicles. Discover how these compact powerhouses are reshaping the landscape of vehicular edge systems by offering customization and performance reliability, all while keeping data privacy at the forefront. Dive into the captivating interplay between SLMs and their larger counterparts, Large Language Models (LLMs), and learn how they together address domain-specific tasks and complex computations in the cloud. This episode promises to equip you with a deeper understanding of why SLMs are the secret sauce for advancing automotive AI in this data-sensitive era. We also spotlight the remarkable optimization journey of the Tiny Llama 1.1 model. Learn about the fine-tuning process that brought about an astounding 700% improvement in throughput and a drastic reduction in model size. Uncover the fascinating world of edge deployment using devices like Pi 4B and Jetson Oren Nano, and explore the audio and chat functionalities that are setting new standards in vehicular AI. Finally, imagine the future of personalized interactions in cars, where generative AI transforms the way we communicate and engage with our vehicles and surroundings. This episode is a treasure trove of forward-thinking solutions and innovative ideas, perfect for anyone eager to explore the cutting edge of automotive AI. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Unlock the secrets to deploying machine learning models on edge devices with Chen Lai from the PyTorch Edge team at Meta. Discover how XTorch, a brainchild of the PyTorch team, is transforming edge deployment by addressing challenges like memory constraints and hardware diversity. Get an insider's view on the technical collaborations with tech giants like Apple, Arm, Qualcomm, and MediaTek, which are revolutionizing the deployment of advanced language models like LLAMA on platforms such as iOS and Android. With Chen's expert insights, explore the fascinating process of converting PyTorch models into executable programs optimized for performance, stability, and broad hardware compatibility, ensuring seamless integration from server to edge environments. Immerse yourself in the world of XTorch within the Red Bull Ecosystem, where deploying machine learning models becomes effortless even without extensive hardware knowledge. Learn how key components like Torchexport and Torchio capture compute graphs and support quantization, elevating edge deployment capabilities. Discover how Torchchat facilitates large language model inference on various devices, ensuring compatibility with popular models from Hugging Face. As we wrap up, hear about the community impact of Meta's Executorch initiative, showcasing a commitment to innovation and collaboration. Chen shares his passion and dedication to advancing edge computing, leaving a lasting impression on listeners eager for the next wave of technological breakthroughs. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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Unlock the future of TinyML by learning how to harness the power of large language models, as we sit down with Roberto Morabito to dissect this intriguing technological convergence. Discover how the collaborative efforts with Eurocom and the University of Helsinki are shaping a groundbreaking framework designed to elevate TinyML's lifecycle management. We promise to unravel the complexities and opportunities that stem from integrating these technologies, focusing on the essential role of prompt templates and the dynamic challenges posed by hardware constraints. Through a proof-of-concept demonstration, we bring you invaluable insights into resource consumption, potential bottlenecks, and the exciting prospect of automating lifecycle stages. Our conversation ventures into optimizing language models for end devices, delving into the transformative potential of Arduinos and single-board computers in enhancing efficiency and slashing costs. Roberto shares his expertise on the nuances of model conversion across varying hardware capabilities, revealing the impact this has on success rates. The episode crescendos with a compelling discussion on automating industrial time series forecasting, underscoring the critical need for adaptive solutions to maintain accuracy and efficiency. Through Roberto's expert insights, listeners are invited to explore the forefront of technology that is poised to revolutionize industrial applications. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Harnessing Edge AI: Transforming Industries with Advanced Transformer Models with Dave McCarthy of IDC and Pete Bernard of tinyML Foundation 33:53
Unlock the transformative potential of edge computing with the insights of industry experts Dave McCarthy from IDC and Pete Bernard. Ever wondered how advanced transformer models are catalyzing technological leaps at the edge? This episode promises to enlighten you on the nuances of AI-ready infrastructure, pushing the boundaries of autonomous operations in multi-cloud and multi-edge environments. With an emphasis on trust, security, and sustainability, our guests illuminate the strategic importance of optimizing edge designs and the benefits of hybrid and multi-cloud strategies. Explore the dynamic world of Edge AI as we dissect the complexities of heavy and light edge scenarios, particularly within industrial contexts. Dave and Pete help navigate the shift from centralized systems to the cutting-edge distributed frameworks necessary for processing the explosion of data generated outside traditional data centers. Discover how Edge AI and TinyML are reshaping industries by empowering smarter devices and solutions, pushing AI workloads from the cloud to resource-constrained environments for improved efficiency and real-time data processing. Dive into the fascinating migration of AI workloads from the cloud to the edge, driven by the demands of smart cities and critical infrastructure. Our experts share insights from global surveys, examining how inference is increasingly shifting to the edge, while training remains cloud-based. Listen in as we explore the evolving edge AI hardware landscape, cost-effective solutions, and the burgeoning interest in specialized models. Uncover emerging generative AI use cases poised to revolutionize various sectors, and gain a glimpse into the future opportunities and challenges in the ever-evolving landscape of edge AI. Join us for a riveting discussion that promises to leave you informed and inspired. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Transforming the Edge with Generative AI: Unraveling Innovations Beyond Chatbots with Danilo Pau, IEEE Fellow from STMicroelectronics 6:47
Generative AI is poised to transform the edge, but what does this mean for technology, innovation, and everyday life? Join us for an enlightening discussion led by Danilo Pau, featuring a distinguished panel of experts including Dave, Roberto Chen, Alok, Seung-Yang, Arniban, and Alberto. They promise to unravel the mysteries beyond large language models and chatbots, offering fresh insights into the interplay of algorithms, software, chips, and methodologies from an EDA perspective. The conversation aims to democratize generative AI, making its groundbreaking potential accessible to all, and sparking inspiration throughout the tiny ML community. With gratitude to the TinyML Foundation for their invaluable support, this episode builds on the momentum of previous forums. Reflecting on the foundation laid by Davis Sawyer's inspiring March session, we explore how generative AI is not just a cloud-based innovation but a technology set to revolutionize the edge. Expect to hear how these developments could impact everyone's work and life, and gain a glimpse into the collective vision for the future from our esteemed speakers. Don’t miss the chance to be part of this vibrant exchange, where innovation is not just discussed but propelled forward. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Unlock the secrets to revolutionary weather forecasting with our latest episode featuring Jonah Beysens, the brilliant mind behind the Aurora project. Imagine a world where remote and resource-limited areas can access reliable weather data without the hassle of maintaining traditional mechanical stations. Learn how the Aurora, an acoustic smart weather station, is making this possible. Born from the TinyML Challenge 2022, Aurora employs a TinyML board with a microphone to classify wind and rain intensity, ensuring robustness and ease of deployment. Jonah walks us through the journey of crafting a real-world dataset and shares the collaborative spirit behind making this data open for community-driven innovation. Discover how the shift towards low-cost, acoustics-based devices is reshaping weather forecasting, offering enhanced spatial resolution with multiple ground stations. Jonah sheds light on the collaborative efforts to refine prediction models with open datasets, emphasizing the profound global impact, especially in developing nations where agriculture depends heavily on accurate forecasts. As we discuss the ongoing work to make weather data more accessible worldwide, we highlight the role of community and open access in driving forward weather-related technologies. Join us in exploring how these innovative solutions promise timely, dependable forecasts, paving the way for a future where environmental data is a shared resource for all. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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Unlock the secrets of edge computing and on-device learning with Elias Cereda, a trailblazing PhD student at the Dalle Molle Institute for Artificial Intelligence in Italy, as we explore the transformative potential of AI in nano-UAV technology. Discover how Elias is pioneering solutions to the challenges of domain shifts in AI models, particularly those trained in simulations and deployed in real-world scenarios. From enhancing privacy and security through on-device learning to mastering the intricacies of human pose estimation for autonomous navigation, this episode is a treasure trove of insights. We dive into the practicalities of deploying systems using the Crazyflie 2.1 drone alongside GreenWaves' sophisticated RISC-V GAP8 and GAP9 chips, all while managing tight power constraints. Take a closer look at the complexities of on-device and online learning with Elias as we delve into the nuances of continual learning. Learn how maintaining a balance between retaining previous knowledge and integrating new data is crucial in the field. Elias introduces us to a self-supervised metric that operates without initial labels, cleverly utilizing odometry data to refine model predictions. By considering human movement as measurement noise and refining data through post-processing techniques, the episode unveils strategies to enhance model performance without explicit tracking. For those eager to delve deeper into the methodologies discussed, Elias points to a comprehensive paper that promises to enrich your understanding of this cutting-edge technology. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Deploying TinyML Models at Scale: Insights on Monitoring and Automation with Alessandro Grande of Edge Impulse 20:34
Unlock the secrets of deploying TinyML models in real-world scenarios with Alessandro Grande, Head of Product at Edge Impulse. Curious about how TinyML has evolved since its early days? Alessandro takes us through a journey from his initial demos at Arm to the sophisticated, scalable deployments we see today. Learn why continuous model monitoring is not just important but essential for the reliability and functionality of machine learning applications, especially in large-scale IoT deployments. Alessandro shares actionable insights on how to maintain a continuous lifecycle for ML models to handle unpredictable changes and ensure sustained success. Delve into the intricacies of health-related use cases with a spotlight on the HIFE AI cough monitoring system. Discover best practices for data collection and preparation, including identifying outliers and leveraging Generative AI like ChatGPT 4.0 for efficient data labeling. We also emphasize the importance of building scalable infrastructure for automated ML development. Learn how continuous integration and continuous deployment (CI/CD) pipelines can enhance the lifecycle management of ML models, ensuring security and scalability from day one. This episode is a treasure trove of practical advice for anyone tackling the challenges of deploying ML models in diverse environments. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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…
Curious about how you can run a colossal 405 billion parameter model on a device with a mere 2 billion footprint? Join us with Mahesh Yadav from Google, as he shares his journey from developing small devices to working with massive language models. Mahesh reveals the groundbreaking possibilities of operating large models on minimal hardware, making internet-free, edge AI a reality even on devices as small as a smartwatch. This eye-opening discussion is packed with insights into the future of AI and edge computing that you don't want to miss. Explore the strategic shifts by tech giants in the language model arena with Mahesh and our hosts. We dissect Microsoft's investment in OpenAI’s Phi model and Google's development of Gamma, exploring how increasing the parameters in large language models leads to emergent behaviors like logical reasoning and translation. Delving into the technical and financial implications of these advancements, we also address privacy concerns and the critical need for cost-effective model optimization in enterprise environments handling sensitive data. Advancements in edge AI training take center stage as Mahesh unpacks the latest techniques for model size reduction. Learn about synthetic data generation and the use of quantization, pruning, and distillation to shrink models without losing accuracy. Mahesh also highlights practical applications of small language models in enterprise settings, from contract management to sentiment analysis, and discusses the challenges of deploying these models on edge devices. Tune in to discover cutting-edge strategies for model compression and adaptation, and how startups are leveraging base models with specialized adapters to revolutionize the AI landscape. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Revolutionizing Space Technology with Edge AI and Satellite Autonomy 1:01:39
1:01:39 پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شد1:01:39
پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدImagine a world where satellites can make real-time decisions without waiting for ground-based commands. Learn how edge AI is revolutionizing space technology with David Maloney from Ubotica, who brings unparalleled expertise from his time at Movidius and Intel. Uncover the transformative power of performing AI inference directly on satellites, and why traditional ground-based systems are no longer sufficient. We explore advanced imaging techniques like hyperspectral imaging, which can now detect forest fires or monitor environmental changes with unprecedented speed and accuracy. Delve into the fascinating intersection of image compression and generative AI, and see how these technologies can overcome the challenges of power consumption and energy efficiency in space. Hear about real-world implementations such as the FISAT-1 satellite's cloud detection and removal capabilities and the impressive radiation tolerance of hardware tested at CERN's Large Hadron Collider. By examining the trade-offs and legacies of space technology, we reveal how cutting-edge AI applications are optimizing data transmission and processing. Finally, we discuss the advanced applications of hyperspectral sensors and image pattern recognition in environmental monitoring and security. Learn how these technologies can assess vegetation health, evaluate soil nutrients, and even detect illegal activities. Discover the challenges of deploying sensors in the harsh conditions of space and the significance of early warning systems for space weather events. With insights into the European Space Agency's Vigil mission and real-time edge processing in space, we also cover the exciting potential of Tiny Train technology for on-board training and updates, ensuring that our satellites are smarter and more responsive than ever before. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Ready to unlock the secrets behind real-time sensing algorithms for embedded devices? In this episode, you’ll gain valuable insights into transforming raw sensor data into actionable intelligence. We begin by breaking down the complexities of signal preprocessing, event triggering mechanisms, and feature extraction. Learn how event detection can drastically reduce false positives and computational overhead, setting the stage for robust and efficient real-time systems. Next, we delve into the world of AutoML tailored for embedded devices. Discover the nuances of hyperparameter tuning, cross-fold validation, and model ranking based on key performance metrics like F1 score and accuracy. We also introduce you to Piccolo AI, an open-source game-changer for model building and sensor data management. Plus, we answer listener questions about practical implementation details, making this segment a must-listen for any embedded systems enthusiast. Finally, get hands-on with Piccolo AI as we guide you through setting up your environment using Docker and exploring its powerful web interface. From adding new feature extractors to using synthetic data for model validation, we cover everything you need to contribute to or leverage this open-source project. We also emphasize community engagement, highlighting how collaborative efforts can drive innovation and improve the versatility of machine learning in embedded systems. Join us and become part of a thriving community pushing the boundaries of what's possible. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Can machine learning models be both powerful and tiny? Join us in this episode of TinyML Talks, where we uncover groundbreaking techniques for making machine learning more efficient through high-level synthesis. We sit down with Russell Clayne, Technical Director at Siemens EDA, who guides us through the intricate process of pruning convolutional and deep neural networks. Discover how post-training quantization and quantization-aware training can trim down models without sacrificing performance, making them perfect for custom hardware accelerators like FPGAs and ASICs. From there, we dive into a practical case study involving an MNIST-based network. Russell demonstrates how sensitivity analysis, network pruning, and quantization can significantly reduce neural network size while maintaining accuracy. Learn why fixed-point arithmetic is superior to floating-point in custom hardware, and how leading research from MIT and industry advancements are revolutionizing automated network optimization and model compression. You'll gain insights into how these techniques are not just theoretical but are being applied in real-world scenarios to save area and energy consumption. Finally, explore the collaborative efforts between Siemens, Columbia University, and Global Foundries in a wake word analysis project. Russell explains how transitioning to hardware accelerators via high-level synthesis (HLS) tools can yield substantial performance improvements and energy savings. Understand the practicalities of using algorithmic C data types and Python-to-RTL tools to optimize ML workflows. Whether it's quantization-aware training, data movement optimization, or the fine details of using HLS libraries, this episode is packed with actionable insights for streamlining your machine learning models. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
Unlock the secrets to high-efficiency embedded computer vision with industry experts Sandeep Mistry from Arm and Alex Chang from Himax Technology. We promise insights into the TinyML community and the collaborative efforts that are setting new benchmarks in the field. Alex Chang shares an in-depth look at Himax Technology’s cutting-edge AI processors and always-on sensors designed for low-power, battery-operated devices. Learn how Himax’s dual-mode CMOS sensors are revolutionizing applications like doorbells and smart devices, and why efficient AI processing at the edge is increasingly crucial. Curious about the architecture of state-of-the-art AI processors? Discover the intricate details of a sophisticated Wi-Fi processor designed specifically for AI applications. We explore groundbreaking features such as DC-DC converters, dynamic voltage and frequency scaling (DVFS), and advanced security measures like Physical Unclonable Functions (PUF) and qubit-toe accelerators. You'll also understand how specialized hardware accelerators for motion detection, JPEG decoding, and voice detection enhance comprehensive audio and video AI processing. The development ecosystem, complete with essential software tools and downloadable resources on GitHub, is laid out to ease your implementation process. Ready to see AI in action? Follow our guided process of porting a pose estimation model to the iMac's YSI2 processor, aimed at tasks like fall detection and human-machine interfaces. We detail how to use a modified version of the UltraLytics GLLv8 postmodel for better accuracy and how to optimize the model for the ARM Ethos U55 MPU using the Ethos U Vella compiler. Witness a live demo showcasing the model’s real-time performance, achieving over 10 frames per second. We wrap up with a discussion on revolutionary partnerships driving Edge AI forward, spotlighting contributions from companies like Syntient, Atreus, ARM, and many others. Don't miss this chance to stay at the forefront of embedded computer vision and Edge AI technology! Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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1 Pioneering Personalized Medicine with Advanced AI Algorithms 1:06:10
1:06:10 پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شد1:06:10
پخش در آینده پخش در آینده لیست ها پسندیدن دوست داشته شدUnlock the transformative potential of AI in healthcare with Jim Wang and Steve Yu from the University of Sydney and listen to their revelatory insights on TinyML Network models in medical devices. Our latest episode is a treasure trove of innovation, where machine learning meets wearable technology to redefine patient care. From the pressing need for low latency in critical health monitoring to the intricacies of biosensor evolution and data privacy, this conversation maps out the future of medical diagnostics and the promise of personalized treatments. Imagine a world where your medical device knows you better than you know yourself. That's the future Jim and Steve unveil as we scrutinize the optimization of machine learning algorithms for edge devices, balancing the scales between performance and power constraints. We explore the regulatory hurdles and breakthroughs in model tailoring, ensuring that your health is monitored with meticulous precision. Our discussion also peels back the layers on the importance of public datasets and hospital partnerships in enhancing the accuracy and responsiveness of life-saving technology. Stepping into the realm of neuromorphic computing, we navigate the promising landscape of on-device training and model compactness. With an eye on patient privacy, we delve into the adaptability of models like the S4D and NCP, overcoming the challenges of limited data and simplifying complex architectures. Jim and Steve's research opens up a dialogue on the future of medical devices, where health monitoring is not just personalized but also proactive, ensuring that the care you receive is as unique as your heartbeat. Join us for an enlightening journey into the heart of healthcare innovation where edge computing is not just smart—it's genius. Send us a text Support the show Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org…
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Daily Deals
Daily Deals
مشابه EDGE AI POD
Africa-focused technology, digital and innovation ecosystem insight and commentary.
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Show notes are at https://stevelitchfield.com/sshow/chat.html
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Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Rae Johnston and guests take a fun, deep dive into how technology is reshaping our lives.
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WSJ’s Bold Names brings you conversations with the leaders of the bold-named companies featured in the pages of The Wall Street Journal. Hosts Tim Higgins and Christopher Mims speak to CEOs and business leaders in interviews that challenge conventional wisdom and take you inside the decisions being made in the C-suite and beyond.
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Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
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The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
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We help founders make something people want.
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This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
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Redefining AI is the 2024 New York Digital Award winning tech podcast! Discover a whole new take on Artificial Intelligence in joining host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and ...
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Three nerds discussing tech, Apple, programming, and loosely related matters.
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