Podcasts about edge impulse

In this episode of The G2 on 5G, Will Townsend and Anshel Sag break down the latest developments in 5G technology, network advancements, and industry leadership changes. They discuss T-Mobile's definition of 5G Advanced, Intel's new CEO, and Broadcom's converged 5G fiber and satellite appliance. The conversation also covers Vodafone UK's AI-driven energy efficiency, Qualcomm's Edge Impulse acquisition, and Viasat & Space 42's partnership on NTN connectivity.  Their discussion covers:

OpenMV has a new Kickstarter so CEO Kwabena Agyeman chatted with us about more powerful (and smaller!) programmable cameras.  See OpenMV's site for their existing cameras. See their (already funded!) kickstarter page for the super powerful N6 and the ridiculously small AE3. Note that OpenMV still is committed to open source. See their github if you want to know more. Edge AI is the idea of putting intelligence in the devices (instead of in the cloud). There is an advocacy and education foundation called Edge AI Foundation. This organization was formerly the TinyML Foundation. Edge Impulse and Roboflow are companies that aid in creating and training AI models that can be put on devices.  ARM talks about their Ethos-U55 NPU (and how to write software for it). Transcript

In this 219th episode of The G2 on 5G, we cover:1. T-Mobile's plans for 5G Advanced in the United States2. Intel appoints Lip-Bu Tan as permanent CEO3. Broadcom's Velosky converged 5G fiber and satellite appliance4. Vodafone UK and Ericsson use AI to reduce 5G network energy consumption5. Qualcomm acquires Edge Impulse to boost IoT capabilities6. Viasat and Space42 partner on direct-to-device satellite connectivityThe hosts discuss T-Mobile's 5G Advanced strategy, Intel's leadership change, Broadcom's new network solution, AI-driven energy efficiency in 5G networks, Qualcomm's IoT expansion, and developments in satellite connectivity. They provide insights on industry trends, technological advancements, and the competitive landscape in the 5G ecosystem.

Shawn Hymel is an engineer and content creator who recently left his developer relations job at Edge Impulse to work on developing courses full time

In this episode of the Altium OnTrack podcast, host Tech Consultant Zach Peterson explores the fascinating world of Edge AI and how Large Language Models (LLMs) fit into the picture with Jan Jongboom, co-founder of Edge Impulse. The two discuss the evolution from GPT-2 to GPT-4, the importance of edge computing, and the hardware requirements for running AI on edge devices. Discover how reducing the size of LLMs enables efficient deployment on edge devices, gain insights into the practical applications of AI in various industries, and learn about EDGE IMPULSE.   More resources: Getting started w/ Edge Impulse on Renesas platforms Connect with Jan on LinkedIn Learn more about Edge Impulse Check out a recent video from Edge Impulse: Using GPT-4o to train a 2,000,000x smaller model (that runs directly on device) Exclusive 15 Days Free Altium Designer Access

How is AI being used at the edge, and what possibilities does this create for businesses? In this episode, host Bill Pfeifer sits down with the co-authors of the book AI at the Edge, Jenny Plunkett, Senior Developer Relations Engineer and Daniel Situnayake, Head of ML at Edge Impulse. They discuss how to determine which problems can actually be addressed through AI at the edge, how to think about effective AI, and unexpected use cases in generative AI and synthetic data generation. Plus, they cover how AI can support data distillation efforts and how to build teams that can successfully navigate this landscape. ---------Key Quotes:“We're going to be using generative AI to help us build a synthetic data set to train other AI models to deploy to edge devices.” - Jenny“One of the things that's really cool about synthetic data and using generative AI for that, is it potentially reduces the cost of training a model because instead of having to spend huge amounts of money labeling all this data, if you create the data yourself, you can have it implicitly be labeled.” - Dan --------Show Timestamps:(01:49) How did they get started in tech? (03:14) What brought them to AI?(08:12) What brought them together to write their book?(13:26) Determining which problems can be addressed with AI at the edge(15:51) What possibilities does AI at the edge create for businesses? (20:41) Synthetic data and generative AI (24:15) Using AI for data distillation (31:00) Building a skilled and interdisciplinary team (39:30) AI's transition from a career path to a tool (43:06) Effective AI (46:46) Edge / wildlife conservation case study (49:37) What are they excited about moving forward? --------Sponsor:Over the Edge is brought to you by Dell Technologies to unlock the potential of your infrastructure with edge solutions. From hardware and software to data and operations, across your entire multi-cloud environment, we're here to help you simplify your edge so you can generate more value. Learn more by visiting dell.com/edge for more information or click on the link in the show notes.--------Credits:Over the Edge is hosted by Bill Pfeifer, and was created by Matt Trifiro and Ian Faison. Executive producers are Matt Trifiro, Ian Faison, Jon Libbey and Kyle Rusca. The show producer is Erin Stenhouse. The audio engineer is Brian Thomas. Additional production support from Elisabeth Plutko and Eric Platenyk.--------Links:Follow Bill on LinkedInConnect with Jenny Plunkett on LinkedInConnect with Daniel Situnayake on LinkedIn and TwitterDaniel's substack

Zach Shelby, CEO of Edge Impulse, was a recent guest on the BrainChip podcast. Shelby is an IoT pioneer in simplifying development platforms for AI at the edge. He brought his passion for machine learning, embedded solutions and IoT to this lively and enlightening discussion with BrainChip CMO Nandan Nayampally. Hear about Shelby's astounding metrics for developer recruitment, training volume, and adoption; using AI to fill the gap when data sets are small or non-existent; the challenges of bringing AI to manufacturing and real-world use cases. Shelby is a familiar and highly respected leader in the ML community. He founded Sensinode, an enterprise wireless network provider in the early days of IoT that was acquired by ARM, enabling him to develop ARM's IoT business, first as Director of Technology and later as VP of Developers. At ARM, he helped create the non-profit BBC Micro:bit Educational Foundation and served as its CEO. In addition to his activities as a serial entrepreneur, Shelby is an angel investor in Amini.ai, Augmenta.ai, Operant.ai, and Petasense. Shelby serves on the board of TinyML and has won a Nokia Foundation Award for his work on IoT.

This week's Electromaker Show is now available on YouTube and everywhere you get your podcasts! Welcome to the Electromaker Show episode 119! Linux on Arduino, and we don't mean the Pro line! We also look at some fantastic upcycled Raspberry Pi projects, an interesting SeeedStudio LoraWAN Kickstarter, and announce the biggest Product of the Week Giveaway yet! Tune in for the latest maker, tech, DIY, IoT, embedded, and crowdfunding news stories from the week.   Watch the show! We publish a new show every week. Subscribe here: https://www.youtube.com/channel/UCiMO2NHYWNiVTzyGsPYn4DA?sub_confirmation=1 We stock the latest products from Adafruit, Seeed Studio, Pimoroni, Sparkfun, and many more! Browse our shop: https://www.electromaker.io/shop Join us on Discord! https://discord.com/invite/w8d7mkCkxj​ Follow us on Twitter: https://twitter.com/ElectromakerIO Like us on Facebook: https://www.facebook.com/electromaker.io/ Follow us on Instagram: https://www.instagram.com/electromaker_io/ Featured in this show: Ian's Fundraising link for Mind UK Linux on an Arduino Nano Upcycling Projects on the Pi Blog Tomy Turner Incredible Pi Arcade Mod Pi Powered Restomod Wurlitzer 1015 Jukebox Udoo X86 Interactive Vintage Radio Product of the Week: LattePanda Sigma Seeed Studio SenseCap T1000 Kickstarter Imagine Edge AI conference from Edge Impulse

When we think about machine learning today we often think in terms of immense scale — large language models that require huge amounts of computational power, for example. But one of the most interesting innovations in machine learning right now is actually happening on a really small scale. Thanks to TinyML, models can now be run on small devices at the edge of a network. This has significant implications for the future of many different fields, from automated vehicles to security and privacy. In this episode of the Technology Podcast, hosts Scott Shaw and Rebecca Parsons are joined by Andy Nolan, Director of Emerging Technology at Thoughtworks Australia, and Matt Kelcey of Edge Impulse, to discuss what TinyML means for our understanding of machine learning as a discipline and how it could help drive innovation in the years to come.

In episode 67 of The Gradient Podcast, Daniel Bashir speaks to Daniel Situnayake. Daniel is head of Machine Learning at Edge Impulse. He is co-author of the O'Reilly books "AI at the Edge" and "TinyML". Previously, he's worked on the Tensorflow Lite team at Google AI and co-founded Tiny Farms, an insect farming company. Daniel has also lectured in AIDC technologies at Birmingham City University.Have suggestions for future podcast guests (or other feedback)? Let us know here!Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterOutline:* (00:00) Intro* (1:40) Daniel S Origin Story: computer networking, RFID/barcoding, earlier jobs, Tiny Farms, Tensorflow Lite, writing on TinyML, and Edge Impulse* (15:30) Edge AI and questions of embodiment/intelligence in AI* (21:00) The role of hardware, other constraints in edge AI* (25:00) Definitions of intelligence* (29:45) What is edge AI?* (37:30) The spectrum of edge devices* (43:45) Innovations in edge AI (architecture, frameworks/toolchains, quantization)* (53:45) Model compression tradeoffs in edge* (1:00:30) Federated learning and challenges* (1:09:00) Intro to Edge Impulse* (1:20:30) Feature engineering for edge systems, fairness considerations* (1:25:50) Edge AI and axes in AI (large/small, ethereal/embodied)* (1:37:00) Daniel and Daniel go off the rails on panpsychism* (1:54:20) Daniel's advice for aspiring AI practitioners* (1:57:20) OutroLinks:* Daniel's Twitter and blog* Edge Impulse Get full access to The Gradient at thegradientpub.substack.com/subscribe

Daniel Situnayake joined us to talk about AI, embedded systems, his new book on the previously mentioned topics, and writing technical books.  Daniel's book is AI at the Edge: Solving Real-World Problems with Embedded Machine Learning from O'Reilly Media. He is also the Head of Machine Learning at Edge Impulse, which makes machine learning on embedded devices simpler. They have a Responsible AI License which aims to keep our robot overlords from being too evil. We mentioned AI Dungeon as an amusing D&D style adventure with an AI. We also talked about ChatGPT. Daniel was previously on the show, Episode 327: A Little Bit of Human Knowledge, shortly after his first book came out: TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers Transcript

Edge devices are hardware devices that sit at the edge of a network. They could be routers, switches, your phone, voice assistant, or even a sensor in a factory that monitors factory conditions. Machine learning on the edge combines ideas from machine learning with embedded engineering. With machine learning models running on edge devices amazing new types of applications can be built, such as using image recognition to only take pictures of the objects you care about, developing self-driving cars, or automatically detect potential equipment failure. However, with more and more edge devices being used all the time that might be collecting sensitive information via sensors, there are a number of potential privacy and security concerns. Dan Situnayake, Head of Machine Learning at Edge Impulse, joins the show to share his knowledge about the practical privacy and security concerns when working with edge IoT devices and how to still leverage this incredible technology but do so in an ethical and privacy-preserving way. Topics: What's your background and how did you end up as the head of machine learning at Edge Impulse? What is an edge device? What is Edge Impulse and what are the types of use cases people are solving with AI on edge devices through the Edge Impulse platform? What are the unique security challenges with edge devices? Since these devices are potentially observing people, collecting information about someone's movements, what kind of privacy concerns does someone building for these devices need to think about? Are there industry best practices for protecting potentially sensitive information gathered from such devices? Is there research into how to collect data but protect someone's privacy when it comes to building training sets in machine learning? What happens if someone steals one of these devices? Are there safeguards in place to protect the data collected on the device? Where do you see this industry going in the next 5-10 years? Do you foresee security and privacy getting easier or harder as these devices become more and more common? Resources: Edge Impulse AI at the Edge

The conversation this week is with Shawn Hymel. Sean is a machine learning DevRel Engineer, Instructor and University Program Manager at Edge Impulse. He creates compelling technical videos, courses and workshops around edge machine learning that inspire engineers of all skill levels. Shawn is an advocate for enriching education through stem and believes that the best marketing comes from teaching, you can be found giving talks, running workshops and swing dancing in his free time.If you are interested in learning about how AI is being applied across multiple industries, be sure to join us at a future AppliedAI Monthly meetup and help support us so we can make future Emerging Technologies North non-profit events!Emerging Technologies NorthAppliedAI MeetupResources and Topics Mentioned in this EpisodeEdge ImpulseTensorFlowIntroduction to TensorFlow for AI, ML, and Deep LearningMicrosoft AzureGitHubDeveloper Marketing Does Not Exist by Adam DuVanderYoutility: Why Smart Marketing Is about Help Not Hype by Jay BaerShawnHymel on AdafruitGartner hype cycleSparkFunSpiking neural networkNeuromorphic ComputingField-programmable gate arrayA Thousand Brains: A New Theory of Intelligence by Jeff HawkinsEnjoy!Your host,Justin Grammens

Today, we spoke with Daniel Situnayake of Edge Impulse. We discussed Cloud-based dev environments, Cloud-based IDEs, Infrastructure as code, Dev containers and Live collaboration.             Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Edge Impulse with Daniel Situnayake appeared first on Software Engineering Daily.

Today, we spoke with Daniel Situnayake of Edge Impulse. We discussed AI, machine learning, edge devices, TinyML and AI tool chain.             Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Edge Impulse with Daniel Situnayake appeared first on Software Engineering Daily.

Today, we spoke with Daniel Situnayake of Edge Impulse. We discussed AI, machine learning, edge devices, TinyML and AI tool chain.             Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Edge Impulse with Daniel Situnayake appeared first on Software Engineering Daily.

Machine learning models are often thought to be mainly utilized by large tech companies that run large and powerful models to accomplish a wide array of tasks. However, machine learning models are finding an increasing presence in edge devices such as smart watches. ML engineers are learning how to compress models and fit them into smaller and smaller devices while retaining accuracy, effectiveness, and efficiency. The goal is to empower domain experts in any industry around the world to effectively use machine learning models without having to become experts in the field themselves. Daniel Situnayake is the Founding TinyML Engineer and Head of Machine Learning at Edge Impulse, a leading development platform for embedded machine learning used by over 3,000 enterprises across more than 85,000 ML projects globally. Dan has over 10 years of experience as a software engineer, which includes companies like Google (where he worked on TensorFlow Lite) and Loopt, and co-founded Tiny Farms America's first insect farming technology company. He wrote the book, "TinyML," and the forthcoming "AI at the Edge". Daniel joins the show to talk about his work with EdgeML, the biggest challenges facing the field of embedded machine learning, the potential use cases of machine learning models in edge devices, and the best tips for aspiring machine learning engineers and data science practitioners to get started with embedded machine learning.

In this episode, BrainChip's Rob Telson and Edge Impulse's Jan Jongboom discuss how machine learning on neuromorphic computing can make IoT devices smarter, faster, and more efficient.

Alexandra Covor spoke with us about engineering, making, drawing, school, and what it means to be an artist.  Alex's projects are on GitHub and Hackster.io. Her electronics comics can be found as PikaComics on Instagram. The 2022 Open Hardware Summit named Alex as part of the Ada Lovelace Fellowship. Her favorite talk from the summit was Anuradha Reddy talking about Knotty (Naughty) Hardware. Alex works for Zalmotek, a design services firm in Bucharest. We talked about Waylay.io, including their smart pet feeder built on that platform. For example projects for Edge Impulse, they built a tools organizer that uses ML. Transcript

Adam Benzion explains what tinyML is and how his company Edge Impulse is working to save elephants and more.

Jeremy Ellis said about Portenta, Edge Impulse, helping hands on robotics for kids. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app

55.000 projects, 30.000 developers, $54M funding, and customers including the likes of NASA, in a bit over 2 years. Edge Impulse is riding the wave of machine learning at the edge. Article published on ZDNet

Tania Rascia joins the round up to discuss how to organize your code across files, directories, components, and repos within your React app. The panel chimes in with what they've seen and clarify how these approaches effect the overall application functionality of your app. Panel Jack HerringtonPaige NiedringhausTJ Vantoll Guest Tania Rascia Sponsors Dev Influencers AcceleratorLevel Up | Devchat.tv Links React Architecture: How to Structure and Organize a React Application | Tania RasciaBackends for Frontends pattern - Cloud Design Patterns | Microsoft DocsChakra UIFront End Tables: Sorting, Filtering, and Pagination | Tania RasciaTania RasciaTwitter: Tania Rascia ( @taniarascia ) Picks Jack- react-location - npmPaige - Newline.coPaige- Fullstack React with Typescript courseTania - NetlifyTJ - Edge Impulse Contact Jack: Jack Herrington – YouTubeBlue Collar CoderTwitter: Jack Herrington ( @jherr ) Contact Paige: Paige NiedringhausPaige Niedringhaus – MediumTwitter: Paige Niedringhaus ( @pniedri )GitHub: Paige Niedringhaus ( paigen11 ) Contact TJ: TJ VanToll's BlogProgress SoftwareKendoReactTwitter: TJ VanToll ( @tjvantoll ) Special Guest: Tania Rascia.

In this episode, Rob Telson and Zach Shelby (Edge Impulse) discuss the broader AI ecosystem and how developers leverage data-driven engineering to enable the rapid development of ML models.

In this episode, we talk to Alessandro Grande and Robert Wolff, who run the Arm Innovation Coffee livestream on YouTube (which you can check out here). They tell the story about how they joined forces about a year ago to create a weekly interview video series during the pandemic.Alessandro and Robert use StreamYard to help manage the livestream, including green (waiting) rooms for guests, overlays, and live comment pop-ups. They also use Open Broadcaster Software Studio (OBS Studio) to stream their own personal feeds into StreamYard to manage multiple cameras and other overlays.Livestreams are great for making connections with audiences where people can chat and ask live questions. They offer a different form of engagement rather than a video or podcast where audience members are expected to passively watch/listen to the presenters. This helps humanize a brand by allowing customers (or potential customers) to interact directly with the presenters and each other.Developer evangelists (advocates, etc.) should consider adding livestreaming to their toolbox as a way to interact with customers and audiences.The new form of voice-only hangouts (e.g. Clubhouse, Twitter Spaces) offers something similar to livestreaming, but seems to lack many feedback features available on other platforms, such as the ability for audience members to type something into a chatbox. Robert talks about how to measure success with livestreams, which can be different than many common business metrics. These measurements include brand awareness and engagement compared to the amount of time to prepare and create the livestream (i.e. the return on investment). Alessandro mentions that a livestream should offer something to the audience to keep them engaged. SponsorWe want to thank Twilio for sponsoring this episode! Twilio is a cloud platform that helps developers automate phone calls, text messages, and other communications through their web API. Check out twilio.com/go/helloblink for more information about using Twilio for automated messaging and IOT applications. List of ResourcesArm Innovation Coffee LivestreamStreamYardOpen Broadcaster Software Studio (OBS Studio) Guest InformationAt the time of this episode’s release, Alessandro Grande has left Arm and taken a new position as Director of Technology at Edge Impulse.  Robert Wolff is an Ecosystem Developer Evangelist Manager at Arm. Guest Contact InformationLinkedIn - Alessandro GrandeLinkedIn - Robert WolffTwitter - Alessandro GrandeTwitter - Robert Wolff Host Contact Informationshawnhymel.comkennyconsultinggroup.comLinkedIn - Shawn HymelLinkedIn - Harris KennyTwitter - Shawn HymelTwitter - Harris Kenny License Information“Hello Blink Show” by Kenny Consulting Group, LLC and Skal Risa, LLC is licensed under CC BY 4.0Intro and outro song is “Routine” by Amine Maxwell is licensed under CC BY 3.0

In episode 31,  be ready to enter the realm of Embedded Machine Learning and Tiny ML with Jan Jongboom - CTO, Edge Impulse

Welcome to the Electromaker Show, episode 41! This week’s DIY tech news highlights include an Edge Impulse and TinyML on the Raspberry Pi, the Adafruit FunHouse WiFi home automation development board announced, the Piunora open-source carrier board for the Raspberry Pi seeks crowdfunding, and more! Tune in for the latest maker, tech, DIY, IoT, embedded, and crowdfunding news stories from the week! We publish a new show every week. Subscribe here! Read the article! Listen to the Electromaker Show in podcast format! Electromaker Discord Server Hydraulics made simple Eyecam: Anthropomorphic Webcam Learn Embedded Systems intro to the Sparkfun RP2040 Thing+  DIY textile bend sensor Revisiting Piunora on Crowd Supply HEGduino V2 Edge Impulse and TinyML on the Raspberry Pi Olimex RP2040-Pico-PC and RP2040-Pz boards Adafruit FunHouse:  ESP32-C6 announced

Daniel is a founder, an engineer, a teacher and a communicator. He currently works at Edge Impulse as Founding TinyML Engineer. He is a co-author of the great book published by O'Reilly called "TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers". He previously worked at Google as a Developer Advocate for TensorFlow Lite, enabling developers to deploy machine learning to edge devices, from phones to SoCs and was also Developer Advocate for Dialogflow, a tool for building conversational AI. ————————————————————————————— Connect with me here: ✉️ My weekly email newsletter: jousef.substack.com

TinyML - AI pushed to the edge, delivering larger impact in smaller packages We discuss the state of edge technologies, emergence of AI in microcontrollers, use cases of TinyML ranging from maritime to savannah plains, and predict what's going to happen in the future of edge AI. Zach Shelby is the CEO of Edge Impulse, and a seasoned veteran of edge technologies. Zach sold his previous IoT technology company, Sensinode, to ARM in 2013, he has since directed ARM's development and edge technology teams. In 2019, he embarked on another entrepreneurial venture to co-found Edge Impulse, a Tiny Machine Learning platform, aiming to democratize AI in smaller packages. Ville Hulkko is Co-Founder at Silo.AI, the largest private AI lab in the Nordics. Prior to Silo.AI he co-founded Valossa Labs, a computer vision startup. Ville lead the company to Silicon Valley, where he also founded Blackbear Startup Incubator.

Join Zach Shelby, the founder of Micro:Bit as he explores what makes this such an exciting time for hardware, especially within the LoRaWAN ecosystem.

Interview With Jan Jongboom (Edge Impulse) by The Things Industries