Podcasts about edge ai

What happens when the technology keeping essential services running fails at the worst possible moment? When most people think about workplace technology, they picture laptops, smartphones, and office software. But for millions of workers maintaining power networks, repairing infrastructure, supporting emergency services, managing transport systems, and operating in remote environments, technology has a very different job to do. It has to work every single time, often in conditions where failure is simply not an option. In this episode of Tech Talks Daily, I speak with Alex Gittins from Getac about the changing world of field operations, rugged computing, and the growing role of Edge AI in supporting the deskless workforce. Alex explains why rugged technology is far more than placing a consumer device inside a protective case. From extreme temperatures and harsh weather to vibration, dust, poor connectivity, and demanding working environments, true rugged devices are engineered from the ground up to support people working where most technology struggles. We also discuss the often-overlooked reality that around 80% of the global workforce operates away from a desk. These workers are increasingly dependent on digital tools to receive work orders, access mapping systems, capture field data, complete inspections, and communicate with central teams in real time. The conversation also turns to Edge AI and its growing importance for frontline teams. Rather than relying on constant connectivity and cloud processing, Edge AI enables workers to access intelligence directly on their devices. Whether identifying damaged assets through image recognition, guiding inspections, reducing paperwork, or supporting faster decision-making, AI is becoming a practical tool for improving efficiency and safety in the field. Alex also shares how customer expectations are changing. Organisations are no longer buying devices in isolation. Instead, they are involving technology providers much earlier in the process to help design complete solutions that can support future operational requirements. From defence roots to modern field operations, this episode offers a fascinating look at the technology helping keep critical services running behind the scenes. How will AI, connectivity, and rugged computing continue to reshape the future of work for the billions of people who never sit behind a desk?

Edge AI is exceeding the expectations that I had for the technology, at least at this early point in its ramp-up. I had expected it to take longer to reach fruition than it actually has, although you could probably argue that it hasn't come close to reaching even the beginnings of its potential. To understand where Edge AI stands today, where it's going, and when it could potentially get there, I spoke to John Weil, the Vice President and General Manager for IoT and Edge AI Processors at Synaptics, on this week's Embedded Executives podcast.

Listen Now to 011 WTFuture Watch 011 WTFuture This week’s show kicks off with the hosts untangling the literal and figurative wires of modern podcasting before nerding out over “Edge AI” running locally on smartphones to save energy and protect privacy. The banter takes a wonderfully weird turn when Al brainstorms an AI assistant specifically designed to intentionally repeat sentences not heard properly in a soothing voice to hearing-impaired friends to save them from social isolation. This quickly spirals into a debate over the origins of tinnitus; Bobby suspects it’s triggered by high-frequency Bluetooth headphones and EMFs, while Al hopefully wonders if the ringing is actually a neural data channel or a precursor to telepathy. The crew then marvels at AL’s one minute cinematic video recreating the exact day a dinosaur-killing asteroid hurled molten glass beads into the gills of paddlefish in North Dakota. Before diving into global politics, they take a delightful detour into inter-species communication, pondering whether a local crow leaving a dead bat as a “gift” is a sign of cross-species neighborliness, which even prompts them to trick the backyard flock by playing crow sounds from an app. The conversation blasts into orbit with a breakdown of recently released footage showing a pod of UFOs swarming a nuclear submarine, but the real fireworks explode during a heated debate over the impending arrival of Artificial General Intelligence (AGI). Bobby and Al take a pragmatic, geopolitical stance, warning that owning personal, localized AI is necessary to defend against global manipulation, specifically citing fears that the CCP wants to win the AGI race to implement the “great firewall of all time”. This triggers a passionate disagreement with Sun, who accuses the guys of falling into a fear-mongering, male-centric “dominate and subjugate” mindset that mirrors a perpetual arms race. Hurt feelings emerge as Sun advocates for trusting our collective intelligence to build an abundant, Star Trek-style utopia rather than focusing on apocalyptic Terminator scenarios, forcing AL to frantically defend himself as a fun “cheerleader for AI” rather than a pessimist. Ultimately, the trio cools down and finds common ground in their hopes for joining a peaceful galactic community, perfectly capped off by Sun referencing Iain M. Banks’ sci-fi Culture series as a brilliant blueprint for a post-scarcity society that has successfully conquered traditional cultural hierarchies. Enjoy!

The United States Navy is taking steps to integrate artificial intelligence into Maritime Operations Centers — balancing the need for operational agility with the rigor required for warfighting, according to Rear Adm. Susan BryerJoyner, director of the Warfighting Integration Directorate in the Office of the Chief of Naval Operations. Speaking with AI GovCast, BryerJoyner said Navy leadership is focused on maximizing taxpayer return on investment through data-informed analysis to determine which AI capabilities are ready for operational use and which require further evaluation. Mitigating AI hallucinations remains a top priority, BryerJoyner added, emphasizing that commanders will always remain part of the decision-making process. She said operational staff must understand how AI-generated recommendations are developed to ensure outputs align with mission requirements, planning assumptions and ethical standards. BryerJoyner also discussed how the Chief of Naval Operations is working with the Naval Postgraduate School to expand AI education through the school's new master's degree program in AI.

In this episode, I sit down with Steven Yates, CTO and co-founder of Federant, to dive deep into the urgent need for runtime governance in edge AI. Drawing on decades of experience in embedded systems and PLC design, Steven reveals why the shift to the edge demands more than just powerful inference—it requires robust, local authority to keep operations safe when connectivity falters. We unpack real-world incidents where lack of governance led to costly mishaps, and explore how new open-source solutions are bridging the gap between cloud convenience and industrial reliability. If you think cloud SLAs are enough for industrial AI, this conversation will make you rethink the fundamentals. Join me as we explore the future of safe, autonomous operations—and why the old rules of industrial control are more relevant than ever.

Healthcare CIOs are under pressure to deliver faster insights, safer care, and sustainable operations—without adding complexity. In this joint NVIDIA and Dell Technologies panel at HIMSS26, leaders from across the ecosystem explored how imaging, connected devices, and clinical edge AI are converging to transform care delivery.Here's a look at our panel of experts:* Rebecca Woods, Former CIO and Founder & CEO | Bluebird Leaders* Yu Liu, Co-Founder and CTO | Heidi* Dan Schneider, Professional Visualization Solution Specialist | NVIDIA* Sandra Colner, GM Global Healthcare & Life Sciences | Dell TechnologiesLearn more about Bluebird Leaders: https://www.bluebirdleaders.org/Learn more about Heidi: https://www.heidihealth.com/en-usLearn more about NVIDIA: https://www.nvidia.com/en-us/industries/healthcare-life-sciences/Learn more about Dell Technologies: https://dell.com/HealthcareHealthcare IT Community: https://www.healthcareittoday.com/

This episode of 100 Year Thinkers brings together Chris Mayer and Ian Cassel for a deep discussion on long-term stock picking, microcap investing, business quality, AI disruption, management teams, and the behavioral skills that separate great investors from great analysts. They explore why the edge in investing may increasingly come from judgment, presence, relationships, patience, and the ability to hold the right businesses through uncertainty.Matt Zeigler and I had the privilege of hosting Ian Cassel and Chris Mayer for a special 100-Year Thinkers Edition of the Excess Returns Podcast.Available now on Excess Returns Podcast and Talking Billions.

This episode of our new showThe 100 Year Thinkers brings together Chris Mayer and Ian Cassel for a deep discussion on long-term stock picking, microcap investing, business quality, AI disruption, management teams, and the behavioral skills that separate great investors from great analysts.They explore why the edge in investing may increasingly come from judgment, presence, relationships, patience, and the ability to hold the right businesses through uncertainty.Subscribe to the 100 Year Thinkers on Spotify⁠⁠⁠⁠Subscribe to the 100 Year Thinkers on AppleTopics CoveredWhy being present with management teams may still be an investor edge in the age of AIHow microcap investing differs from small-cap, mid-cap and large-cap investingWhy talking to management can build conviction but also create biasHow Chris Mayer thinks about vertical market software, mission-critical systems and AI disruptionWhy AI may become table stakes rather than a durable competitive advantageHow small companies can use AI to improve workflows, sales, inventory and productivityWhy many microcaps have short shelf lives and rarely become true long-term compoundersThe role of intelligent fanatics, owner-operators and repeat winners in great investmentsWhy management transitions can create powerful microcap opportunitiesThe difference between being a great analyst and being a great investorWhy execution, position sizing, selling losers and holding winners matter more than hit rateHow Matt and Bogumil apply the lessons to AI, business quality and the limits of small business scalabilityTimestamps00:49 Introducing Chris Mayer, Ian Cassel and 100 Year Thinkers04:59 Ian Cassel's first management meeting and XM Satellite Radio09:00 Why management meetings deepen understanding but can also mislead14:32 Chris Mayer on the real edge in long-term investing18:40 Mission-critical software, systems of record and AI disruption22:45 How microcap companies are using AI in real businesses27:02 AI as table stakes and when disruption creates opportunity31:29 Why most microcaps have short shelf lives35:51 Finding Tom Brady before the market knows he is Tom Brady40:53 Why owner-operators and intelligent fanatics matter45:03 Second-in-command leaders, repeat winners and chips on shoulders49:27 Analyst vs investor and the missing skills of stock picking54:00 Using data to identify investor strengths, weaknesses and decision errors58:14 Position sizing and letting small positions earn the right to grow01:03:00 Peter Lynch, stocks as businesses and learning to think like an owner01:07:00 AI, human judgment and the limits of automation01:11:00 Why not every small business can become the next Facebook01:15:00 Where to follow Bogumil and the 100 Year Thinkers series

Frances Edmonds, head of sustainable impact at HP Canada For Canadian IT solution providers, sustainability has always been something to think about – eventually. Frances Edmonds says the clock is running out on “eventually.” Edmonds is the Head of Sustainable Impact at HP Canada, a two-time Clean50 award winner, and one of the most recognized voices in the country at the intersection of technology, procurement, and environmental responsibility. On this episode of In The Channel, she makes the business case for why Canadian MSPs and resellers need to be fluent in sustainability today – and what being fluent actually looks like in a sales conversation. The data from HP’s own Amplify Impact program is striking: over 70% of partners who lead with sustainability report winning new business as a result, and self-assessment scores among participating partners have improved 59% since 2021. But the more urgent signal is in the procurement numbers. The Canadian Collaboration for Sustainable Procurement represents organizations with $105 billion in combined spend – and among them, OECM (the Ontario Education Collaborative Marketplace) is already applying a 12% weighting for ESG criteria in bid documents, scored at both the OEM and channel partner level. That’s not a coming wave. It’s already in the water. Edmonds also makes a compelling case on the AI front: Edge AI carries an estimated 90% lower environmental impact than Cloud AI – a stat with real implications for how MSPs frame hardware refresh conversations with clients who have sustainability or data sovereignty mandates. Resources mentioned in this episode: HP Amplify Impact program OECM – Ontario Education Collaborative Marketplace Bob Willard’s Sustainability Advantage – free tools for sustainability planning Climate Fresh training – available through HP Amplify Impact CBSR – Canadian Business for Social Responsibility Read Full Transcript Robert Dutt: Hello and welcome to In The Channel from ChannelBuzz.ca, bringing news and information to the Canadian IT channel community for the last sixteen years. I’m Robert Dutt, editor of ChannelBuzz.ca, and your host for the show. We talk a lot on this show about the “how” of the channel — how to build a practice, how to manage a migration, how to secure a client. Today we’re looking at a different kind of how: how to win deals in an environment where your customers care as much about your carbon footprint as they do about your hourly rate. My guest today has been living this story for 30 years. Frances Edmonds is the Head of Sustainable Impact at HP Canada, and she’s one of the most recognized voices in the country when it comes to the intersection of technology and sustainability. HP’s own data shows that over 70% of partners who lead with sustainability are seeing measurable impact on their win rates. What does that actually look like for a Canadian MSP in 2026? We’re going to dig into the shift in procurement rules, including some hard numbers on ESG weighting in Canadian bid documents, and why the rise of Edge AI might actually be the biggest sustainability story of the year for the channel. Let’s get right into it — my chat with Frances Edmonds. Frances, thanks for taking the time. Frances Edmonds: You’re very welcome. Robert Dutt: You sit in a unique place in that you’ve been focused on sustainability for a while now — long before it was a mainstream business conversation. Can you give us the quick picture of what your role is at HP Canada today, and how that has evolved as the story has evolved over time? Frances Edmonds: Sure. My title today is Head of Sustainable Impact — that’s the name of our sustainability program. And I practice what I call CSR 2.0: corporate social responsibility 2.0. I spent the first half of my career really getting HP Canada to the point where we could call ourselves Canada’s most sustainable technology company — you can find all the proof of that at hp.ca/sustainableimpact. Then we took a look around and said: sustainability from a business context in Canada isn’t really advancing. We’ve got a few leaders, but the vast majority of Canadian businesses aren’t doing very much — including our channel. So we thought: how do we change that? In a capitalist economy, the demand signal for sustainability performance in suppliers comes at the ballot box of procurement. About eight years ago, we switched our strategy to focus on how do we change how Canada buys. That’s really my job today — to encourage everyone in the industrial economy to add sustainability into their procurement criteria and decision-making, so there’s an incentive for all companies to step up and do more. Robert Dutt: Is that all? Frances Edmonds: [laughs] Well, on top of all the other things we do to maintain being Canada’s most sustainable technology company. But I don’t do this alone — sustainability is a team sport. We require all players to come to the table and bring their relative strengths. One thing we’re doing right now: we’re onto our fourth cohort working with a nonprofit called CBSR, Canadian Business for Social Responsibility. We teach sustainability professionals at some of Canada’s largest companies — Walmart, Canadian Tire, the banks, insurance companies — how to work alongside their procurement teams to implement sustainable procurement. We partner with nonprofits like Green Economy Canada, CBSR, other industry associations, and customers and partners to drive the change that’s necessary. Robert Dutt: You mentioned there’s still a need to mature how organizations across Canada are approaching this. The Amplify Impact data shows that 70-plus percent of partners report winning new business by leading with sustainability — that’s a striking number. When a Canadian MSP or reseller is actually leading with sustainability in a sales conversation, what does that look like in the room? Frances Edmonds: It really depends on who the customer is. Some customers have sustainability goals, but the people the MSP is actually talking to don’t know that — there’s often a gap between what the corporation is committed to and what the people doing the buying or the IT implementation are aware of. So you have to do your research: understand where the customer is coming from, what the opportunity is, and then align what the MSP and the OEM are doing on sustainability with the customer’s actual pain points. Do they have difficulty managing products at end of first life — the most common issue? Do they understand where their security vulnerabilities are? If you think about managing print, for instance — you’d normally do a print assessment and find printers 15 or 20 years old sitting on the network. That’s a huge security vulnerability that nobody’s really paying attention to. Helping customers with pain points like that — showing them the opportunities, whether it’s getting value back from end-of-first-life equipment to help fund new purchases, or moving into buying as a service — that’s really the sweet spot for both an MSP and a customer to maximize their sustainability performance. Robert Dutt: Is this primarily a large enterprise and government discussion today, or is it moving into the mid-market and down into SMB? A lot of partners are working with smaller businesses who may not have a strong sustainability mandate at the top of their priority list. Frances Edmonds: I think it’s quite spotty, honestly — I see bid documents from across the country in all sectors of the economy, so it’s hard to generalize. One advantage small businesses have is that they’re often purpose-driven, and the owner can make a decision quickly. “I’m buying from a company that puts ocean-bound plastics into their products” — and that’s a faster decision than getting a university to change its procurement policy, which can take three years of approvals. What I am seeing that’s changed over the eight years I’ve been working in this area: before, people didn’t really understand the link between sustainability and procurement. Today they understand it, and the people who want to do it differently often just have inhibitors in the way — or they default to “this product’s carbon footprint is two kilograms less, so I’ll buy it.” That’s not really how sustainable procurement works. You need more information to make a well-rounded decision. Sustainable procurement is still about getting the best value for the goods and services you’re buying — but now you’re also looking at the most sustainable or circular option from the most sustainable or circular supplier, in alignment with your own organization’s goals. And governments, whose sustainability goals range from zero poverty to life below water and everything in between, have a tremendous opportunity to practice this. Robert Dutt: You’ve spoken before about sustainability scoring in RFPs and procurement documents. Where does that stand in Canada right now — is this something MSPs need to be ready for today, or is it still a coming wave? Frances Edmonds: There’s always opportunity for competitive advantage because each customer has a different focus — whether it’s bridging the digital divide in Indigenous communities, disability inclusion, or a dozen other areas. But let me give you some numbers. The Canadian Collaboration for Sustainable Procurement just issued their latest annual report. They represent broader public sector organizations with $105 billion in combined spend. Twenty-seven members have sustainable procurement embedded in their policies. Fourteen have a dedicated full-time person working on it. And one of the best examples to date: OECM, the Ontario Education Collaborative Marketplace, publicly states that they’re applying a 12% weighting for environmental, social, and governance items in bid documents — scored at not just the OEM level, but at the channel partner level as well. Robert Dutt: So if I’m a partner who wants to get ahead of this — with so many angles and approaches to consider — what’s the minimum literacy they need to have in a procurement conversation today? What should they know cold? Frances Edmonds: The universal language is carbon. What are your carbon emissions? How are you working to reduce your carbon impact? That question is coming in some form from customers, regardless of sector. We know our products are carbon-intensive: 80% of a notebook computer’s carbon impact is determined before it ever reaches the customer — it’s in how it’s built. So understanding where carbon sits in the system, and how customers can help reduce it, is the first place to start. Through the Amplify Impact Program, HP offers a wide range of training — from basic 101s all the way through to what we call Climate Fresk. That’s a three-hour workshop that helps a group understand the interconnectedness of climate change and what they can do about it. We deliver it to partner leadership so they can understand how important this is to their business. We’re actually running one next week, and partners are welcome to attend. Robert Dutt: For a partner who’s hearing this and thinking “I’m interested, but where do I start?” — what are the tools and resources inside Amplify Impact that are actually moving the needle? Frances Edmonds: The Amplify Impact Program basically took 80 years of HP’s expertise in sustainability leadership, put it into a web-enabled system, and made it available to partners for free. Everything a partner could possibly need is in there. If you’re not in the program yet, I’d strongly encourage you to join — it’s free and straightforward to get started. You sign a pledge to commit to the program, then complete an online self-assessment. With AI enhancements, it benchmarks you against your peers worldwide and gives you a customized action plan to improve your scores. The results have been meaningful: since we launched in 2021, self-assessment scores globally have increased by 59%. Partners redo the assessment annually, and we’re seeing steady progress. In Canada specifically, we’ve seen over 6,000 sustainability courses completed by partners and employees — which tells you the interest is there at the individual level. For anyone outside the Amplify Impact Program, Dr. Bob Willard at Sustainability Advantage offers a whole suite of high-quality tools for free. That’s another strong place to start. Robert Dutt: How has the partner conversation in Canada on this evolved over the last five years, and where does it need to go next? Frances Edmonds: Let’s look at the economic situation partners are in today. Prices are going through the roof, availability is constrained. What does a logical customer do in those circumstances? They start thinking about buying for durability and longevity — and that leads right into the “as a service” conversation. This is about deepening relationships with your customers. Customers don’t want a one-time fix anymore — they need a partner at the table. And selling as a service, with a longer and deeper customer relationship, is where the market is going. We’re moving away from selling boxes to selling services, and sustainability is just another one of those services that’s part and parcel of that shift. I always think of security and sustainability as two sides of the same coin. That’s what customers need — and we can deliver both. Robert Dutt: Security as a service is certainly well-established. Where do you see sustainability as a service in terms of maturity and adoption? Frances Edmonds: Within the Amplify Impact Program, for instance, if a partner wants to measure and manage their carbon footprint, HP has negotiated a globally discounted rate for partners to acquire a software-as-a-service tool to do exactly that. They become carbon-literate in a hands-on way and understand how to report on it to their own stakeholders — employees, investors, customers, whoever. In some cases, we even allow partners to use MDF to pay for that software. We’re essentially paying them to get started with carbon management. Robert Dutt: I have to ask about AI — it’s the conversation everyone in the channel is having right now. There’s a real tension between the push to build AI infrastructure, which is enormously energy-intensive, and sustainability goals. How should partners be navigating that for their clients? Frances Edmonds: Great question. Let’s start with the distinction between cloud AI and Edge AI. Edge AI — which, in a country of small and medium businesses like Canada, is where AI is really going to drive productivity — is estimated to have greater than 90% lower carbon impact and to be more secure than cloud AI. So we’re already on a winner there, assuming we can get AI-enabled devices into the right businesses. At its simplest: most tech people don’t actually know the relative carbon footprint of doing a Google search versus running a generative AI query. Can we just educate people to use the right tool in the right place? Don’t burn your carbon budget on something where a Google search would do. When you get into the ethics of AI use broadly, that’s a much longer conversation — and I’d like to see a lot more guidance documentation coming out on that front. Robert Dutt: That’s quite telling — that much lower footprint at the edge also speaks to what solution providers control, and brings in data sovereignty, security, many different factors. Frances Edmonds: Exactly. Security is the other piece — and they really go hand in hand. Robert Dutt: One last question: what’s the one thing you wish more MSPs and resellers understood about sustainability that they’re currently either getting wrong or overlooking? Frances Edmonds: Even when partners have made real investments in becoming more sustainable — gone through the training, completed the program — I don’t think they’re maximizing that return on investment by actually selling with sustainability. And I think it often comes down to the people taking the education not being the people making the go-to-market decisions. But as we see this shift into selling as a service, I think it will come along with it naturally. If you think about WXP — HP’s Workforce Experience Platform — there’s sustainability built right into it alongside security. The opportunity to delight customers with sustainability is real, and it’s not hard to do. It’s really just about making sure everyone knows, understands, and can connect it to what the customer actually needs. Robert Dutt: Some great advice in there. I appreciate you taking the time to share where things stand and where you see them going. Frances Edmonds: Thank you. From Canada’s most sustainable technology company — listed as one of the top 100 most sustainable corporations worldwide — this is near and dear to my heart. We’re here to make a difference, and this is one of the ways we do that. Robert Dutt: Brilliant. And it’s a conversation HP Canada has been having consistently for a while now — so it’s clearly not just an Earth Month thing. There you have it — Frances Edmonds from HP Canada. I’d like to thank Frances for her time today. It’s rare to talk to someone who can bridge the gap between high-level environmental goals and the gritty reality of a municipal RFP response, and I think she gave us some real clarity on where that line is being drawn right now. And as always, I’d like to thank you for listening. My big takeaway from that conversation is that sustainability is becoming a hard technical requirement, much like security. When you hear that organizations like OECM are moving toward a 12% weighting for ESG in their procurement documents — that’s not a nice-to-have anymore. That’s a gating factor. If you’re an MSP and you aren’t literate in this space, you’re essentially spotting your competitors a 12-point lead before the conversation even starts. I also found Frances’s point about Edge AI particularly striking. The idea that processing at the edge carries 90% less carbon impact than the cloud is a powerful narrative for partners — especially when you layer in the data sovereignty benefits we discussed. It’s a rare triple-win of performance, privacy, and planet that fits perfectly into the AI PC refresh cycle we’re seeing right now. If you enjoyed this episode, please make sure to follow or subscribe to In The Channel on Apple Podcasts, Spotify, YouTube, or wherever you get your shows. Ratings and reviews are always hugely appreciated — they really do help other Canadian channel pros find the show. Until next time, I’m Robert Dutt for ChannelBuzz.ca, and I’ll see you in the channel.

Apple (AAPL) earnings are out and the "extraordinary demand" for iPhone 17 products shows its hardware business continues to hold a strong grip on smartphone market share. But for Stephen Sopko, he's waiting to hear more about its AI exposure. "I like to say that Apple is the largest Edge AI company in the world," he says. Stephen wants to know how much AI processing occurs on the iPhone devices themselves and believes the company needs more "breadcrumbs" on newer products. He later addresses Apple's China market and how incoming CEO John Ternus will navigate the company's brand abroad. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

In this episode, Adam King of MediaTek and Francis Sideco of TIRIAS Research explore how MediaTek is scaling edge AI across a wide range of devices and markets, from smartphones and tablets to Chromebooks and AI workstations. They also dive into what's next for physical AI, the hype around AGI, and MediaTek's partnerships with NVIDIA and Google.  

Rajat Monga, CVP AI Frameworks @ Microsoft, joins the podcast to discuss his leadership and founder journey, from Google Brain / Tensorflow to inference.io and back to Microsoft. He dissects what it means to refound vs. start from scratch, the value of the open source community, and strategies for discovering what problem to solve when going the startup route. We also cover how to determine your users' hidden incentives and what that means for both product development & marketing, along with navigating the balance between a product's usefulness and consumers' willingness to pay for it. Additionally, Rajat shares about what he's currently up to at Microsoft and the emerging ML / AI technologies he's most excited about.   ABOUT RAJAT MONGA Rajat Monga is responsible for enabling an efficient AI stack at Microsoft from cloud to the edge. Before joining Microsoft, Rajat was founder and CEO of Inference.io, a smart analytics platform powered by AI. During his decade-long tenure at Google, he co-founded and led TensorFlow, and was a founding member of Google Brain. He's built out and led many engineering teams, and designed large scale distributed systems including web scale crawling and eBay's search engine. Rajat is a graduate of IIT Delhi.   Unblocked: The context engine your coding agents are missing. Give your coding agents the context your best engineers have. Your agents can read code, but they don't know how your team works. Rules and MCPs give access to information but not understanding. That's why you still have to tell them where to look and what to look for. Unblocked gives your agents the history, conventions, and decisions behind your code so they generate mergeable output without the back and forth. It automatically surfaces the right context for every task, so agents stay on track without the set up tax or the correction loops. getunblocked.com/elc   SHOW NOTES: Rajat's journey with Google Brain: Scaling deep learning from single PCs to thousands of machines with Jeff Dean & Andrew Ng (2:57) Moving from Google Brain to TensorFlow: Why new hardware and architectures required a total system rebuild (6:02) The "refounding" question: Choosing between starting from scratch or evolving an existing system (8:33) Why Google open-sourced TensorFlow to set industry standards and avoid supporting external copies (10:16) How open-source enabled global innovation, from Japanese cucumber sorting to African plant health (12:02) Transitioning as a leader: Why Rajat left Google during the height of TensorFlow to found a company (13:57) The discovery phase at inference.io: Navigating the pivot from IoT into solving data analytics gaps (15:31) Lessons on PMF: Moving beyond a "useful" product to one that solves a truly critical customer pain point (16:52) Why habits are harder to change than technology and the challenge of competing with established workflows (21:02) Marketing strategies: Tailoring personas for top-down prestige versus bottom-up personal efficiency (23:19) Deciding when to stop: A founder's framework for re-evaluating bets based on current knowledge (24:57) Rajat's new role at Microsoft: Overseeing Edge infrastructure and large-scale Cloud AI inference (27:46) Dissecting ML edge strategy: Using ONNX Runtime to unify AI performance across Windows, iOS, and Android (30:02) Edge AI trends: Shifting from experimental models to production models optimized for cost and privacy (31:20) The future of Edge: How on-device processing will power AI in robotics, smart glasses, and wearables (33:23) Scaling inference: Treating multi-GPU clusters like a distributed operating system for AI models (34:25) Rapid fire questions (37:45)   LINKS AND RESOURCES Epic Disruptions: 11 Innovations That Shaped Our Modern World - Innovation expert Scott Anthony masterfully weaves together the fascinating stories behind history's most transformative disruptions—from ninth-century China to twenty-first-century Silicon Valley. Through eleven pivotal innovations, including the printing press, mass-produced automobiles, the McDonald's revolutionary food system, and the iPhone, Anthony reveals the hidden patterns behind world-changing breakthroughs.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us Fan MailIn this episode of Embedded Insiders, Ken sits down with Sakyasingha Dasgupta, PhD., Founder, CEO, & Chairman of Edge Cortix, to discuss Edge AI and the impact both software and hardware have when they work together efficiently at the edge.Next, Rich and Ed Kaste, the Senior Vice President of the Ultra-Low Power Business at GlobalFoundries, discuss power consumption when building an Edge-based device. GlobalFoundries is one vendor that has a lot to say about power and the rules they set around it. But first, we're highlighting some important upcoming events:Register for the 2026 Automotive Technologies Virtual Conference on May 14th. For more information, visit embeddedcomputing.com

For many years, RFID technology has been used by leading retailers such as Walmart, Macy's, and Lowe's. CVS, Zara, and others for theft prevention. But now, it is ready to go beyond this limited use case and transform supply chain logistics. In the episode, I talk to Gagan Luthra, VP of Product and Strategy at RAIN RFID leader Impinj, about the history of technology, how it is currently being used, how it is evolving to support complex supply chain use cases, including Gen2X performance enhancements, new form factors, higher processing power, and more.  We also delve into even more exciting opportunities, including using AI models for better forecasting, analytics, and trend analysis, as well as monetizing data through third-party players. Also, check out my EE Times article about RFID tackling food waste losses, utilizing Avery Dennison food labels: https://bit.ly/47APGav  Index: 00:00 - Intro 02:13 - Guest intro (Gagan Luthra) 04:41 - History and current state of RFID, expanding use cases, beyond theft prevention 06:30 - RFIDs are much more than wireless barcodes - much more information and value, from "cradle-to-grave" of products 09:25 - How RFID works without batteries - Tags are energized by an RF signal, and the receiver "reads" the reflections from the tags for identification 11:32 - Automated and Real-time information, unlike barcodes, with static information, from manual operation 15:03 - Higher initial cost of RFID compared to barcode, but much lower opex, much higher utility, and better ROI 20:30 - RFID cost curve continuing to go down, with economies of scale, wider adoption, and improvement in silicon process technology 22:19 - RAIN Alliance, standards for interoperability, difference between RAIN RFID, and NFC  25:13 - Upgrades needed beyond RFID standards for complex supply chain use cases, details of Impinj's Gen2X enhancements to address those needs, Gen2X traction   29:07 - Full backward compatibility with RAIN standards, how that works 31:30 - Edge processing needs at RFID readers, Impinj's latest announcement about R700 enhancements for readers 33:45 - How AI can power next phase of RFID - real-world, physical data for AI models, Edge AI in readers for smart decisions, utilizing cloud for better forecasting, trend analysis, and more, monetization opportunities for anonymized data for third-party players 37:59 - "Crystal Ball" question, where is RFID headed in the next 3-5 years - wider adoption across many verticals, tagging almost anything, even very low-cost items, and adoption of AI     40:35 - Closing  

Digital imaging is so ubiquitous today that it's easy to forget how improbable it once was. In this episode of TechSurge, guest host Nic Brathwaite sits down with Dr. Eric Fossum, inventor of the CMOS active pixel image sensor, to unpack the breakthrough that made it possible to embed cameras into billions of devices and the deeper lessons behind it.Eric explains how his work began not with consumer electronics, but with a NASA constraint: how to shrink a refrigerator-sized space camera into something small enough for spacecraft. The solution required a fundamental shift in architecture. By moving from CCD-based imaging to CMOS, where sensing and processing could happen on a single chip, he enabled a level of miniaturization and scalability that transformed cameras from standalone systems into embedded infrastructure.But the conversation goes far beyond the invention itself. Nic and Eric explore what it takes to commercialize deep technology, from the early days of Photobit to its acquisition by Micron, and the critical role ecosystems play in turning breakthroughs into global platforms. They discuss why intellectual property is less about protection and more about leverage, and why even the most important inventions require manufacturing scale, capital, and partnerships to succeed.The episode also looks forward. As AI systems increasingly rely on visual and physical data, sensors are shifting from tools designed for human perception to components optimized for machine intelligence. Eric highlights the challenges of pushing intelligence to the edge, the limitations of current architectures, and the growing importance of sensing technologies beyond traditional imaging—including molecular detection and new materials that go beyond silicon.While much of today's investment is concentrated in models and compute, this conversation makes the case that the next wave of innovation may come from deeper layers of the stack, where machines interact directly with the physical world. The future of AI may depend not just on how systems think, but on how they see, detect, and understand their environment.If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future Season 2 episodes.Episode LinksConnect with Eric and learn more about his work and recognition: https://engineering.dartmouth.edu/community/faculty/eric-fossum Learn more about CMOS image sensors: https://www.spacefoundation.org/space_technology_hal/active-pixel-sensor/Timestamps02:00 From CCD to CMOS: Rethinking How Images Are Captured06:45 The NASA Problem: Shrinking a Camera for Space12:30 From Refrigerator to Coffee Cup and Beyond19:30 From Lab to Market: Founding Photobit26:00 Scaling the Technology: Micron, Manufacturing, and Cost31:00 The Role of IP in Deep Tech: Leverage vs Protection39:30 From Human Vision to Machine Perception44:30 Edge AI vs Centralized Compute: Where Intelligence Lives49:30 Beyond Imaging: Molecular Sensing and New Frontiers53:30 What Comes Next: Materials, Sensors, and the Limits of Silicon

Cutting-edge research does not necessarily guarantee patient access.Welcome to Pharma Minds, Mini-Series “Who controls innovation?". In this mini-series, we explore one question in two parts: who controls innovation and who actually makes it happen.Artificial intelligence in oncology is booming. Public programs, private partnerships, and massive volumes of data are driving the field forward. Yet, as China closely observes European research, a critical issue remains: the gap between academic excellence and actual industrial deployment.In this episode, we explore where strategy meets reality with Prof. Nathalie Lassau, radiologist at the Gustave Roussy Institute (IGR), professor at Paris Saclay University, and INSERM researcher.Prof. Lassau is a master of execution. From labeling 55,000 metastases to integrating her innovations into ultrasound machines worldwide, she has spent her career bridging the gap between research, clinical practice, and private industry.Driven by relentless pragmatism and resilience, she collaborates with giants like INRIA, Canon Medical, OWKIN, and Guerbet to build revolutionary platforms for cancer prevention and treatment.But despite these massive efforts, the patient often remains caught in a fragile position between lab breakthroughs and bedside access.In this episode, we cover:◾️ The reality of AI in Oncology: How massive data and public-private partnerships are transforming cancer care.◾️ The execution gap: Why Europe produces world-class research but struggles with equal patient access.◾️ Building bridges: Prof. Lassau's insights on forcing collaboration between academia and the private sector.◾️ The global observation: How China is watching Europe's AI advancements.◾️ The power of resilience: How overcoming structural obstacles is required to drive true medical innovation.If Europe excels in AI research, why does access remain unequal? Is it regulation, industrial caution, or the fragmentation of our healthcare systems?

Send us Fan MailOn this episode of Embedded Insiders, Ken and Robert Otręba, Chief Executive Officer at GRINN, discuss the company's edge AI products and full-stack engineering services. They recap the trends and demos showcased at embedded world, highlighting the company's System on Module (SoM) and Edge AI SBC solutions. Next, Rich and Sean Dougherty, a Vice President with Everspin Technologies, discuss the current memory crisis. Specifically, skyrocketing memory costs and the large capacities needed for artificial intelligence. But first, Ken and I are talking about sustainable AI, such as the growing environmental cost of AI and the role of data centers. For more information, visit embeddedcomputing.com

In this episode, we sit down with Alexander Selegenev, Executive Director of TMT Investments, the AIM-listed venture capital firm focused on high-growth technology companies across AI, software, and fintech.Alexander opens with an introduction to TMT's business and investment philosophy, then walks us through the firm's strategy and thesis in detail.We explore how TMT balances genuine excitement about artificial intelligence with the valuation discipline required to generate returns for shareholders.We dig into the numbers, asking why deployed capital fell sharply in 2025 compared to the prior year, and what that tells us about how the team is reading the current opportunity set. Alexander then takes us through the portfolio's core holdings, including the standout story of Scale AI, which delivered a 138% uplift in just eight months following Meta's investment, and what originally attracted TMT to the business.We also look at Bolt, now EBIT positive and active in more than 800 cities globally, and discuss how close the ride-hailing giant might be to an IPO or significant exit event. On the other side of the ledger, Alexander addresses the write-downs seen over the past year and the factors behind them.Alexander provides insight into their thinking around balancing special dividends with share buybacks and what success looks like for TMT Investments. Hosted on Acast. See acast.com/privacy for more information.

What does “AI at the edge” really mean in 2026, and why does it matter now more than ever before? In this episode, we're joined by Brandon Shibley, Edge AI Solutions Engineering Lead at Qualcomm's Edge Impulse, to discuss the current state and future of Edge AI in 2026. We discuss Gen AI, Small Models, and Cascades of Models, along with real-world constraints like latency, power, and privacy. We also dive into the role of MLOps, evolving hardware, and how developers can start building practical edge AI systems today.Featuring:Brandon Shibley – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Read our Ultimate Guide to Edge AIDownload your copy of O'Reilly's AI at the Edge Check out the Edge Impulse blogSign-up for an expert led trial of Edge ImpulseUpcoming Events: Register for upcoming webinars here!

At BIO-Europe Spring 2026 in Lisbon, Portugal, web editor Nicole Raleigh spoke with Dr Olga Nissan, vice president of business development at Evogene, a computational chemistry company, specialising in the generative design of small molecules for the pharmaceutical and agricultural industries. Nissan discusses recent developments at Evogene, including its extended collaboration with Google Cloud to develop and integrate AI agents into Evogene's ChemPass AI platform, as well as its collaboration with Queensland University of Technology in the non-small cell lung cancer (NSCLC) space. She also speaks to where industry is at in its integration of cutting-edge AI into scientific research.

Daniel is joined by Dr. Veer Kheterpal. Veer has founded three technology companies and possesses full-stack expertise spanning software to silicon across edge and datacenter applications. Currently, he is the CEO & co-founder of Quadric, a semiconductor IP licensing company that delivers the blueprints for efficient,… Read More

In this episode of the Electromaker Show, Ian takes you on a fast tour through Embedded World 2026, covering the interviews, demos, and products that stood out most on the show floor. From the new Arduino Ventuno Q and native Zephyr on Arduino Nano Matter, to Nordic's in-house Edge AI tools, Bluetooth channel sounding, and satellite-connected nRF9151 demos, this episode covers a wide spread of embedded tech in one place. At the event we stopped by Silicon Labs, D-Robotics, JetBrains, Texas Instruments, DFRobot, and Epishine to look at robotics platforms, AI-enabled IDEs, sensor demos, x86 single board computers, and indoor solar energy harvesting. If you want a sharp overview of what mattered at Embedded World 2026, this is the place to start.   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: Arduino Ventuno Q Silicon Labs Bluetooth Sounding Demo Arduino Nano Matter DIY Fan Native Zephyr Arduino Nano Matter Factory Demo Shop at the Electromaker Store! Nordic Semiconductor Neuton and Axon AI demos Nordic Fuel Gauge 2.0 nRF9151 SMA NTN demo Nordic Bluetooth Sounding Demo D-Robotics Jetbrains CLion for Embedded Development Texas Instruments CC Studio IDE Texas Instruments Humanoid Robotics DFRobot Alcohol Sensing Demo Unihiker peripheral and usb example Epishine: flexible indoor solar energy Many More on our YouTube Page! %

A wearable that logs your digestion by tracking hydrogen “events,” Hollywood betting big on one-minute vertical soap operas, and Wi‑Fi 7 routers that may not do what the box implies, this hour is packed with the kind of technology news that makes you stop and go, “wait, is that real?” We take each headline and separate the joke from the actual value, because the story behind the gimmick is usually where the truth lives. We also shift into practical mode with a stack of real scam and phishing emails that show how people get trapped by urgency, fake account warnings, and that tempting unsubscribe link. We talk through the easiest tells like mismatched sender domains, scripts that don't match the offer, and why “just click to verify” is still one of the most effective social engineering moves online. If you've got family members who get nervous when they see “final notice,” this segment is worth sharing. From there, we hit modern tech contradictions: Tinder trying to fix dating app fatigue by pushing in-person singles events, and a promising offline AI board that runs local inference without relying on cloud services. Edge AI and offline AI can mean faster responses, fewer privacy risks, and less dependence on internet outages, but it also raises real questions about updates and long-term support. Subscribe for more consumer tech reality checks, share the show with a friend who needs scam-proofing, and leave us a review with the strangest tech headline you've seen lately.Support the show

BrainChip CEO Sean Hehir joins me to unpack where artificial intelligence is actually headed—and why the dominant “everything in the data center” narrative is incomplete.Most AI conversations fixate on massive models, GPU farms, and trillion-dollar infrastructure bets. This episode shifts the frame. Sean and I explore the structural reality that power consumption, latency, and grid constraints are forcing AI to decentralize—and what that means for founders, engineers, and the broader economy.Sean explains how neuromorphic computing and ultra-low-power silicon enable AI inference outside the data center—inside wearables, medical devices, drones, manufacturing systems, and even space applications. We examine why CPUs and GPUs aren't optimized for edge workloads, how custom silicon changes the economics, and why power efficiency isn't a side issue—it's the bottleneck that determines what scales.The conversation expands into workforce displacement, labor fluidity, productivity cycles, and whether technological acceleration inevitably creates unemployment crises—or simply reshuffles value creation again, as history repeatedly shows.This isn't a speculative futurism episode. It's a grounded look at model trends, infrastructure limits, and how companies survive inside a market moving at month-scale rather than decade-scale.The lesson isn't that AI replaces everything.It's that architecture determines outcomes.TL;DR* AI is centralizing in data centers—but it's also rapidly decentralizing to the edge* Power constraints will shape the next phase of AI more than hype cycles* Neuromorphic and event-driven silicon drastically reduce energy per compute* Edge AI enables medical wearables, safety detection, space systems, and industrial automation* Models are getting larger—but optimization techniques will shrink them into smaller form factors* Productivity gains historically displace tasks—not human adaptability* The future isn't about bigger servers—it's about smarter distribution* Lowest power per compute is a strategic advantage, not a marketing lineMemorable Lines* “Don't bet against humanity. We're very creative.”* “The future of AI isn't just in data centers.”* “Power isn't a feature—it's the constraint.”* “If you're the lowest power solution, you will always have customers.”* “Architecture decides what becomes possible.”GuestSean Hehir — CEO of BrainChipTechnology executive leading the commercialization of neuromorphic AI processors focused on ultra-low-power edge inference. Oversees BrainChip's evolution from early engineering innovation to market-driven, customer-focused deployment.

Behnam Bastani, CEO and cofounder of OpenInfer, breaks down why the last two years of AI feel explosive, and why the next wave is not chat, it is action at the edge.We get into always on inference, what actually forces compute to move closer to the data, and the missing layer that makes edge AI scale: the Android like infrastructure that lets devices collaborate instead of living in silos.Key takeaways• The hype spike is real, but the runway is decades, it took compute, sensors, and communication protocols maturing over generations to unlock this moment• AI is shifting from conversational to actionable, which means continuous, always on inference becomes the norm• Edge wins when cost, reliability, and data sovereignty matter, cloud and edge will coexist, but the workload placement changes• The biggest bottleneck is not just silicon, it is the infrastructure layer that makes building and deploying across devices easy, plus a shared fabric so devices can cooperate• Adoption is as much a human story as a technical one, this shift lands faster and broader than previous tech transitions, so anxiety is predictable and needs real attentionTimestamped highlights00:38 OpenInfer's mission, intelligence on every physical surface, and why collaboration matters02:07 Electricity as the earlier revolution, intelligence as the next kind of power, and the control problem05:54 Where we really are on the maturity curve, early products are here, mass adoption and safety take time08:31 When the device boundary disappears, it stops being you versus the agent, it becomes one system11:04 Always on inference, and the three forces pushing compute to the edge: cost, reliability, data sovereignty14:40 The Android moment for edge AI, why the operating system layer unlocks developers, apps, and adoptionA line worth replayingThose are going to be the three pillars that really enforces that edge and cloud are going to live together.Pro tips for builders• If your product needs real time decisions, design for intermittent networks from day one, reliability is not optional• Treat data sovereignty as a product feature, not a compliance afterthought, it is becoming the moat• Push for interoperability early, the fabric that lets devices share the right data is what makes edge feel seamlessCall to actionIf this episode helped you rethink where AI should run and what it takes to ship it in the real world, follow the show and share it with one builder who is working on edge, robotics, devices, or applied AI.

As someone who spends a lot of time covering AI announcements, product launches, and conference stages, it is easy to forget that most AI today is still built for desks, screens, and digital workflows. Yet the reality is that the vast majority of the global workforce operates in the physical world, on roads, construction sites, depots, and job sites where mistakes are measured in injuries, collisions, and lives lost. That gap between where AI innovation happens and where real risk exists is exactly why I wanted to sit down with Amish Babu, CTO at Motive. In this episode, I speak with Amish about what it truly means to build AI for the physical economy. We unpack why designing AI for vehicles, fleets, and safety-critical environments is fundamentally different from building AI for emails, documents, or dashboards. Amish explains why latency, trust, and reliability are non-negotiable when AI is embedded directly into vehicles, and why edge AI, multimodal sensing, and on-device compute are essential when milliseconds matter. This is a conversation about AI that has to work perfectly in messy, unpredictable, real-world conditions. We also explore how Motive approaches AI as a full system, combining hardware, software, and models into a single platform built specifically for life on the road. Amish shares how AI can help prevent collisions, support drivers in the moment, and create measurable safety and operational outcomes for fleets operating across transportation, construction, energy, and public sector environments. Along the way, we challenge common misconceptions around AI in vehicles, including the idea that it is about surveillance rather than protection, or that all AI systems are created equal when lives are on the line. If you are interested in how AI moves beyond productivity tools and into high-stakes environments where safety, accountability, and trust matter most, this episode offers a grounded and practical perspective from someone building these systems every day. I would love to hear your thoughts on this one. How do you see the role of AI evolving as it moves deeper into the physical world? Useful Links Connect with Amish Babu Learn More About Motive How Motive's AI works: Real-time edge intelligence, humans-in-the-loop, and continuous improvement.

Doug Green, Publisher of Technology Reseller News, spoke with Dinakar Munagala, CEO & Co- Dinakar Munagala Founder of Blaize, and Joseph Sulistyo, SVP of Corporate Marketing, about Blaize's push to make AI inference practical outside the data center—and why a new strategic collaboration with Nokia is designed to accelerate that shift, especially across Asia Pacific. Blaize positions itself as an AI computing company built around a purpose-built, fully programmable processor architecture it calls a graph streaming processor, paired with software intended to simplify development of “real-world” AI. Munagala framed the company's focus as practical AI inference for environments like smart factories, smart cities, agriculture, defense, and other edge and hybrid deployments where latency, power, thermal limits, and operating conditions are non-negotiable. A centerpiece of the discussion was Blaize's announcement that Nokia is strengthening edge AI capabilities through a strategic collaboration with Blaize to deliver hybrid inference solutions across APAC. Munagala and Sulistyo described the move as a signal that AI's next phase isn't only about large-scale training in centralized data centers, but about deploying inference where outcomes are realized—near cameras, sensors, machines, and field infrastructure. In their view, Nokia's global reach in networking, automation, and integration creates a path to deliver end-to-end solutions that combine connectivity and compute for real deployments, not demos. Sulistyo emphasized the economics driving hybrid inference: cost-sensitive, power-constrained environments often cannot justify a single “monolithic” compute approach. Instead, he argued, the market is moving toward heterogeneous architectures—mixing different compute types to hit performance targets while controlling total cost of ownership. In APAC, he noted, the scale of deployments makes marginal savings meaningful, and hybrid designs become an operational requirement, not a preference. The conversation also connected edge inference to public-sector and community outcomes. Both executives highlighted smart-city use cases—such as traffic management, tolling, and first-responder automation—where real-time inference can improve accuracy and responsiveness while reducing labor-intensive processes. They extended that point to rural and underserved regions, arguing that “smart city” also includes municipalities and regional governments, where automation and analytics can unlock revenue (e.g., tolls and fines) while improving safety. Doug pushed on definitions and practicality, prompting Munagala to describe edge inference as compute performed as close as possible to the sensor—for example, processing video near a camera mounted on a pole, at a toll booth, or in a factory—so systems can detect events and respond with low latency. He added that some deployments may route inference to nearby on-prem servers or regional data centers, depending on architecture and proximity, and Blaize aims to support these variations with a common hardware/software platform. Blaize also addressed the “AI energy speed bump” impacting communities and operators—particularly where power availability and cost are constrained. Munagala said low power is foundational to Blaize's design goals and argued that purpose-built inference architectures can reduce the burden associated with power-hungry AI approaches. Sulistyo added that the broader infrastructure conversation increasingly includes cooling realities (air and liquid) and the need to match the deployment environment to the right compute profile. To ground “real-world AI” in examples, the guests pointed to deployments including license plate recognition in complex, variable conditions and traffic anomaly detection (identifying behavior that deviates from normal flow). They described these as compute-intensive workloads that must run reliably outdoors and under harsh conditions, where latency and endurance matter as much as accuracy. They also discussed retail analytics as another example of edge inference delivering measurable business outcomes by connecting what happens in-store to revenue-driving decisions. Looking ahead, Munagala described the Nokia collaboration as a model for additional partnerships that bring inference solutions into production environments at scale. Sulistyo noted APAC is the initial focus, with other regions expected to follow based on demand, proof points, and the prioritization of specific use cases. To learn more about Blaize and its technology, visit https://www.blaize.com/.

What if your classroom could adapt to each learner without handing their data to the cloud? That's the promise we dig into with technologist and founder Sebastien Fenelon, whose journey from scarce resources in Haiti to building privacy-first, edge AI tools reframes what “future-ready” really means for educators and instructional designers.We start with the power of resilience—how self-taught coding, late-night study sessions, and community support can outpace limited infrastructure—and move into practical strategies for teaching code with clarity and context. Sebastien shares why AI should compress project timelines, not critical thinking, and offers a simple “100-hour” ramp to acquire new languages fast. From K–12 to higher ed, we outline how to design small, visible wins that build confidence while using AI to scaffold learning rather than replace it.We close with a playbook for staying adaptable: keep learning in focused sprints, plug into communities that share what works, and seek mentors who reveal the path behind the skills. If you're ready to personalize learning, protect student data, and keep your curriculum uniquely yours, this conversation offers a clear blueprint. If it resonates, follow and share with a colleague, and leave a quick review to help more educators find thoughtful, practical guidance on AI in the classroom.

On this episode of That Tech Pod, we talk with Logan Lawler, Senior Director at Dell Technologies, about what it takes to make AI actually work in the real world. Logan shares his 16-year journey at Dell and why his focus today is less on hype and more on practical infrastructure choices that enable AI at scale.We break down Edge AI versus Cloud AI with clear, concrete examples, including how GPU-accelerated desktops, workstations, and hybrid cloud setups can turn “that's impossible” AI problems into manageable ones. Logan also highlights why storage, not compute, is often the biggest bottleneck, and the common mistakes organizations make when data can't keep up with GPUs. The conversation gets into energy and sustainability, from the environmental cost of massive data centers to what it means when nuclear power and AI collide. We also explore the human side of AI: whether instant answers are making us lazier, why struggle is still essential for learning, and how that idea shows up in parenting, education, and work. We close with real-world edge AI success stories, a few cautionary tales, and some lighter moments, making this a grounded discussion on AI, infrastructure, and the tradeoffs we rarely talk about.Logan Lawler works at Dell Technologies, where he leads strategy for Dell Pro Precision AI Solutions. Over his 16-year career at Dell, he's worked across sales, marketing, and e-commerce, and now helps enterprises and creative studios leverage high-performance AI workstations and hybrid cloud infrastructure. A frequent speaker and media guest, Logan explains how GPU-accelerated PCs and storage solutions are transforming industries from film and animation to healthcare research. Logan was raised in Missouri and is a graduate of the University of Missouri. He now lives in Texas with his family.

On this episode of China Manufacturing Decoded, Adrian is joined by Kate, who leads the supply chain management team at The Sophist Group, to unpack her top takeaways from CES 2026. Kate reports on the scale of the show, who was there, and what matters for product teams, developers and manufacturing leaders.   Episode Sections: 01:00 – CES 2026 overview: scale, attendance & significance Kate gives headline numbers: attendance, international visitors, exhibitors, and why this was the biggest post-pandemic CES. 02:19 – Why CES still matters: networking & deal-making CES is positioned as a major networking event for hardware companies, startups, and partners. 02:57 – Surge of Chinese exhibitors at CES Kate explains the sharp increase in Chinese suppliers and how Eureka Park has changed. 03:55 – Eureka Park explained & why it matters What Eureka Park is, why it's important, and how it differs from the main convention halls. 04:36 – Humanoid robots emerge as the biggest trend Robotics numbers, China's dominance, and the rise of affordable humanoid robots. 05:09 – Real-world humanoid robot capabilities Examples of shipping models, pricing, applications, and programmability. 06:36 – From viral clips to serious industrial AI Discussion of public misconceptions vs what was actually demonstrated at CES. 07:31 – Physical AI & China's hardware advantag Why China excels at turning AI concepts into physical products quickly and cheaply. 08:16 – Regulation risks & trade considerations Concerns about regulation, drones, and geopolitical limits when using Chinese AI hardware.  09:01 – Western tech giants respond (chips, OS, industrial AI) NVIDIA, Siemens, Qualcomm, and others building humanoid and robotics ecosystems.  10:06 – Edge AI & on-device intelligence Shift toward low-power, on-device AI for privacy, speed, and autonomy.  11:08 – Other global players at CES France, Korea, Hong Kong, and their strengths across AI, mobility, health tech, and industry.  13:04 – Fun tech, tracking & wearables everywhere Smart collars, VR Lego, transparent displays, health tracking, and elder-care tech.  14:49 – AI in smart manufacturing & formulation AI-assisted production, cosmetics, materials mixing, and industrial applications.  15:51 – Manufacturing strategy discussions at CES Conversations with exhibitors about shifting production out of China — and back again.  16:28 – Why companies return to China for early runs Speed, ecosystem depth, prototyping, and complex AI electronics remain China's edge.  17:11 – Hybrid manufacturing strategies Starting in China, then diversifying later once scale and risk justify it.  18:09 – Tariffs, uncertainty & predictability Why geopolitical volatility elsewhere makes China comparatively predictable for many US firms.  19:38 – Final takeaways: manufacturing is mathematics No single recipe — strategy depends on product, scale, cost, and risk.  20:03 – Wrap-up & Sofeast support Adrian summarizes, invites listeners to get in touch, and closes the episode.    Related content… Best of CES 2026 - The Verge 7 Crazy Robots at CES 2026 Get in touch with us Connect with us on LinkedIn Contact us via Sofeast's contact page Subscribe to our YouTube channel Prefer Facebook? Check us out on FB

What happens when the AI race stops being about size and starts being about sense? In this episode of Tech Talks Daily, I sit down with Wade Myers from MythWorx, a company operating quietly while questioning some of the loudest assumptions in artificial intelligence right now. We recorded this conversation during the noise of CES week, when headlines were full of bigger models, more parameters, and ever-growing GPU demand. But instead of chasing scale, this discussion goes in the opposite direction and asks whether brute force intelligence is already running out of road. Wade brings a perspective shaped by years as both a founder and investor, and he explains why today's large language models are starting to collide with real-world limits around power, cost, latency, and sustainability. We talk openly about the hidden tax of GPUs, how adding more compute often feels like piling complexity onto already fragile systems, and why that approach looks increasingly shaky for enterprises dealing with technical debt, energy constraints, and long deployment cycles. What makes this conversation especially interesting is MythWorx's belief that the next phase of AI will look less like prediction engines and more like reasoning systems. Wade walks through how their architecture is modeled closer to human learning, where intelligence is learned once and applied many times, rather than dragging around the full weight of the internet to answer every question. We explore why deterministic answers, audit trails, and explainability matter far more in areas like finance, law, medicine, and defense than clever-sounding responses. There is also a grounded enterprise angle here. We talk about why so many organizations feel uneasy about sending proprietary data into public AI clouds, how private AI deployments are becoming a board-level concern, and why most companies cannot justify building GPU-heavy data centers just to experiment. Wade draws parallels to the early internet and smartphone app eras, reminding us that the playful phase often comes before the practical one, and that disappointment is often a signal of maturation, not failure. We finish by looking ahead. Edge AI, small-footprint models, and architectures that reward efficiency over excess are all on the horizon, and Wade shares what MythWorx is building next, from faster model training to offline AI that can run on devices without constant connectivity. It is a conversation about restraint, reasoning, and realism at a time when hype often crowds out reflection. So if bigger models are no longer the finish line, what should business and technology leaders actually be paying attention to next, and are we ready to rethink what intelligence really means? Useful Links Connect with Wade Myers Learn More About MythWorx Thanks to our sponsors, Alcor, for supporting the show.

What does “trust” really mean when AI lives at the edge? Welcome to Edge of Tomorrow – The Edge AI Debate, our spin-off series from The IoT Podcast, created in collaboration with the  @edgeaifoundation  This series brings together leading voices from across the Edge AI ecosystem to debate the toughest questions shaping its future. In this episode, host Pete Bernard (CEO, EDGE AI FOUNDATION) is joined by Rosario Cammarota (Chief Scientist, Intel Privacy Lab) and Aydin Aysu (Founder, MithrilAI) to tackle: Can you trust Edge AI - and if so, where does that trust really come from? As intelligence becomes distributed across edge devices, the traditional assumptions around privacy, security, and ownership start to break down. This conversation digs into how trust changes when AI runs locally, whether hardware can (or should) be trusted, and what it means for users, builders, and regulators alike. From cryptographic techniques like homomorphic encryption to real-world deployment scenarios, the debate explores what it actually takes to build Edge AI systems that are not only powerful, but trustworthy. Chapters… 00:00 Introductions & debate setup 02:30 What does “trust” mean when AI lives at the edge? 07:10 Edge vs. cloud: control, risk, and responsibility 11:40 Can we secure Edge AI without trusting hardware? 17:20 The role of homomorphic encryption 22:30 Data ownership, governance, and user sovereignty 28:40 Real-world Edge AI deployments and security trade offs 34:10 Final reflections: rebuilding trust in the Edge AI stack  The episode is live now on all major podcast platformsListen here: https://linktr.ee/theiotpodcast What's your take? Join the debate in the comments. Connect with our guests… Rosario Cammarota – Chief Scientist, Intel Privacy Lab: https://www.linkedin.com/in/ro-cammarota-a226b817/ Aydin Aysu – Founder, MithrilAI: https://www.linkedin.com/in/aydinaysu/ Moderator: Pete Bernard – CEO, EDGE AI FOUNDATION: https://www.linkedin.com/in/bernardpete/ About Edge of Tomorrow – The Edge AI Debate Edge of Tomorrow is our dedicated debate series bringing together technologists, researchers, and industry leaders to tackle the most pressing and controversial questions in Edge AI. 

Jan. 13, 2026- Assemblymember Alex Bores, a Manhattan Democrat, and State Sen. Andrew Gounardes, a Brooklyn Democrat, discuss the fate of their 2025 bill to regulate cutting-edge artificial intelligence development, which was the subject of intense lobbying and got tweaked by Gov. Kathy Hochul.

Edge AI is evolving quickly - what's changing in the tooling and frameworks that support it? And where do the biggest opportunities for improvement lie? In this episode of Edge of Tomorrow – The Edge AI Debate, host Pete Bernard (CEO, EDGE AI FOUNDATION) is joined by Elia Schoenberger (Product Marketing, AI Division at Civa) and Nathan Francis (Business Development at AIZip) for an in-depth discussion on the role of tooling and frameworks in shaping the future of Edge AI. While much of the attention in AI is placed on models and hardware, this conversation focuses on the layers in between — compilers, SDKs, deployment pipelines, and frameworks — and how they influence speed, scalability, and collaboration across the ecosystem. The discussion explores how hardware constraints, model design, and tooling choices intersect, whether the industry is moving toward standardisation or continuing to prioritise innovation, and what practical steps could help simplify Edge AI development without slowing progress. This episode offers a look at how the Edge AI stack is evolving - and what it will take to support broader, more efficient deployment in the years ahead. Chapters… 00:00 Introductions 01:40 Why tooling and frameworks matter in Edge AI 03:25 Hardware constraints, models, and deployment realities 05:23 Fragmentation vs fit-for-purpose tooling 07:59 Power, performance, and memory trade-offs 09:18 Where Edge AI sits on the maturity curve 11:32 Standardisation, innovation, and ecosystem balance 13:32 Compilers, MLIR, and unifying the toolchain 16:02 Deployment challenges and quantisation complexity 25:17 Generative models arriving at the edge 31:36 Local-first intelligence and when the cloud still matters 32:52 What would help accelerate Edge AI development 36:13 Final reflections and closing thoughts The episode is live on all major listening platforms now: https://linktr.ee/theiotpodcast Connect with our guests… Elia Schoenberger (CIVA,Inc): https://www.linkedin.com/in/eliashenberger/ Nathan Francis (AIZip): https://www.linkedin.com/in/nathanfrancis99/ About Edge of Tomorrow – The Edge AI Debate Edge of Tomorrow is our debate-led spin-off series bringing together leaders from across the Edge AI ecosystem to explore the technical, commercial, and strategic decisions shaping how intelligence moves closer to the real world. SUBSCRIBE TO THE IOT PODCAST ON YOUR FAVOURITE LISTENING PLATFORM: https://linktr.ee/theiotpodcast Sign up for exclusive email updates: https://theiotpodcast.com/get-exclusive-access/ Contact us to become a guest or partner: https://theiotpodcast.com/contact/

In this episode of Eye on AI, Craig Smith sits down with Anurag Dhingra, Senior Vice President and General Manager at Cisco, to explore where AI is actually creating value inside the enterprise. Rather than focusing on flashy demos or speculative futures, this conversation goes deep into the invisible layer powering modern AI: infrastructure. Anurag breaks down how AI is being embedded into enterprise networking, security, observability, and collaboration systems to solve real operational problems at scale.  From self-healing networks and agentic AI to edge computing, robotics, and domain-specific models, this episode reveals why the next phase of AI innovation is less about chatbots and more about resilient systems that quietly make everything work better. This episodeis perfect for enterprise leaders, AI practitioners, infrastructure teams, and anyone trying to understand how AI moves from theory into production. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Why AI Only Matters If the Infrastructure Works (01:22) Cisco's Evolution (04:39) Connecting Networks, People, and Experiences at Scale (09:31) How AI Is Transforming Enterprise Networking (12:00) Edge AI, Robotics, and Real-World Reliability (14:18) Security Challenges in an Agent-Driven Enterprise (15:28) What Agentic AI Really Means (Beyond Automation) (20:51) The Rise of Hybrid AI: Cloud Models vs Edge Models (24:30) Why Small, Purpose-Built Models Are So Powerful (29:19) Open Ecosystems and Agent-to-Agent Collaboration (33:32) How Enterprises Actually Adopt AI in Practice (35:58) Building AI-Ready Infrastructure for the Long Term (40:14) AI in Customer Experience and Contact Centers (44:14) The Real Opportunity of AI and What Comes Next

Welcome to episode 335 of The Cloud Pod, where the forecast is always cloudy! Welcome to the first show of 2026, and it's a full house, too! Justin, Jonathan, Ryan,  and Matt are all here to reflect on 2025, plus bring you their predictions for 2026. Let's get started!  Titles we almost went with this week SQL Me Maybe: AlloyDB Gets Chatty With Your Database **OpenAI SELECT * FROM natural_language WHERE accuracy LIKE ‘100%’ **Anthropic etcd You Were Worried About Database Limits: CloudWatch Has Your Back CSV You Later: Looker Adds Drag-and-Drop Data Uploads AWS Spots an Opportunity to Manage Your Container Costs EKS Network Policies: No More IP Address Whack-a-Mole AWS Security Hub Splits: It’s Not You, It’s CSPM Spot On: ECS Finally Manages Your Cheapest Compute TOON Squad: DigitalOcean’s New Format Makes JSON Look Bloated The Price is Wrong: AWS Breaks Two Decades of Downward Pricing Tradition Show Your Work: Why AI-Generated Code Without Tests is Just Expensive Spam No More Agent Orange: Google Simplifies VM Extension Deployment AWS Discovers Prices Can Go Both Ways, Raises GPU Costs 15 Percent Sovereignty Washing: When Your European Cloud Still Answers to Uncle Sam Agent Builder Gets a Memory Upgrade: Google’s AI Finally Remembers Where It Put Its Keys Ctrl+F for the Future: A year-end Scorecard & Next-Gen Bets AI Agents, GPU Prices, and The best of the Cloud Pod 2025 Beyond the Hype: The Cloud Pods Definitive 2025 Year in Review Apocalypse Now… What? Our 2026 Forecast Follow Up  01:27 RYAN’S PREDICTIONS Prediction Status Notes Quick LLM models for individuals ACCURATE Meta-Llama-3.1-8B-Instruct, GLM-4-9B-0414, and Qwen2.5-VL-7B-Instruct—each chosen for an outstanding balance of performance and computational efficiency, making them ideal for edge AI deployment. A new AI inference application called Inferencer allows even modest Apple Mac computers to run the largest open-source LLMs. AI at the edge natively (Lambda-esque) ACCURATE Akamai launched a new Inference Cloud product for edge AI using Nvidia’s Blackwell 6000 GPUs in 17 cities. AWS IoT Greengrass with Lambda functions for edge logic. “Edge AI allows for instant decision-making where it matters most—close to the data source.” Cloud native security mesh multi-cloud UNCLEAR Service mesh technologies continue to evolve (Istio, Linkerd), but I didn’t find a breakthrough “app-to-app at the edge” security mesh product announcement in 2025. This one needs more specific evidence. Ryan Score: 2/3 02:25 MATTHEW’S PREDICTIONS Prediction Status Notes FOCUS adopted by Snowflake or Databricks ACCURATE FOCUS version 1.2 was ratified on May 29, 2025. Three new providers announced support: Alibaba Cloud, Databricks, and Grafana. Databricks officially adopted FOCUS! AI security/ethical standard (SOC or ISO) ACCURATE ISO 42001 is the first international standard outlining requirements for AI governance. Major companies achieving certification in 2025: Automation Anywhere is among the first 100 companies worldwide to earn ISO/IEC 42001:2023 certification. Anthropic also achieved ISO 42001 certification. Amazon deprecates 5+ services (WorkMail bonus) ACCURATE (no bonus) 19 services are mothballed, four are being sunset, and one is end of its supported life. Deprecated services include CodeCommit, Cloud9, S3 Select, CloudSearch, SimpleDB, Forecast, Data Pipeline, QLDB, Snowball Edge, and more. WorkMail NOT deprecated – WorkDocs was (April 2025), but WorkMail remains active. Matthew Score: 3/3 03:22 JONATHAN’S PREDICTIONS Prediction Status Notes Company claims AGI achieved ACC

GlobalLogic Inc., a Hitachi Group Company and leader in digital engineering, has released a new report, in partnership with HFS Research, that highlights insights into how industrial enterprises are managing AI adoption, sustainability transitions, and workforce transformation. The research reveals that despite executive ambitions, 51% of organisations cite skills gaps as the primary reason AI and advanced technology initiatives fail or underperform. The research, which surveyed more than 100 C-level and senior executives from $1 billion+ industrial firms across automotive, aerospace, chemicals, energy and utilities, and construction, highlights a clear challenge: while leaders acknowledge the urgency of AI, sustainability, and talent transformations, a fundamental misalignment between present priorities and future expectations is halting innovation. "We undertook this research to understand why industrial leaders see AI, sustainability, and talent as top priorities yet struggle to turn them into measurable results," said Srini Shankar, President and CEO at GlobalLogic. "We found many are trying to deploy advanced technologies without the talent, the clear AI governance frameworks, and without transition plans that link today's efficiency pressures to tomorrow's strategic goals. As onshoring accelerates in the United States, leaders face rising domestic demand but scarce and costly specialised talent. "At GlobalLogic, we're moving beyond experimentation to deliver AI-driven industrial ecosystems that create measurable value today. By combining our deep heritage in embedded systems, Edge AI, IT-OT convergence, OT cybersecurity, Industrial IoT, and next-generation connectivity, such as 5G/6G, GlobalLogic delivers the core capabilities industrial clients need to advance their Physical AI journeys. "When combined with Hitachi's proven OT and product excellence, we are empowering organisations to modernise faster, operate smarter, and accelerate their transformation across sustainability, productivity, and talent. Together with our industrial clients, we are advancing next-generation capabilities in servitisation, digital twins, industrial automation, predictive maintenance, and frontline worker productivity and safety - helping them unlock new revenue models while driving meaningful gains in operational efficiency and performance." Key Findings from the Report: The study reveals that industrial enterprises are trapped between ambition and capability, lacking the talent, frameworks, and integration strategies to execute on generational transitions: Upskilling Becomes the New Imperative: While 51% of companies say skills gaps hinder AI and advanced technology initiatives, half lack structured upskilling programs, and 42% struggle to find digital and AI talent. As seasoned workers retire and fewer new candidates enter traditional roles, industrial leaders are turning to agentic AI and sustainability-driven innovation to bridge the divide. Legacy Systems Create Technical Debt & Block Progress: Legacy systems create technical debt and are a clear sign of limited readiness to support the new, 'intelligent,' connected operating models required for technologies like agentic AI. Nearly half (49%) identify integrating new technologies with legacy systems as their greatest barrier to deploying advanced digital technologies. Priorities Shift to AI: Nearly half (46%) of executives currently prioritise reducing operational costs in their top three priorities, but research shows that in 2 years, AI adoption and operational optimisation will take top spot in priorities. Industry Seen as Career Dead-End: 58% believe talent sees limited career mobility in the manufacturing sector, 48% cite lack of innovation perception, and 46% acknowledge underpaying compared to other sectors - fueling a deepening talent crisis. "Industry executives must immediately embed their sustainability, talent, and technology transitions in both strategy and daily operat...

AI is devouring the planet's electricity ... already using up to 2% of global energy and projected to hit 5% by 2030. But a Spanish-Canadian company, Multiverse Computing, says it can slash that energy footprint by up to 95% without sacrificing performance.They specialize in tiny AI: one model has the processing power of just 2 fruit fly brains. Another tiny model lives on a Raspberry Pi.The opportunities for edge AI are huge. But the opportunities in the cloud are also massive.In this episode of TechFirst, host John Koetsier talks with Samuel Mugel, Multiverse's CEO, about how quantum-inspired algorithms can drastically compress large language models while keeping them smart, useful, and fast. Mugel explains how their approach -- intelligently pruning and reorganizing model weights -- lets them fit functioning AIs into hardware as tiny as a Raspberry Pi or the equivalent of a fly's brain.They explore how small language models could power Edge AI, smart appliances, and robots that work offline and in real time, while also making AI more sustainable, accessible, and affordable. Mugel also discusses how ideas from quantum tensor networks help identify only the most relevant parts of a model, and how the company uses an “intelligently destructive” approach that saves massive compute and power.00:00 – AI's energy crisis01:00 – A model in a fly's brain02:00 – Why tiny AIs work03:00 – Edge AI everywhere05:00 – Agent compute overload06:00 – 200× too much compute07:00 – The GPU crunch08:00 – Smart matter vision09:00 – AI on a Raspberry Pi10:00 – How compression works11:00 – Intelligent destruction13:00 – General vs. narrow AIs15:00 – Quantum inspiration17:00 – Quantum + AI future18:00 – AI's carbon footprint19:00 – Cost of using AI20:00 – Cloud to edge shift21:00 – Robots need fast AI22:00 – Wrapping up

My podcast guest this week is EMASS CEO Mark Goranson. Mark and I chat all about the biggest challenges of edge AI development today, the features included in the EMASS SDK and the details of their ultra-low-power edge AI SoC called EMASS ECS-DoT.

Kirin Sinha, MIT math prodigy and founder/CEO of Illumix, embodies the vital intersection of AI, XR, and real-world relevance. On this episode, she unpacks the hard realities of spatial computing's journey—from grinding through MIT at sixteen and “building the Iron Man desk as a senior project” to launching Five Nights at Freddy's AR (garnering 60M+ downloads) and powering Disney/Six Flags location-based XR.Sinha challenges the XR hype machine: “Location-based constraints are the best sandbox. Real-world variability, lighting, edge compute, and privacy aren't just demos—they're survivability.” She candidly discusses why the first era of mobile AR rarely survived outside of theme parks and why the true metaverse won't arrive through geofenced phone gimmicks, but rather from ambient cameras, context-aware AI, and wearables that deliver daily relevance.The conversation dives into XR's scaling riddle: most startups go too big, too soon—Illumix ran lean and learned real lessons from thousands of live deployments before expanding. Sinha's take on platform dominance? “Whoever pairs visual context with an always-on, lightweight wearable—without being creepy—wins.” She weighs the mergers-and-acquisitions question with nuance (“you keep every door open, but we've built for independence and profitability”), and explains exactly why Niantic's follow-up AR games failed to recapture Pokemon Go's lightning-in-a-bottle.Guest HighlightsEnrolled at MIT at 16; bridge between math, AI, and real-world camera vision.Founded Illumix, powering everything from “Five Nights at Freddy's” AR (60M+ organic downloads) to Disney and Six Flags' location-driven XR.Deep infrastructure: dynamic, privacy-first, real-time spatial intelligence at the edge, not reliant on the cloud.Insights on product-market fit and startup timing: “Most of the world's ‘available' XR space is dead space without a ‘why' for users.”Honest, nuanced take on M&A, survival, and why lean teams win when timing finally shifts.News SegmentNvidia's $4.5T valuation—is big tech over-hyped, or will foundational arms dealers keep winning while everyone else corrects?Major tech layoffs attributed to AI “efficiency”—stock prices keep rising as automation accelerates, but most Americans are left behind.Brendan Iribe's $300M AI/AR glasses startup—a kinder, context-aware approach to ambient interfaces, but does anyone actually break out from the pack?Google/Magic Leap factory reboot, patent arsenal, and Surface team members cycling across Meta and Apple—XR's “three Spider-Mans” all fight for the same future.OpenAI's privatization and AGI date bets—the team debates when, how, and if superintelligence IPOs.XR economy is in a phase shift—who survives, who gets acquired, and who makes it to scale?Special thanks to our sponsor Zappar. Subscribe for weekly insider takes from industry veterans who aren't afraid to challenge Big Tech. New episodes every Tuesday. Watch the full videos on YouTube. Hosted on Acast. See acast.com/privacy for more information.

Recorded live at NVIDIA's first GTC conference in Washington, D.C., this special episode of the Washington AI Network Podcast features four of NVIDIA's top innovators and partners on how AI, supercomputing, and robotics are transforming telecom, healthcare, and quantum computing. Host Tammy Haddad speaks with Ronnie Vasishta, SVP of Telecom at NVIDIA, on 6G and AI-powered networks, Kimberly Powell, VP of Healthcare at NVIDIA,  on intelligent hospitals and drug discovery, Pranav Gokhale, CTO of Infleqtion, on connecting quantum processors to NVIDIA GPUs, and Deepu Talla, VP of Robotics and Edge AI at NVIDIA,  on autonomous robots and the future of work.

In this episode of Convergence.fm, Ashok Sivanand sits down with Farhan Thawar, Head of Engineering at Shopify, to go behind the scenes of how Shopify not only keeps pace with rapid change but leads it.  The discussion explores how Shopify became one of the first platforms to allow merchants to sell products directly inside ChatGPT, why that move challenges Amazon's dominance, and what it takes to build a company that learns faster than it fails.  Farhan explains the systems that make being first repeatable rather than accidental, including Shopify's internal LLM proxy, MCP servers, experimentation culture, and democratized tooling.  If you are a CEO, COO, or CTO looking to scale through culture, systems, and intentional technology adoption, this episode shows what it looks like to operate with conviction and long-term relevance. Key Topics and Moments: Shopify and OpenAI's commerce integration. The same day OpenAI enabled in-chat shopping, Shopify merchants were already live. Farhan explains what it takes for a company of Shopify's size to move with that kind of speed Competing with Amazon through culture, not size. Shopify has 3,000 engineers compared to Amazon's 35,000+, yet continues to outpace bigger players by focusing on coherence, focus, and empowered execution rather than bureaucracy and scale. The meaning behind Tobi Lütke's April AI memo. Farhan discusses how Shopify operationalized its “AI is non-optional” stance, what baseline expectations look like, and how performance is evaluated in an AI-native organization. AI reflexivity and the “three buckets.” Farhan explains how teams are taught to recognize “AI not allowed,” “AI optional,” and “AI mandatory” problems so that employees develop instinct for when to reach for AI — and when to pick up the screwdriver. The risk of ‘vibe coding' and why hand tools still matter. Farhan shares lessons from real incidents inside and outside Shopify, like the Cloudflare outage caused by unreviewed AI-generated code, and how engineering leaders teach judgment, not just prompting. The LLM Proxy and MCP Servers. Inside look at how Shopify democratized AI across departments by building an internal platform that connects all major models and corporate data sources, enabling every employee to build workflows and ask intelligent questions — not just engineers. AI budgeting vs. SaaS budgeting. Farhan explains why AI usage isn't treated like traditional SaaS spend and how Shopify encourages heavy experimentation by rewarding impact rather than punishing token consumption. Experimentation as a system. How teams are encouraged to show work at 20%, not 80%, and why the speed of learning, not perfection, is the true productivity metric. Subtraction as leadership. Farhan shares how founders and executives must delete outdated processes, rules, and layers of bureaucracy to make room for new ideas — why process should only exist if it makes something possible or 10x better. Hiring and growing AI-native talent. Why Shopify doubled down on internships, hiring 1,000 interns this year and next, and how younger engineers push full-timers to stay current by being born AI-native “centaurs.” Responsibility versus accountability. Why leaders can delegate tasks but not responsibility, and how to stay in the work without disempowering the team. Certainty as intolerance. Farhan's reflection on why overconfidence kills creativity, and how leaders can replace fixed beliefs with wayfinding, curiosity, and adaptive decision-making. Rapid-fire reflections for CEOs. Ashok and Farhan close with lessons on showing unfinished work, modeling curiosity, and removing friction as a cultural operating system. Who Should Listen: Mid-market CEOs, COOs, and CTOs building adaptable organizations that can scale.  Leaders focused on culture and transformation, not just technology adoption.  Operators who want to apply product thinking and modern software practices to traditional industries. Notable Quotes: “We have a baseline expectation of using AI. If you have two people, one using AI and one not, they will both be evaluated the same.” – Farhan Thawar on AI usage expectations  “We don't like waste, but we don't have limits. If you believe in your workflow, use the best model for your problem solving.” – Farhan Thawar on AI token cost and consumption   “You can now buy directly in chat from Shopify merchants. That is a major shift in how people discover and buy online.” – Ashok Sivanand on Shopify launching all their merchants on ChatGPT's Shop feature on the very day it was launched  Related Reading and References: Shopify Blog: Shopify and OpenAI bring commerce to ChatGPT (official announcement) - https://www.shopify.com/news/shopify-open-ai-commerce?podconvergence   Reuters: OpenAI partners with Shopify, Stripe, and others to expand ChatGPT integrations - https://www.reuters.com/world/americas/openai-partners-with-etsy-shopify-chatgpt-checkout-2025-09-29/?podconvergence   TechCrunch: Inside Tobi Lütke's AI Memo and Shopify's Cultural Shift - https://techcrunch.com/2025/04/07/shopify-ceo-tells-teams-to-consider-using-ai-before-growing-headcount/?podconvergence  Farhan's opinions about token consumption - https://x.com/fnthawar/status/1930367595670274058  Farhan's article about “looking stupid”- https://medium.com/helpful-com/why-looking-stupid-is-my-superpower-2ee3fe00a748?podconvergence  The Convergence.fm first episode with Farhan in 2024 - https://convergence.fm/episode/from-code-to-culture-how-shopify-thrives-under-farhan-thawars-thought-leadership  The Convergence.fm Episode about Tobi Lütke's leaked AI memo mandate, and our 6 takeaways - https://convergence.fm/episode/shopifys-leaked-ai-mandate-explained-6-takeaways-for-your-product-team  Tobi's memo Tweet - https://x.com/tobi/status/1909231499448401946 Unreasonable Hospitality (book) - https://www.amazon.com/Unreasonable-Hospitality-Remarkable-Giving-People/dp/0593418573  Farhan's Twitter (public handle) - https://x.com/fnthawar  Reflection and Action Steps: Start with your mission. Before choosing tools, clarify what problem you are solving and what your business stands for.  Enable your team. Ask whether you are removing barriers or creating them.  Are employees empowered to experiment?  Model the change. Use AI tools yourself. Share your learnings, wins, and failures openly. F Foster learning. Consider introducing internal forums or “thinking clubs” that encourage curiosity and reflection across your team.  

In this episode, Arm's Paul Williamson and VDC Research's Chris Rommel unpack the findings from a new industry study exploring how edge AI is reshaping the future of embedded systems and IoT development. The conversation spans the evolving role of software, the rise of Python and Linux in embedded engineering, and how Arm's ecosystem and compute platforms are enabling scalable, intelligent edge solutions.

Send us a textWant to know what “better hearing in noise” actually sounds like when AI, sensors, and human care work in sync? We bring together Starkey's president and CEO, Brandon Sawalich, and Chief Hearing Health Officer, Dr. Dave Fabry, for a candid look at Starkey Omega AI—why it exists, what changed from Edge AI, and how it turns hearing aids into confident, 360-degree listening tools without sidelining professionals.We dig into DNN 360 and how deep neural networks now blend noise management with directionality and low-latency binaural processing to deliver measurable gains in speech understanding. Dave explains the role of IMU sensors in tracking movement and intent—think following a walking companion at your side—while Brandon shares how being privately held enables a patient-first pace of innovation. TeleHear AI adds timely support: when a clinic visit isn't possible, users can describe the problem, get smart on-device adjustments, compare results, and keep what works, with changes reported back to their clinician. It's an example of “friendly AI” that saves time, lifts outcomes, and preserves the provider-patient bond.We also talk access and ethics. From fall detection offered across tiers to StarkeyCares and Hear Now, the team argues that safety and dignity shouldn't be premium features. Data logging grows from hours-worn into environment-aware insights that inform personalization, reduce returns, and drive satisfaction. And for clinicians worried about being replaced, the takeaway is clear: the irreplaceable value is knowing the person behind the audiogram, translating powerful tech into the two or three features that matter most to that life.If you care about hearing technology, clinical excellence, health equity, and where AI is truly useful, this conversation maps the road ahead—fast, human, and focused on outcomes. Subscribe, share with a colleague who still thinks “adaptive directionality” is enough, and leave a quick review telling us which Omega AI feature you want to try first. Connect with the Hearing Matters Podcast TeamEmail: hearingmatterspodcast@gmail.com Instagram: @hearing_matters_podcast Twitter: @hearing_mattasFacebook: Hearing Matters Podcast

Peloton unveils brand-new equipment and an AI-powered user interface.Details on the upcoming Peloton Chicago Shakeout run.Exploring the hidden gems and extra programming on Peloton's YouTube channel.Camila Ramon sits down for a special interview with the legendary Gloria Estefan.Alex Rodriguez interviews Peloton's own Robin Arzon for Bloomberg.We share the exciting news from Selena Samuela's gender reveal.Hannah Corbin announces her upcoming book tour.TCO Top Five: We count down the top classes of the week as voted by you.This Week at Peloton: Your guide to all the new classes and events.A deep dive into Andy Speers' strength classes and what makes them a must-take for your fitness journey.Ash Pryor and Alex Karwoski launch a brand-new program for the Peloton Row.Peloton drops a challenging 75-minute Hyrox-style boot camp.Jeffrey McEachern leads a special run for World AIDS Day.We celebrate Peloton instructor birthdays, starting with Nico Sarani on October 3rd.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode we spoke with Mike Rohrmoser, VP of Product Management for OEM Solutions at Digi, a global provider of mission-critical IoT connectivity products and services. We explored how manufacturers are addressing labor shortages with IoT and automation, the trade-offs between retrofitting existing factories and building new ones, the evolving sensor and connectivity landscape, and practical steps to scale IoT pilots into production. Key insights: • Retrofitting existing plants is often the smarter move. Brownfield upgrades can cost 40–60% less than new builds and achieve faster returns when paired with business-focused use cases and retrofit connectivity. • Sensors and networks must be judged as a whole system. Industrial buyers weigh accuracy, deployment simplicity, and lifetime cost over unit price, with wireless IO-Link and LTE Cat 1 gaining traction and 5G RedCap on the horizon. • Edge AI is real, but focused. Today it is most effective in computer vision for quality inspection and counting, while new designs anticipate broader workloads as adoption matures. • GenAI augments people, not machines. Its strengths are in analysis, documentation, and device management, while safety-critical real-time control remains firmly in the domain of conventional automation. • Scaling pilots requires proving value early. Many initiatives stall when they start with technology instead of problems; success depends on production-ready components, operator trust, and leadership alignment. IoT ONE database: https://www.iotone.com/case-studies The Industrial IoT Spotlight podcast is produced by Asia Growth Partners (AGP): https://asiagrowthpartners.com/

In this DCF Trends-Nomads at the Summit Podcast episode, the editors of Data Center Frontier and the hosts of Nomad Futurist sit down with Doug Recker, a telecommunications veteran and edge data center pioneer with more than 30 years of industry leadership. Today, Recker leads Duos Edge AI, driving initiatives to bring multi-access edge data centers (EDCs) to underserved communities, including schools and health facilities across the U.S. From founding Edge Presence (acquired by Ubiquity in 2023) and Colo5 Data Centers (later acquired by Cologix in 2014), to deploying more than 40 TM2500 units worldwide, Recker has consistently been at the forefront of building scalable, resilient infrastructure. His career is marked by multiple honors, including Northeast Florida's Ultimate CEO Award and recognition among Inc. 500's fastest-growing companies. In this conversation, Recker shares insights on the evolution of edge computing, lessons learned from decades in telecom and data centers, and how his time in the U.S. Marine Corps shaped his leadership philosophy. Tune in for a wide-ranging discussion on innovation, resilience, and the future of edge AI.

Join me for episode 444 of the Mobile Tech Podcast with guests Adrian Mikolajczak (Infineon) and Carolina Milanesi (Creative Strategies) -- brought to you by Infineon. Today's episode comes in two parts. First, we explore edge AI, robotics, and quantum computing with Infineon. Second (21:15), we recap the Apple event and share our first impressions of the iPhone 17/17 Pro/17 Pro Max, iPhone Air, AirPods Pro 3, and Apple Watch SE 3/11/Ultra 3. Finally, we discuss Samsung, Lenovo, and TCL's latest devices, and cover news from Nothing, Xiaomi, Huawei, and Vivo... Phew!Episode Links- Support the podcast on Patreon: https://www.patreon.com/tnkgrl- Donate: https://tnkgrl.com/tnkgrl/- Infineon: https://www.infineon.com/event/oktobertech (sponsor)- Silicon Valley Innovation Center: https://svictechzone.vfairs.com/- Edge AI Video: https://www.youtube.com/watch?v=4Xn_iaqs6lM- Adrian Mikolajczak: https://www.linkedin.com/in/adrianmikolajczak/- Carolina Milanesi: https://www.threads.com/@caro_milanesi- Carolina's recap of the Apple event: https://creativestrategies.com/research/slim-smart-integrated-the-real-story-of-apples-september-event/- New iPhones, Apple Watches, and AirPods Pro hands-on: https://www.youtube.com/watch?v=idEAABFzpfg- Nothing ear(3) coming Sept 18: https://www.gsmarena.com/this_is_what_the_nothing_ear_3_looks_like-news-69458.php- Xiaomi 15T series coming Sept 24: https://www.gsmarena.com/xiaomi_15t_and_15t_pro_launch_date_is_official-news-69401.php- Samsung Galaxy Tab S11 series: https://www.gsmarena.com/samsung_galaxy_tab_s11_and_galaxy_tab_s11_ultra_debut-news-69338.php- Samsung Galaxy S25 FE: https://www.gsmarena.com/samsung_galaxy_s25_fe_announced_with_exynos_2400_soc_triple_rear_cameras-news-69335.php- Lenovo Legion Go 2: https://www.gsmarena.com/lenovo_legion_go_2_announced_with_up_to_amd_ryzen_z2_processor_74whr_battery-news-69380.php- Huawei Mate XTs tri-fold: https://www.gsmarena.com/huawei_mate_xts_announced_with_kirin_9020_and_updated_40mp_ultrawide_cam-news-69347.php- Vivo X300 series design teased: https://www.gsmarena.com/vivo_x300_series_camera_bump_compared_to_iphone_17_pro-news-69428.php- TCL NxtPaper 60 Ultra: https://www.gsmarena.com/tcl_nxtpaper_60_ultra_debuts_with_72_nxtpaper_40_display_stylus_support_and_a_50mp_telephoto_-news-69343.phpAffiliate Links (If you use these links to buy something, we might earn a commission)- Samsung Galaxy Tab S11 Ultra: https://amzn.to/4mcfWw9- Samsung Galaxy Tab S11: https://amzn.to/42t1iJV- Samsung Galaxy S25 FE: https://amzn.to/47JVv6q- Lenovo Legion Go S: https://amzn.to/46yiWyl- TCL NxtPaper 60 XE: https://amzn.to/4nromkd

Meta is going straight superintelligent? OpenAI and Google are teaming up? And Microsoft might kill tutorials? The big AI dogs are at it again, making some head-turning moves in the AI space. Don't get left behind. Join us on Mondays for our AI News That Matters segment. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Have a question? Join the convo here.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:OpenAI & Google Cloud PartnershipMeta's $14B AI Superintelligence BetDisney & Universal vs. Midjourney LawsuitApple's AI Translation Across DevicesOpenAI Expands GPT Projects & FeaturesMicrosoft Updates Copilot Vision ToolsAmazon's AI Video Tool for SellersMeta AI App Privacy ControversyTimestamps:00:00 AI Insights: This Week's Headlines04:28 ChatGPT Project Features Update08:42 AI Wednesdays: Updates and Insights11:57 Meta's $14B Superintelligence Investment15:24 Meta's Acquisition of Scale AI17:31 OpenAI Partners with Google Cloud22:41 Apple Translation Integration Delayed26:00 Third-Party AI to Improve Siri30:43 Microsoft Copilot's Quiet Feature Updates33:40 Amazon Enhances AI for Ads37:34 Copyright Lawsuit: Midjourney vs. Studios41:43 OpenAI O3 Pro: Accuracy Over Speed45:54 AI News & Events Week PreviewKeywords:OpenAI, Google Cloud, Meta, superintelligence, Scale AI, $14 billion investment, artificial superintelligence, Midjourney, Disney lawsuit, Universal lawsuit, AI copyright issues, Microsoft Copilot Vision, Copilot AI updates, real-time AI assistance, AI-powered video generator, Amazon video tools, chat GPT projects, GPTs, AI compute, Tensor Processing Units, regulatory scrutiny, AI market competition, OpenAI revenue, O3 Pro model, ChatGPT Pro, AI reasoning models, voice mode, Apple WWDC, AI translation, Edge AI, cloud infrastructure, Meta AI assistant, Apple AI struggles, Siri upgrade, AI legal battle, OpenAI and Google partnership, Meta's AI investment, $10 billion annual revenue, personal data privacy, Meta privacy concerns, AI model updates.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Try Google Veo 3 today! Sign up at gemini.google to get started. Try Google Veo 3 today! Sign up at gemini.google to get started.

Google just dropped like 3 years of AI updates on us in 3 hours.