『Forging The Future with Chris Howard』のカバーアート

Forging The Future with Chris Howard

Forging The Future with Chris Howard

著者： Chris Howard
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Join Chris Howard, Founder and CEO of Softeq, as he interviews knowledgeable leaders in the innovation spectrum, including CEOs, CTOs, R&D professionals, and start-up founders. Real conversations, technology, and processes of bringing new ideas to market.© 2022 All rights reserved. "Forging the Future" podcast, content, title, and logo owned by Softeq. Unauthorized use prohibited. Contact: ftf@speakerboxmedia.com. Respect our creativity. 経済学
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  • How Microchip's Brian McCarson Is Building the Data Center Infrastructure Powering AGI

    How Microchip's Brian McCarson Is Building the Data Center Infrastructure Powering AGI
    2026/06/04
    In this episode, Brian McCarson (Microchip Technology) breaks down AI's four evolutionary eras: machine learning, training, inference, and AGI. In today’s conversation, Brian makes a bold case that most organizations are building infrastructure for the wrong phase. Based on nearly 25 years at Intel and now driving innovation at Microchip Technology, he explains why the real bottleneck in AI today is not compute power but the high-speed switches, retimers, and storage controllers that connect GPUs, CPUs, and memory at scale, what he calls the "nervous system" of AI infrastructure. He warns that enterprises over-investing in cloud-based training architectures are heading toward a costly redesign within 18 months, and that the winning strategy is to plan now for inference-first, agent-friendly systems that push compute as close to the endpoint as possible. 🎧 Episode Highlights [01:37]: Brian's journey from semiconductor automation to modern AI [13:41]: Inheriting and rebuilding Microchip's data center business [20:10]: How Microchip deployed AI agents to scale operations without expanding headcount [34:43]: Why Microchip positions itself as the nervous system of AI infrastructure [43:07]: The energy and supply chain constraints reshaping the future of data centers 🔑 Key Takeaways: ● Most organizations are investing in AI infrastructure for the wrong phase. The shift from the training era to the inference era demands a fundamental rethink of architecture, and companies building cloud-dependent, training-heavy systems today are setting themselves up for a costly and disruptive redesign within 18 months. Planning now for inference-first, agent-friendly systems that push compute closer to the endpoint is the strategic move that separates long-term winners from short-term optimizers. ● The real bottleneck in AI is not compute power but the infrastructure connecting it. As Nvidia accelerates its hardware refresh cycle to an annual cadence, the switches, retimers, and storage controllers that enable GPUs, CPUs, and memory to communicate at scale have become the critical constraint. Investing in high-performance interconnect technology is no longer an afterthought but a core requirement for getting full value out of expensive compute investments. ● AI delivers its greatest business value when it augments people rather than replaces them. Microchip's turnaround demonstrated that deploying AI agents as PhD-level assistants to handle menial, repetitive tasks, while keeping humans focused on high-value strategic work, drives better outcomes, stronger team morale, and sustainable growth. The companies using AI purely to cut headcount and improve a balance sheet are optimizing for the short term at the expense of long-term organizational health. 👤 About The Host: Brian McCarson Brian McCarson is Corporate Vice President at Microchip Technology, where he leads the company's data center solutions business with a focus on the high-speed interconnect infrastructure powering next-generation AI systems. He brings nearly 25 years of experience at Intel Corporation, where he built deep expertise across semiconductor innovation, factory automation, and advanced technology development. A longtime advocate for using AI to drive real business outcomes, Brian is recognized for his ability to turn around complex technology organizations and translate emerging AI trends into actionable enterprise strategy. Stay Connected: ● https://www.softeq.com ● https://www.linkedin.com/in/techris ● https://www.linkedin.com/in/brianmccarson ● https://www.microchip.com Produced by Speakerbox Media.
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    59 分
  • AI for Good: How NVIDIA’s Thorsten Stremlau Is Transforming Life for People with Disabilities

    AI for Good: How NVIDIA’s Thorsten Stremlau Is Transforming Life for People with Disabilities
    2026/04/30
    NVIDIA systems architect Thorsten Stremlau sees “AI for good” as a way to restore core human abilities like communication, independence, and participation, especially for people with disabilities. Inspired by his work with Stephen Hawking and Peter Scott- Morgan, he’s helped build affordable, AI-powered tools from eye-gaze systems to personalized language models that run on everyday devices like smartphones. He contrasts these non-invasive solutions with brain-computer interfaces from companies like Neuralink, highlighting that while implants may unlock richer interaction in the future, today’s priority is scalable tech that already improves lives. He also explores how AI can support areas beyond ALS, including heart disease, PTSD, and mobility. At its core, his work is about using AI to create a more inclusive world where disability doesn’t mean disconnection. 🎧Episode Highlights [01:24]: Thorsten’s early work with nonverbal disabled youth [07:41]: AI restoring communication, autonomy, participation [18:09]: Working with Stephen Hawking and Peter Scott-Morgan [29:55]: Low-cost eye-gaze and circular-keyboard communication [43:12]: Beyond ALS: speech, PTSD, AI prosthetics 🔑 Key Takeaways: ● AI for good is ultimately about restoring human agency, not just boosting efficiency. By focusing on communication, autonomy, and participation, AI systems can give people with disabilities the ability to express themselves, make choices, and engage with the world on their own terms, rather than being defined by their limitations. ● The most impactful assistive technologies are built on mainstream, affordable hardware instead of specialized, high-cost rigs. Eye-gaze interfaces, circular keyboards, personalized language models, and speech-decoding systems that run on laptops and smartphones dramatically expand access, making advanced assistive tech viable not just for a few patients in wealthy systems, but for millions of people worldwide. ● Non-invasive AI solutions are a powerful bridge to the future of human–computer interaction, even as brain–computer interfaces rapidly advance. By combining clever sensing (eyes, face, voice, heart rate, touch), behavior modeling, and personalized AI, we can already enable richer communication, calmer nervous systems, and more natural movement, laying the groundwork for a world where disability no longer means disconnection from work, creativity, or community. 👤 Guest Spotlight: Thorsten Stremlau Thorsten Stremlau is a Principal Systems Architect at NVIDIA and a technology leader focused on building next-generation computing platforms and customer-centered innovation. Previously with Lenovo and IBM, he holds 30+ patents and is widely recognized as a thought leader in platform security and advanced systems architecture, known for turning complex technical challenges into trusted, market-ready solutions. Stay Connected: ● https://www.softeq.com ● https://www.linkedin.com/in/techris ● https://www.linkedin.com/in/thorsten-stremlau-247930 ● https://www.nvidia.com Stay inspired and ahead of the curve by subscribing to Forging the Future. Share your thoughts on this episode with the hashtag #ForgingTheFuture or tag us online!
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    52 分
  • The “SaaS-pocalypse” Is Here: Equipt.ai’s Amanpreet Kaur on How AI Is Rebuilding Software

    The “SaaS-pocalypse” Is Here: Equipt.ai’s Amanpreet Kaur on How AI Is Rebuilding Software
    2026/04/09
    Episode Summary: Amanpreet Kaur, Chief AI and Technology Officer of Equipt.ai, breaks down the so-called “SaaS-pocalypse” and argues that SaaS isn’t dying, it’s evolving into smarter, AI-embedded systems of execution. Amanpreet explains how traditional SaaS created fragmentation and operational friction, and how Equipt.ai is rebuilding the stack by unifying workflows, data, and decision-making into a single AI-driven execution layer. Drawing from her experience in asset-heavy industries like energy, Aman shares how their platform replaces multiple disconnected tools while enabling real-time, guided operations from quote to cash. She also reflects on the early startup journey, from landing their first enterprise customer to navigating investor skepticism and refining their positioning. A key shift is undoubtedly taking place: the future belongs to agentic SaaS platforms that reduce human intervention and turn software into an active driver of business outcomes. 🎧 Episode Highlights [02:09]: SaaS solved infrastructure but created fragmentation [04:59]: “Dumb SaaS is dying:” AI-powered execution rises [06:17]: Replacing 10-20 tools with one platform [10:44]: AI as “steroids” for SaaS, not replacement [14:38]: First enterprise client before having a product [23:13]: Embedding AI across the full workflow 🔑 Key Takeaways: The “SaaS-pocalypse” isn’t about SaaS disappearing, it’s about a shift from systems of record to systems of execution. Traditional SaaS created fragmented workflows and heavy reliance on human coordination, while AI-enabled platforms are now unifying data and driving real-time decisions directly within operations. AI’s real value is not replacing software, but embedding intelligence into every layer of it. From automation and optimization to predictive insights, the winning approach is combining machine learning, simple automation, and context-aware AI to reduce manual work and enable more deterministic, reliable outcomes. Startups that succeed in this shift will focus on solving real operational problems, not just adding AI for hype. Equipt.ai’s journey shows that deep industry understanding, clear pain points, and delivering immediate value to customers matter more than technology trends, especially when building trust and scaling from early enterprise clients. 👤 Guest Spotlight:Amanpreet KaurAmanpreet Kaur is the co-founder as well as the Chief AI and Technology Officer of Equipt.ai, where she builds AI-powered operational platforms for asset-intensive industries. With a background in energy and industrial technology, she previously led the development and commercialization of digital solutions, including enterprise-scale platforms and digital twin systems. Kaur brings deep domain expertise and a product-first mindset to redefining how businesses move from fragmented SaaS tools to AI-driven systems of execution. Stay Connected: https://www.softeq.com/ https://www.linkedin.com/in/techris/ https://www.linkedin.com/in/amanpreet-hon-doc/ https://www.equipt.ai/ Stay inspired and ahead of the curve by subscribing to Forging the Future. Share your thoughts on this episode with the hashtag #ForgingTheFuture or tag us online!
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    33 分
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