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  <description><![CDATA[<p>Bringing technology into focus. We talk to leaders with technology of interest to engineers.</p>]]></description>
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    <itunes:title>Brittany Ng, Siemens Maritime Division, On Getting the US Back in the Game</itunes:title>
    <title>Brittany Ng, Siemens Maritime Division, On Getting the US Back in the Game</title>
    <itunes:summary><![CDATA[We sit down with Brittany Mays Ing, VP of Siemens Maritime, right after her US Senate testimony on “Less Hype, More Help” about AI and unpack what industrial AI looks like when you have to build real ships on real timelines. We connect digital twins, copilots, and the digital thread to the biggest constraint shipbuilders face today: talent, throughput, and first-time quality.  • Why Brittany gets tapped to speak to Congress about industrial AI across manufacturing  • How Siemens Mar...]]></itunes:summary>
    <description><![CDATA[<p>We sit down with Brittany Mays Ing, VP of Siemens Maritime, right after her US Senate testimony on “Less Hype, More Help” about AI and unpack what industrial AI looks like when you have to build real ships on real timelines. We connect digital twins, copilots, and the digital thread to the biggest constraint shipbuilders face today: talent, throughput, and first-time quality. <br/>• Why Brittany gets tapped to speak to Congress about industrial AI across manufacturing <br/>• How Siemens Maritime uses the Siemens Xcelerator portfolio plus Altair tools for shipbuilding <br/>• Why ship design tools look different from typical CAD and simulation workflows <br/>• What a record scale ship digital twin proves about complexity and visualization <br/>• Why AI in shipbuilding reduces repetitive work instead of eliminating jobs <br/>• How AI helps first-time quality, reduces rework and cuts burnout in shipyards <br/>• What “digital thread” means for suppliers, OEMs, and national defense readiness <br/>• How commercial, military, and unmanned vessel programs are reshaping the market <br/><br/><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>We sit down with Brittany Mays Ing, VP of Siemens Maritime, right after her US Senate testimony on “Less Hype, More Help” about AI and unpack what industrial AI looks like when you have to build real ships on real timelines. We connect digital twins, copilots, and the digital thread to the biggest constraint shipbuilders face today: talent, throughput, and first-time quality. <br/>• Why Brittany gets tapped to speak to Congress about industrial AI across manufacturing <br/>• How Siemens Maritime uses the Siemens Xcelerator portfolio plus Altair tools for shipbuilding <br/>• Why ship design tools look different from typical CAD and simulation workflows <br/>• What a record scale ship digital twin proves about complexity and visualization <br/>• Why AI in shipbuilding reduces repetitive work instead of eliminating jobs <br/>• How AI helps first-time quality, reduces rework and cuts burnout in shipyards <br/>• What “digital thread” means for suppliers, OEMs, and national defense readiness <br/>• How commercial, military, and unmanned vessel programs are reshaping the market <br/><br/><br/><br/></p>]]></content:encoded>
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    <pubDate>Wed, 13 May 2026 17:00:00 -0700</pubDate>
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  <psc:chapter start="0:00" title="Welcome And Guest Introduction" />
  <psc:chapter start="3:10" title="Why The Senate Called On Brittany" />
  <psc:chapter start="5:00" title="Siemens Maritime Software Stack Explained" />
  <psc:chapter start="7:05" title="Record Breaking Ship Digital Twin" />
  <psc:chapter start="9:05" title="AI And The Shipbuilding Talent Gap" />
  <psc:chapter start="13:00" title="Copilots First Time Quality Less Rework" />
  <psc:chapter start="16:20" title="Digital Thread For National Defense" />
  <psc:chapter start="18:25" title="Commercial Military And New Ship Types" />
  <psc:chapter start="19:55" title="Consulting To Siemens And Service Mindset" />
  <psc:chapter start="23:55" title="Women In Manufacturing And Closing" />
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    <itunes:duration>1584</itunes:duration>
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    <itunes:title>Seeing Around Corners? We Can Do That, says Tristan Swedish of Ubicept</itunes:title>
    <title>Seeing Around Corners? We Can Do That, says Tristan Swedish of Ubicept</title>
    <itunes:summary><![CDATA[We dig into SPAD photon-counting sensors and why converting photons into bits can change low-light imaging, motion blur, and dynamic range for real perception systems. We also connect the physics of uncertainty to modern AI so vision models stop guessing when the data is ambiguous.  • How SPAD arrays work and why they differ from CMOS image sensors  • Why SPAD data volume can reach terabytes and how near-sensor processing makes it usable  • Photon noise as a physics limit and h...]]></itunes:summary>
    <description><![CDATA[<p>We dig into SPAD photon-counting sensors and why converting photons into bits can change low-light imaging, motion blur, and dynamic range for real perception systems. We also connect the physics of uncertainty to modern AI so vision models stop guessing when the data is ambiguous. <br/>• How SPAD arrays work and why they differ from CMOS image sensors <br/>• Why SPAD data volume can reach terabytes and how near-sensor processing makes it usable <br/>• Photon noise as a physics limit and how integrating over time improves confidence <br/>• Motion compensation that enables longer effective exposure without motion blur <br/>• Why night color is often a noise problem, not a missing-color problem <br/>• How uncertainty-aware imaging can reduce AI hallucinations in computer vision <br/>• Automotive and ADAS use cases plus reflections and extreme dynamic range <br/>• What “seeing around corners” means using time-tagged light echoes and real constraints <br/><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>We dig into SPAD photon-counting sensors and why converting photons into bits can change low-light imaging, motion blur, and dynamic range for real perception systems. We also connect the physics of uncertainty to modern AI so vision models stop guessing when the data is ambiguous. <br/>• How SPAD arrays work and why they differ from CMOS image sensors <br/>• Why SPAD data volume can reach terabytes and how near-sensor processing makes it usable <br/>• Photon noise as a physics limit and how integrating over time improves confidence <br/>• Motion compensation that enables longer effective exposure without motion blur <br/>• Why night color is often a noise problem, not a missing-color problem <br/>• How uncertainty-aware imaging can reduce AI hallucinations in computer vision <br/>• Automotive and ADAS use cases plus reflections and extreme dynamic range <br/>• What “seeing around corners” means using time-tagged light echoes and real constraints <br/><br/><br/></p>]]></content:encoded>
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    <pubDate>Mon, 11 May 2026 13:00:00 -0700</pubDate>
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  <psc:chapter start="0:00" title="Welcome And Seeing Around Corners" />
  <psc:chapter start="3:06" title="What SPAD Sensors Actually Do" />
  <psc:chapter start="6:20" title="From Single Pixels To SPAD Arrays" />
  <psc:chapter start="10:40" title="Taming Terabytes With On-Sensor Processing" />
  <psc:chapter start="13:40" title="Photon Noise And Confidence Over Time" />
  <psc:chapter start="18:00" title="Motion Blur Fix And Night Color" />
  <psc:chapter start="23:00" title="AI Hallucinations And Uncertainty-Aware Vision" />
  <psc:chapter start="26:50" title="Dynamic Range Plus Real See-Around-Corners Uses" />
  <psc:chapter start="29:20" title="Costs, Deployment Path, And Closing" />
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    <itunes:duration>1788</itunes:duration>
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    <itunes:title>Ron Close: Marketing in the Age of AI</itunes:title>
    <title>Ron Close: Marketing in the Age of AI</title>
    <itunes:summary><![CDATA[Research by Ron reveals how AI (ChatGPT, Gemini, etc.) ignores conventional sources such as business to business publications and industry analysts, instead citing vendor pages, Reddit, resellers, and even mystery sites. Guidelines proposed on how AEO (Answer Engine Optimization) might work in practice.  Comparison reviews may be the clearest path to being sourced by answer enginesRon’s AEO research goalsA prompt-based testing method across ChatGPT and Gemini Missing citations and w...]]></itunes:summary>
    <description><![CDATA[<p>Research by Ron reveals how AI (ChatGPT, Gemini, etc.) ignores conventional sources such as business to business publications and industry analysts, instead citing vendor pages, Reddit, resellers, and even mystery sites. Guidelines proposed on how AEO (Answer Engine Optimization) might work in practice. </p><ul><li>Comparison reviews may be the clearest path to being sourced by answer engines</li><li>Ron’s AEO research goals</li><li>A prompt-based testing method across ChatGPT and Gemini </li><li>Missing citations and why vendor or reseller sources get treated as authoritative </li><li>The CADSoft USA mystery and how high-volume comparison pages get rewarded </li><li>Why advertising incentives weaken trade media independence and credibility </li><li>Zero click answers from search engines and how AI previews reduce website traffic </li><li>Comparison reviews as AEO 101 and the business risk of publishing them </li><li>The adjacent CAD ecosystem and how LLMs pull in simulation, PDM, and visualization tools </li><li>The opportunity for a Consumer Reports-style authority for CAD and engineering software </li></ul><p><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>Research by Ron reveals how AI (ChatGPT, Gemini, etc.) ignores conventional sources such as business to business publications and industry analysts, instead citing vendor pages, Reddit, resellers, and even mystery sites. Guidelines proposed on how AEO (Answer Engine Optimization) might work in practice. </p><ul><li>Comparison reviews may be the clearest path to being sourced by answer engines</li><li>Ron’s AEO research goals</li><li>A prompt-based testing method across ChatGPT and Gemini </li><li>Missing citations and why vendor or reseller sources get treated as authoritative </li><li>The CADSoft USA mystery and how high-volume comparison pages get rewarded </li><li>Why advertising incentives weaken trade media independence and credibility </li><li>Zero click answers from search engines and how AI previews reduce website traffic </li><li>Comparison reviews as AEO 101 and the business risk of publishing them </li><li>The adjacent CAD ecosystem and how LLMs pull in simulation, PDM, and visualization tools </li><li>The opportunity for a Consumer Reports-style authority for CAD and engineering software </li></ul><p><br/><br/></p>]]></content:encoded>
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    <pubDate>Wed, 06 May 2026 16:00:00 -0700</pubDate>
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  <psc:chapter start="0:00" title="Welcome And Quick Catch Up" />
  <psc:chapter start="2:40" title="Hope And Politics In Budapest" />
  <psc:chapter start="9:32" title="AEO Guide And The Testing Method" />
  <psc:chapter start="14:04" title="Missing Citations And Biased Sources" />
  <psc:chapter start="19:28" title="Advertising Corrupts Trust In Media" />
  <psc:chapter start="24:56" title="Comparative Reviews As AEO Fuel" />
  <psc:chapter start="29:43" title="Adjacent Tools And Startup White Space" />
  <psc:chapter start="36:08" title="How To Influence Models And Wrap" />
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    <itunes:duration>2235</itunes:duration>
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    <itunes:title>Ivan Tregear, KAIKAKU and Robots In The Kitchen</itunes:title>
    <title>Ivan Tregear, KAIKAKU and Robots In The Kitchen</title>
    <itunes:summary><![CDATA[We explore how purpose-built food assembly robots, computer vision, and better data can push restaurants beyond thin margins and burnout. We share what we learned by running a living-lab restaurant, why we paused it, and how we’re deploying the tech inside partner stores.  • Origins in delivery work and engineering • Why restaurants lag in automation • Building a living-lab restaurant for rapid iteration • Pausing the pilot to deploy with partners • Using robots for repetitive prep and assemb...]]></itunes:summary>
    <description><![CDATA[<p>We explore how purpose-built food assembly robots, computer vision, and better data can push restaurants beyond thin margins and burnout. We share what we learned by running a living-lab restaurant, why we paused it, and how we’re deploying the tech inside partner stores.<br/><br/>• Origins in delivery work and engineering<br/>• Why restaurants lag in automation<br/>• Building a living-lab restaurant for rapid iteration<br/>• Pausing the pilot to deploy with partners<br/>• Using robots for repetitive prep and assembly<br/>• Keeping humans focused on hospitality<br/>• Capturing sensor and vision data at the line<br/>• Pitfalls of bad “labor optimization” AI<br/>• Onshape for fast design, version control and collaboration<br/>• Rejecting humanoids for task-specific mechanisms<br/>• Expansion paths into catering and hospitality<br/><br/><br/><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>We explore how purpose-built food assembly robots, computer vision, and better data can push restaurants beyond thin margins and burnout. We share what we learned by running a living-lab restaurant, why we paused it, and how we’re deploying the tech inside partner stores.<br/><br/>• Origins in delivery work and engineering<br/>• Why restaurants lag in automation<br/>• Building a living-lab restaurant for rapid iteration<br/>• Pausing the pilot to deploy with partners<br/>• Using robots for repetitive prep and assembly<br/>• Keeping humans focused on hospitality<br/>• Capturing sensor and vision data at the line<br/>• Pitfalls of bad “labor optimization” AI<br/>• Onshape for fast design, version control and collaboration<br/>• Rejecting humanoids for task-specific mechanisms<br/>• Expansion paths into catering and hospitality<br/><br/><br/><br/><br/></p>]]></content:encoded>
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    <pubDate>Mon, 19 Jan 2026 13:00:00 -0800</pubDate>
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  <psc:chapter start="0:00" title="Hosts Meet And Warm-Up" />
  <psc:chapter start="1:25" title="Youngest Chartered Engineer Backstory" />
  <psc:chapter start="2:42" title="Why Restaurants Need Robotics" />
  <psc:chapter start="6:34" title="Building A Living Lab Restaurant" />
  <psc:chapter start="10:54" title="Pausing The Pilot And Next Steps" />
  <psc:chapter start="12:07" title="Goal: Healthier Margins And Happier Staff" />
  <psc:chapter start="14:35" title="Onshape For Fast Hardware Iteration" />
  <psc:chapter start="20:01" title="SaaS, Version Control, And Macs" />
  <psc:chapter start="23:18" title="AI In Engineering And Retail Ops" />
  <psc:chapter start="27:05" title="Data Quality Before AI Decisions" />
  <psc:chapter start="28:38" title="Note: Adjusted order to fit duration" />
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    <itunes:duration>1741</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>2</itunes:episode>
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    <itunes:title>Richard Chleboski, 24M and a Thousand-Mile Battery that Is Safer By Design</itunes:title>
    <title>Richard Chleboski, 24M and a Thousand-Mile Battery that Is Safer By Design</title>
    <itunes:summary><![CDATA[We unpack how 24M combines electrode-to-pack design, a fast, high-conductivity electrolyte, and a sensing separator to aim for thousand-mile range and safer batteries. The talk spans dendrites and thermal runaway, drone-ready shapes, long-duration storage, and real-world paths to scale and recycle.  • ETOP packaging for higher energy density and custom shapes • Impervia separator that suppresses dendrites and senses faults • Eternalite electrolyte enabling five-minute charge and late-cycle po...]]></itunes:summary>
    <description><![CDATA[<p>We unpack how 24M combines electrode-to-pack design, a fast, high-conductivity electrolyte, and a sensing separator to aim for thousand-mile range and safer batteries. The talk spans dendrites and thermal runaway, drone-ready shapes, long-duration storage, and real-world paths to scale and recycle.<br/><br/>• ETOP packaging for higher energy density and custom shapes<br/>• Impervia separator that suppresses dendrites and senses faults<br/>• Eternalite electrolyte enabling five-minute charge and late-cycle power<br/>• Lithium metal safety strategy and thermal runaway prevention<br/>• Drone and aviation use cases with conformable packs<br/>• EV vs ESS market dynamics and policy uncertainty<br/>• Manufacturing strategy and onshoring with lower risk<br/>• Long-duration storage for the duck curve<br/>• Binder-free electrodes and closed-loop recycling of LFP and graphite<br/>• Tradeoffs, transition costs, and incremental adoption paths<br/><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>We unpack how 24M combines electrode-to-pack design, a fast, high-conductivity electrolyte, and a sensing separator to aim for thousand-mile range and safer batteries. The talk spans dendrites and thermal runaway, drone-ready shapes, long-duration storage, and real-world paths to scale and recycle.<br/><br/>• ETOP packaging for higher energy density and custom shapes<br/>• Impervia separator that suppresses dendrites and senses faults<br/>• Eternalite electrolyte enabling five-minute charge and late-cycle power<br/>• Lithium metal safety strategy and thermal runaway prevention<br/>• Drone and aviation use cases with conformable packs<br/>• EV vs ESS market dynamics and policy uncertainty<br/>• Manufacturing strategy and onshoring with lower risk<br/>• Long-duration storage for the duck curve<br/>• Binder-free electrodes and closed-loop recycling of LFP and graphite<br/>• Tradeoffs, transition costs, and incremental adoption paths<br/><br/><br/></p>]]></content:encoded>
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    <pubDate>Wed, 31 Dec 2025 16:00:00 -0800</pubDate>
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  <psc:chapter start="0:00" title="Meet 24M And The Big Promise" />
  <psc:chapter start="1:16" title="From Better Electrodes To ETOP" />
  <psc:chapter start="2:32" title="The Dendrite Problem Explained" />
  <psc:chapter start="5:18" title="Impervia Separator: Suppress And Sense" />
  <psc:chapter start="8:35" title="Lithium Metal Safety And Fast Charge" />
  <psc:chapter start="9:58" title="Why Not Just Add More Cells" />
  <psc:chapter start="11:16" title="Aviation And Drones: Shape And Power" />
  <psc:chapter start="14:32" title="Eternalite And End‑Of‑Cycle Power" />
  <psc:chapter start="17:36" title="Safety As Threshold And Continuum" />
  <psc:chapter start="20:12" title="Rethinking Manufacturing And ETOP" />
  <psc:chapter start="24:37" title="Market Caution, Policy, And Reshoring" />
  <psc:chapter start="28:16" title="The Duck Curve And Long Duration Storage" />
  <psc:chapter start="31:10" title="China’s Scale vs. Tech Differentiation" />
  <psc:chapter start="34:00" title="Packaging Gains And System Design" />
  <psc:chapter start="36:09" title="Recycling 90% With Live Forever" />
</psc:chapters>
    <itunes:duration>2282</itunes:duration>
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    <itunes:episode>1</itunes:episode>
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  <item>
    <itunes:title>Dr Mohammad Ashiqur Rahman - AI at FIU</itunes:title>
    <title>Dr Mohammad Ashiqur Rahman - AI at FIU</title>
    <itunes:summary><![CDATA[We trace FIU’s early bet on AI, the rise of AI-ready engineering education, and why security research must outpace attackers. From LLM jailbreaks to drone resilience, we share how to validate tools, keep fundamentals strong, and deploy AI safely in the real world.  • FIU’s AI strategy across engineering disciplines • Faculty journey from cybersecurity to AI-driven defense • Research strength, funding, and emerging tech focus • AI Summit takeaways from flood modeling to controls • Quantum thre...]]></itunes:summary>
    <description><![CDATA[<p>We trace FIU’s early bet on AI, the rise of AI-ready engineering education, and why security research must outpace attackers. From LLM jailbreaks to drone resilience, we share how to validate tools, keep fundamentals strong, and deploy AI safely in the real world.<br/><br/>• FIU’s AI strategy across engineering disciplines<br/>• Faculty journey from cybersecurity to AI-driven defense<br/>• Research strength, funding, and emerging tech focus<br/>• AI Summit takeaways from flood modeling to controls<br/>• Quantum threats and post-quantum cryptography<br/>• LLM jailbreak risks and malware generation<br/>• Layered defense and resilience-by-design<br/>• Teaching with AI while preserving fundamentals<br/>• AI minor structure and discipline-specific courses<br/>• Drone security via side-channel sensing and ML<br/>• Adversarial ML in cyber-physical systems<br/>• Affordability, social mobility, and ROI</p>]]></description>
    <content:encoded><![CDATA[<p>We trace FIU’s early bet on AI, the rise of AI-ready engineering education, and why security research must outpace attackers. From LLM jailbreaks to drone resilience, we share how to validate tools, keep fundamentals strong, and deploy AI safely in the real world.<br/><br/>• FIU’s AI strategy across engineering disciplines<br/>• Faculty journey from cybersecurity to AI-driven defense<br/>• Research strength, funding, and emerging tech focus<br/>• AI Summit takeaways from flood modeling to controls<br/>• Quantum threats and post-quantum cryptography<br/>• LLM jailbreak risks and malware generation<br/>• Layered defense and resilience-by-design<br/>• Teaching with AI while preserving fundamentals<br/>• AI minor structure and discipline-specific courses<br/>• Drone security via side-channel sensing and ML<br/>• Adversarial ML in cyber-physical systems<br/>• Affordability, social mobility, and ROI</p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2530725/episodes/18423919-dr-mohammad-ashiqur-rahman-ai-at-fiu.mp3" length="23166929" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/tqdxtun7cg0xfl6qwtmqs4i6c9i3?.jpg" />
    <itunes:author>Roopinder Tara</itunes:author>
    <guid isPermaLink="false">Buzzsprout-18423919</guid>
    <pubDate>Mon, 29 Dec 2025 16:00:00 -0800</pubDate>
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18423919/transcript" type="text/html" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18423919/transcript.json" type="application/json" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18423919/transcript.srt" type="application/x-subrip" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18423919/transcript.vtt" type="text/vtt" />
    <podcast:chapters url="https://www.buzzsprout.com/2530725/18423919/chapters.json" type="application/json" />
    <psc:chapters>
  <psc:chapter start="0:00" title="Welcome And FIU’s AI Ambition" />
  <psc:chapter start="1:05" title="Faculty Roots And Early AI Adoption" />
  <psc:chapter start="2:56" title="Research Strength And Emerging Tech Focus" />
  <psc:chapter start="4:20" title="Academic Journey Into Cybersecurity And AI" />
  <psc:chapter start="6:20" title="AI Summit: Use Cases From Floods To Physics" />
  <psc:chapter start="8:25" title="White Hat Security And Quantum Threats" />
  <psc:chapter start="12:05" title="Jailbreaking LLMs And Malware Risks" />
  <psc:chapter start="15:05" title="Defender’s Mindset And Layered Resilience" />
  <psc:chapter start="18:06" title="Teaching With AI Without Losing Basics" />
  <psc:chapter start="22:40" title="AI Across Disciplines And The AI Minor" />
  <psc:chapter start="26:30" title="Drone Security: Detection And Recovery" />
  <psc:chapter start="30:00" title="Adversarial ML In Cyber-Physical Systems" />
  <psc:chapter start="31:44" title="Closing And Listener Invitation]" />
</psc:chapters>
    <itunes:duration>1924</itunes:duration>
    <itunes:keywords>Please move this episode to ENGtechnica TV podcast</itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>22</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Dr Chris Parkinson and Vuzix&#39; Smart Glasses</itunes:title>
    <title>Dr Chris Parkinson and Vuzix&#39; Smart Glasses</title>
    <itunes:summary><![CDATA[We explore how smart glasses moved from bulky prototypes to practical tools, why waveguides make displays vanish into lenses, and how hybrid AI solves the offline problem. Dr. Chris Parkinson explains the tradeoffs between tethered and on-board compute, and where enterprise adoption is outpacing consumer demand.  • Waveguides turning thin lenses into bright displays • Tethered glasses as lightweight monitors vs full Android on-head • Enterprise durability, all-day shifts, and safety constrain...]]></itunes:summary>
    <description><![CDATA[<p>We explore how smart glasses moved from bulky prototypes to practical tools, why waveguides make displays vanish into lenses, and how hybrid AI solves the offline problem. Dr. Chris Parkinson explains the tradeoffs between tethered and on-board compute, and where enterprise adoption is outpacing consumer demand.<br/><br/>• Waveguides turning thin lenses into bright displays<br/>• Tethered glasses as lightweight monitors vs full Android on-head<br/>• Enterprise durability, all-day shifts, and safety constraints<br/>• Privacy lessons from Google Glass and why context matters<br/>• Vuzix strategy supplying components and building solutions<br/>• Manufacturing waveguides at scale in the US<br/>• Weight, battery, comfort limits and power tradeoffs<br/>• Monocular vs binocular displays, resolution realities<br/>• Prescription clip-ins and optical placement<br/>• AI voice interfaces, cloud vs edge, hybrid workflows<br/><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>We explore how smart glasses moved from bulky prototypes to practical tools, why waveguides make displays vanish into lenses, and how hybrid AI solves the offline problem. Dr. Chris Parkinson explains the tradeoffs between tethered and on-board compute, and where enterprise adoption is outpacing consumer demand.<br/><br/>• Waveguides turning thin lenses into bright displays<br/>• Tethered glasses as lightweight monitors vs full Android on-head<br/>• Enterprise durability, all-day shifts, and safety constraints<br/>• Privacy lessons from Google Glass and why context matters<br/>• Vuzix strategy supplying components and building solutions<br/>• Manufacturing waveguides at scale in the US<br/>• Weight, battery, comfort limits and power tradeoffs<br/>• Monocular vs binocular displays, resolution realities<br/>• Prescription clip-ins and optical placement<br/>• AI voice interfaces, cloud vs edge, hybrid workflows<br/><br/><br/></p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2530725/episodes/18376591-dr-chris-parkinson-and-vuzix-smart-glasses.mp3" length="16798608" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/m01uo52vfbqa71txx5b0cx0e4gsx?.jpg" />
    <itunes:author>Roopinder Tara</itunes:author>
    <guid isPermaLink="false">Buzzsprout-18376591</guid>
    <pubDate>Sun, 28 Dec 2025 11:00:00 -0800</pubDate>
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18376591/transcript" type="text/html" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18376591/transcript.json" type="application/json" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18376591/transcript.srt" type="application/x-subrip" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18376591/transcript.vtt" type="text/vtt" />
    <podcast:chapters url="https://www.buzzsprout.com/2530725/18376591/chapters.json" type="application/json" />
    <psc:chapters>
  <psc:chapter start="0:00" title="Welcome And Guest Background" />
  <psc:chapter start="2:10" title="What Smart Glasses Can Do Today" />
  <psc:chapter start="3:35" title="Waveguides Explained Simply" />
  <psc:chapter start="5:15" title="Tethered Displays vs Onboard Compute" />
  <psc:chapter start="7:30" title="Enterprise Needs And Rugged Design" />
  <psc:chapter start="10:35" title="Privacy, Google Glass, And Acceptance" />
  <psc:chapter start="12:05" title="Vuzix Strategy: Products And Components" />
  <psc:chapter start="13:15" title="Manufacturing Waveguides At Scale" />
  <psc:chapter start="15:05" title="Weight, Power, And All‑Day Wear" />
  <psc:chapter start="17:20" title="One Display Or Two And Resolution" />
  <psc:chapter start="19:05" title="Prescriptions And Optics Tradeoffs" />
  <psc:chapter start="21:40" title="Miniaturization And The AI Shift" />
  <psc:chapter start="23:00" title="Cloud vs Edge AI And Connectivity" />
</psc:chapters>
    <itunes:duration>1396</itunes:duration>
    <itunes:keywords>Please move this episode to ENGtechnica TV podcast</itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>7</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Inside View - Eduardo Torrealba, Lumafield and X‑Ray Vision of Parts</itunes:title>
    <title>Inside View - Eduardo Torrealba, Lumafield and X‑Ray Vision of Parts</title>
    <itunes:summary><![CDATA[Eduardo Torrealba, founder and CEO of Lumafield, on how industrial CT gives engineers a safe, fast way to see inside products and make better decisions. He discusses LumaField’s approach to trials, safety, resolution and GD&amp;T from scans.  • Value of non‑destructive 3D inspection for complex assemblies • Differences between industrial and medical CT and how shielding works • Try‑before‑you‑buy approach and what it costs • Main manufacturing use cases across batteries, plastics, and electro...]]></itunes:summary>
    <description><![CDATA[<p>Eduardo Torrealba, founder and CEO of Lumafield, on how industrial CT gives engineers a safe, fast way to see inside products and make better decisions. He discusses LumaField’s approach to trials, safety, resolution and GD&amp;T from scans.<br/><br/>• Value of non‑destructive 3D inspection for complex assemblies<br/>• Differences between industrial and medical CT and how shielding works<br/>• Try‑before‑you‑buy approach and what it costs<br/>• Main manufacturing use cases across batteries, plastics, and electronics<br/>• Limits and trade‑offs for resolution, contrast, and dense materials<br/>• CAD‑to‑scan comparison and ethical lines around reverse engineering<br/>• GD&amp;T from scans as a faster alternative to extensive CMM programs<br/>• Company footprint, manufacturing in Massachusetts and software in San Francisco<br/><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>Eduardo Torrealba, founder and CEO of Lumafield, on how industrial CT gives engineers a safe, fast way to see inside products and make better decisions. He discusses LumaField’s approach to trials, safety, resolution and GD&amp;T from scans.<br/><br/>• Value of non‑destructive 3D inspection for complex assemblies<br/>• Differences between industrial and medical CT and how shielding works<br/>• Try‑before‑you‑buy approach and what it costs<br/>• Main manufacturing use cases across batteries, plastics, and electronics<br/>• Limits and trade‑offs for resolution, contrast, and dense materials<br/>• CAD‑to‑scan comparison and ethical lines around reverse engineering<br/>• GD&amp;T from scans as a faster alternative to extensive CMM programs<br/>• Company footprint, manufacturing in Massachusetts and software in San Francisco<br/><br/><br/></p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2530725/episodes/18395962-inside-view-eduardo-torrealba-lumafield-and-x-ray-vision-of-parts.mp3" length="15152635" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/thqumztufh04rwwyl2txawsm9295?.jpg" />
    <itunes:author>Roopinder Tara</itunes:author>
    <guid isPermaLink="false">Buzzsprout-18395962</guid>
    <pubDate>Sun, 21 Dec 2025 15:00:00 -0800</pubDate>
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18395962/transcript" type="text/html" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18395962/transcript.json" type="application/json" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18395962/transcript.srt" type="application/x-subrip" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18395962/transcript.vtt" type="text/vtt" />
    <podcast:chapters url="https://www.buzzsprout.com/2530725/18395962/chapters.json" type="application/json" />
    <psc:chapters>
  <psc:chapter start="0:00" title="Meet LumaField And CT Scanning" />
  <psc:chapter start="2:25" title="Why Industrial CT And Who It Serves" />
  <psc:chapter start="3:55" title="Trust, Trials, And Buying Model" />
  <psc:chapter start="6:40" title="Safety, Shielding, And Radiation Basics" />
  <psc:chapter start="9:40" title="Use Cases Beyond Prototyping" />
  <psc:chapter start="12:55" title="Battery Insights And The Battery Report" />
  <psc:chapter start="16:50" title="Ethics, Reverse Engineering, And IP" />
  <psc:chapter start="20:30" title="Resolution, Contrast, And Visualization" />
</psc:chapters>
    <itunes:duration>1260</itunes:duration>
    <itunes:keywords>Please move this episode to ENGtechnica TV podcast</itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>12</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Fraser Patterson of Skillit. A Data-First Job Platform Aims to Solves Construction’s Labor Shortage</itunes:title>
    <title>Fraser Patterson of Skillit. A Data-First Job Platform Aims to Solves Construction’s Labor Shortage</title>
    <itunes:summary><![CDATA[We talk to Fraser Patterson, CEO and founder of Skillit, about how digitizing skilled trade workers would affect hiring speed and quality, why construction jobs are resistant to AI displacement, and what new data reveals about women entering the trades and pay equity. Practical AI supports recruiters and workers without removing humans from high-stakes decisions.  •Diagnosing labor shortage as an access and data problem • Founder’s journey from journeyman carpenter to tech builder • Fuilding ...]]></itunes:summary>
    <description><![CDATA[<p>We talk to Fraser Patterson, CEO and founder of Skillit, about how digitizing skilled trade workers would affect hiring speed and quality, why construction jobs are resistant to AI displacement, and what new data reveals about women entering the trades and pay equity. Practical AI supports recruiters and workers without removing humans from high-stakes decisions.<br/><br/>•Diagnosing labor shortage as an access and data problem<br/>• Founder’s journey from journeyman carpenter to tech builder<br/>• Fuilding data-rich worker profiles and semantic search<br/>• Privacy-preserving eligibility checks via co‑pilot outreach<br/>• Scale and demand for data center and energy projects<br/>• Worker-friendly onboarding designed for deskless realities<br/>• Rigorous screening and trade assessments as skill signals<br/>• Women in trades data, faster ramp, smaller pay gap<br/>• Why construction resists automation and offshoring<br/>• AI for scheduling and sourcing with humans in the loop<br/>• Focus on US now with future global expansion<br/><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>We talk to Fraser Patterson, CEO and founder of Skillit, about how digitizing skilled trade workers would affect hiring speed and quality, why construction jobs are resistant to AI displacement, and what new data reveals about women entering the trades and pay equity. Practical AI supports recruiters and workers without removing humans from high-stakes decisions.<br/><br/>•Diagnosing labor shortage as an access and data problem<br/>• Founder’s journey from journeyman carpenter to tech builder<br/>• Fuilding data-rich worker profiles and semantic search<br/>• Privacy-preserving eligibility checks via co‑pilot outreach<br/>• Scale and demand for data center and energy projects<br/>• Worker-friendly onboarding designed for deskless realities<br/>• Rigorous screening and trade assessments as skill signals<br/>• Women in trades data, faster ramp, smaller pay gap<br/>• Why construction resists automation and offshoring<br/>• AI for scheduling and sourcing with humans in the loop<br/>• Focus on US now with future global expansion<br/><br/><br/></p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2530725/episodes/18386832-fraser-patterson-of-skillit-a-data-first-job-platform-aims-to-solves-construction-s-labor-shortage.mp3" length="16930425" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/z5mgpygt4pmq98antobbvtv5ki7u?.jpg" />
    <itunes:author>Roopinder Tara</itunes:author>
    <guid isPermaLink="false">Buzzsprout-18386832</guid>
    <pubDate>Fri, 19 Dec 2025 11:00:00 -0800</pubDate>
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18386832/transcript" type="text/html" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18386832/transcript.json" type="application/json" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18386832/transcript.srt" type="application/x-subrip" />
    <podcast:transcript url="https://www.buzzsprout.com/2530725/18386832/transcript.vtt" type="text/vtt" />
    <podcast:chapters url="https://www.buzzsprout.com/2530725/18386832/chapters.json" type="application/json" />
    <psc:chapters>
  <psc:chapter start="0:00" title="Welcome And Labor Shortage Reality" />
  <psc:chapter start="1:08" title="The Core Problem: Undigitized Workforce" />
  <psc:chapter start="2:16" title="Founder’s Journey From Trades To Tech" />
  <psc:chapter start="3:47" title="Building A Data-Rich Talent Engine" />
  <psc:chapter start="4:08" title="Scale, Customers, And Growth Metrics" />
  <psc:chapter start="4:53" title="Data Center Demand At Scale" />
  <psc:chapter start="5:35" title="Privacy, Eligibility, And Co‑Pilot Outreach" />
  <psc:chapter start="6:41" title="Why Workers Join: Less Friction, More Fit" />
  <psc:chapter start="8:20" title="Vetting, Assessments, And Signal Of Skill" />
  <psc:chapter start="9:46" title="Women In The Trades: What The Data Shows" />
  <psc:chapter start="12:18" title="Why Construction Resists Automation" />
  <psc:chapter start="13:21" title="Practical Uses Of AI With Humans In Loop" />
  <psc:chapter start="14:03" title="Competition, Focus, And Future Expansion" />
  <psc:chapter start="15:30" title="Closing And Listener Invitation" />
</psc:chapters>
    <itunes:duration>1407</itunes:duration>
    <itunes:keywords>Please move this episode to ENGtechnica TV podcast</itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>11</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
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