It’s only Monday, and NVIDIA is already having a busy news day. Mark's take: @Meta’s Prometheus is pushing toward a million GPUs, while @NVIDIA uses thousands to simulate quantum computing’s messy realities. One builds bigger. The other helps researchers build smarter. Both expose an uncomfortable truth: buying compute is easier than making it productive. Cooling, networking, reliability, and error management increasingly determine who wins. NVIDIA powers today’s AI ambitions while helping engineer tomorrow’s quantum breakthroughs. The next competitive moat may come from mastering complexity, not simply accumulating chips. That’s where this race gets interesting. #NVIDIA #Meta #AI #QuantumComputing #DataCenters #AcceleratedComputing #SmartTechResearch @BrettBFaulk #KristineNeufeld #KristelMichielsen @JensenHuang #KevinLee #YasharBayani #AdhmedSharif @Thinkers360 @TechNewsNetwork

Could your next PC be an iPhone or Android phone? Earlier attempts to turn phones into PCs never became mainstream. What’s different now? @Apple’s iPadOS windowing and external-display capabilities, alongside @Google’s work on #Android desktop experiences and resizable apps, point toward more capable computing across screens. Add stronger mobile processors, adaptive apps, and cloud services, and the pieces begin to line up: the phone supplies the compute, the platform manages the workspace, and apps adapt to the larger display. Our new SmartTechCheck EduSeries video explores Lotus—a concept that brings those pieces together for phone-powered desktop and laptop experiences. Neither Apple nor Google has committed to Lotus; we examine what their platform directions could enable, who might benefit, and what still needs to be proven. See the link in COMMENTS to watch the video and tell us: Do you find the Lotus concept appealing? #SmartTechCheck #FutureOfComputing #LotusConcept @BrettBFaulk @Thinkers360 @TechNewsWorld

#SmartTechResearch's take: AI has a power problem, and more GPUs won’t fix it. @Infineon and @NVIDIA are tackling the electrical bottleneck with 800 VDC architectures and gallium nitride technology. Less wasted energy. Less heat. More compute density. The next AI breakthrough could start with how we power it. #Infineon #NVIDIA #AI #GaN @BrettBFaulk @Thinkers360 @TechNewsWorld

@NVIDIA’s "sprawling" GTC Berlin announcements underscore its ambition to shape the entire AI infrastructure stack, spanning computing, deployment, security, power management and telecommunications. DSX POD introduces modular, factory-integrated AI infrastructure that NVIDIA says can reduce deployment at prepared sites from six months to as little as 14 days. Its broader DSX platform targets another critical constraint: energy efficiency, with claims of equivalent AI output using up to 30% less power. OpenShell addresses enterprise concerns about autonomous agents through isolation, monitoring and policy enforcement. Meanwhile, NVIDIA’s collaboration with Nokia and telecom operators extends accelerated computing into networks, bringing intelligence closer to users and connected equipment. Mark's take: collectively, these initiatives reinforce NVIDIA’s leadership by connecting its silicon and software with the practical requirements of operating AI at scale. Its extensive partner ecosystem further strengthens that position. However, announcements should be distinguished from demonstrated outcomes across broad commercial deployments. Site readiness, electricity availability, integration costs and customer adoption will determine how quickly these capabilities translate into business value. NVIDIA is addressing deployment economics and operational trust alongside performance. Sustained leadership will depend on delivering measurable improvements that customers can reproduce under their own operating conditions. #NVIDIA #GTCBerlin #ArtificialIntelligence #AIInfrastructure #AgenticAI #Telecom #SmartTechResearch @BrettBFaulk #KristineNeufeld @Thinkers360 @TechNewsWorld @JensenHuang