Jas S.

Nearly every industry is having its "I know kung fu" moment, transforming the world so fast that the human mind can barely grasp what it might look like in five years. It's both thrilling and full of promise - the potential for humanity feels immense.

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See how the release of Llama4 models, Scout and Maverick, on OCI Generative AI service are optimized for multimodal understanding, multilingual tasks, coding, tool-calling, and powering agentic systems. https://lnkd.in/gRqmRE6b

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Researchers at UCLA and UC Riverside have created a quantum computing device that operates at room temperature, potentially reducing energy costs and advancing hybrid quantum-classical systems.

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⚙️ Claude Code is creating a buzz among Seattle engineers, who describe the AI tool as a supercharged coding partner that can refactor large codebases, handle tedious boilerplate, and stitch services together at speed. The article paints a picture of software teams rethinking roles, workflows, and onboarding as coding assistants shift from autocomplete to true collaborators. For engineering leaders, the big challenge is how to harness this productivity jump while maintaining code quality, security, and human expertise in the loop. #AI #Claude #SoftwareDevelopment #EngineeringLeadership #DevTools #Productivity #AIFreakyFacts

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What a great example of #airporttech! I like the "...friendly nudge by an officer." Excellent use case of curb management. Thank you Andrew K Kirk and Automotus for your partnership. INRIX #airports #govtech

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Wrapping a “thin candy shell” around frontier models doesn’t scale. Still, its an easy pitfall to accidentally build AI products that lose their edge as models improve. At our Precision Unveiled event at San Jose, hosted at the Computer History Museum, I was reminded that every computing shift reshapes how engineers work. Tektronix has been part of that story for decades. I’ve been learning AI through the lens of daily work and software development – productivity gains, agent-assisted coding, and new workflow patterns. The improvements are tangible. But translating those learnings into test and measurement is where it gets interesting. In our world, trust is key - in the data, the automation, and in the workflows we rely on. From a product perspective, that means being deliberate about what we build. We should design offerings whose value compounds as models advance and avoid filling temporary capability gaps that frontier models will absorb. I would love to hear about your thinking regarding similar challenges in your own engineering workflows. #Tektronix

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