Technology and the stock market seem to operate in separate universes. Looking at the stock market this week, one might think it’s a bad time for tech. Market indexes are all down, and tech is providing no relief. Nvidia’s stock is down 2.9% this week, and Microsoft, Google, Meta and Amazon are all trading at lower levels now than when markets opened on Monday.

The stock market masks the fact that Nvidia just projected $1 trillion in annual revenue this year—a development that one would think would generate excitement among investors in all kinds of tech, considering that Nvidia’s primary product is the infrastructure underlying most AI. And even without the ongoing war in Iran, the skyrocketing gas prices it brings, and dispiriting economic indicators, including a freeze in interest rates, tech stocks would likely still be relatively down. Wall Street tends to second-guess AI companies’ revenues and projections, questioning whether developments will translate into real increases in business. In Nvidia’s case, it’s consistently outperformed expectations in the recent past—though as the year progresses, we’ll see if it’s set the bar too high.

One thing that impacts every company in every sector is cybersecurity. Remedio CEO Tal Kollender says many companies are overlooking significant risks by focusing on weaknesses in big systems—but forgetting about smaller vulnerabilities across systems, applications and AI. I spoke with her about how to find these weak points and shore them up. An excerpt from our conversation is later in this newsletter.

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Nvidia’s GTC 2026 wraps up today, and it’s been a week full of announcements about the next chapter of AI from the company that’s synonymous with its infrastructure. But the biggest announcement wasn’t truly about new products. At his keynote address, CEO Jensen Huang unveiled the next step for Nvidia: A five-layered full-stack platform approach to AI, showing that the company will own every section of the AI stack, writes Forbes senior contributor Janakiram MSV.

At the bottom is Nvidia’s compute substrate, anchored by its Vera Rubin platform with its seven specialized chips, five rack-scale systems and an integrated supercomputer built for AI workloads. Above that is the networking and data acceleration layer, with NVLink 6 and Spectrum-X. The agent runtime layer is in the middle, represented by the new enterprise NemoClaw stack. Next is the open model ecosystem through the Nemotron Coalition, covering six frontier model families. At the top is the AI factory design layer, with the DSX reference architecture and Omniverse Digital Twin blueprint.

MSV writes that this is the logical next step for Nvidia. The world’s most valuable company became dominant with its GPUs for AI training infrastructure. But as AI develops, the larger need is in inference at scale and always-on agentic systems generating myriad tokens—and Nvidia wants to run the........

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