Uptime
Uptime on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on uptime in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around uptime, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.

Enterprises put non-Nvidia chips 14 points ahead of Nvidia's next-gen GPUs on their evaluation lists
Recent VentureBeat research reveals a significant shift in enterprise AI accelerator strategy. While Nvidia remains dominant in production environments, a striking 39.4% of organizations are now actively evaluating non-Nvidia alternatives like AWS Trainium and Google TPUs – a 14-point increase over Nvidia's next-gen GPUs. This indicates a move toward greater optionality and workload-level scrutiny, with organizations prioritizing integration, performance, and cost-effectiveness. Enterprises are increasingly seeking control over their AI infrastructure, a trend underscored by growing interest in open-source components.

Amazon AGI director says AI agent reliability, not capability, is blocking enterprise deployment at VB Transform 2026
Amazon AGI director Bryan Silverthorn identifies a critical obstacle to enterprise AI agent deployment: reliability, not simply capability. Addressing VentureBeat's Transform 2026 audience, Silverthorn highlighted a concerning trend—85% of enterprises pilot AI agents, yet only 5% reach production. He proposes a framework of consistency, robustness, predictability, and safety to measure agent performance, noting that many agents excel in internal evaluations but falter in real-world use. Ultimately, successful deployment hinges on strong management practices, not just advanced models.