Search Results: AIinfrastructure

Y Combinator’s latest cohort is less about flashy consumer apps and more about the hidden rails that will carry the next wave of AI. From zero‑trust security for agents to AI‑powered on‑call systems, these 150 startups are redefining how businesses build, secure, and scale intelligent tools.

As AI data centers multiply, utilities are forecasting massive energy increases, but questions linger about whether these projects are real or speculative. The uncertainty is driving up electricity bills and prompting a regulatory scramble to protect consumers from footing the bill for phantom infrastructure.

In a surprising turn, bipartisan opposition to data centers is gaining traction across the U.S., particularly in red states like Georgia and Virginia, where newly elected officials are championing community concerns over resource consumption and tax breaks. A new report from Data Center Watch reveals a sharp escalation in resistance, blocking or delaying $98 billion in projects in just three months. As big tech pours billions into AI infrastructure, this grassroots movement signals a pivotal shift in how communities balance economic growth with environmental and affordability impacts.

Anthropic's $50 billion investment in custom-built data centers signals a major shift in how AI companies secure computing power, potentially setting new standards for the industry while raising questions about sustainability and the widening gap between tech giants and startups.

With gpt-oss-120b and gpt-oss-20b, OpenAI has stepped back into the open-weight arena—and straight into the plans of US military contractors who need air-gapped, customizable AI. The models aren’t yet best-in-class, but their mere existence is reshaping how defense, intelligence, and critical industries think about autonomy, trust, and vendor lock-in in the LLM era.

Amid bloated AI pilots and brittle chatbots, Kaarya AI is pushing a retrieval-native architecture designed to handle real enterprise work: contracts, support, operations, and decision flows. Its stack, centered on Retrieval Augmented Workflows, aims to move AI from impressive demos to systems teams can trust in production.