Browsing: NVIDIA

Tech giant Nvidia announced that it has agreed to back hundreds of billions of dollars for a new data center that is being constructed in southern Ohio.

Cisco’s full-stack architecture adds massive AI computing power, offering an NVIDIA Cloud Partner compliant reference architecture built for surging neocloud and sovereign cloud demand.

SANTA CLARA, Calif., Aug. 24, 2026 — NVIDIA today announced that SpaceXAI will deploy NVIDIA Vera CPUs to accelerate its next generation of agentic AI applications, bringing the first CPU built for AI agents to one of the world’s most ambitious AI deployments.

Aug. 24, 2026 — NVIDIA today announced that NVIDIA Groq 3 LPX, the interactive AI inference accelerator, is now in full production. An extension of the NVIDIA Vera Rubin platform, Groq 3 LPX delivers a major boost in AI inference by enabling ultrafast token generation for highly responsive agentic systems.

Nvidia (NASDAQ:NVDA) is reportedly holding talks about investing in artificial intelligence startup Perplexity through a new financing round that could value the company at more than $30 billion

When Nvidia (NVDA) reports its must read earnings report on Wednesday evening, it will be confronting this frustrating reality.

Add to Google Preferred Sources Nvidia is in talks to participate in a new equity funding round for AI search startup Perplexity, a multi-billion-dollar raise that would push the company’s valuation past $30 billion—up more than 50% from a year ago. Perplexity’s annualized revenue has surged from under $250 million at the start of this…

Its latest growth figures point to a dramatic acceleration, while a powerful new backer could reshape the startup’s path toward a planned public listing.

Aug 23 (Reuters) – Nvidia is in talks to invest in Perplexity as part of an equity ‌funding round that would value the AI startup ‌at more than $30 billion, The Information reported on Sunday, citing people ​with knowledge of the discussion.

AI factories are power-constrained industrial systems. The question is no longer how many GPUs fit in a data center, but how much AI output each available megawatt can deliver. For AI inference workloads, this makes application-level performance per watt the key metric for measuring AI factory efficiency.