Shares of AI chipmaker Nvidia plunged on Wednesday, dropping by over two percent in early trading. A major tech selloff caused major players in the AI industry to lose out big. Nvidia, in particular,

The other scorching-hot artificial intelligence stock that stands out in Nvidia's $4.33 billion investment portfolio is semiconductor colossus Arm Holdings ( ARM -5.00%). Nvidia closed out June with the same number of shares of Arm as it had in March (1,101,249), which worked out to a market value of $178.1 million.

The Chinese impact on Nvidia is significant. KeyBanc raised its Q2 revenue estimate to $47.1 billion from $45.1 billion, above Wall Street’s consensus of $45.7 billion. It raised earnings per share to $1.05 from $0.99, slightly above consensus of $1.00.

Nvidia (NASDAQ:NVDA) stock continues to be the talk of the town. Jensen Huang’s GPU empire has really made the most of the AI boom. And while there will be other winners from this revolution, especially as agents and the race to AGI (artificial general intelligence) fuels the boom,

Nvidia ( NVDA 0.94%) owns stock in publicly traded companies as part of its treasury strategy. Its $4.3 billion portfolio included six positions as of the June-ending quarter, but two accounted for 95% of invested assets: 91% was allocated to CoreWeave ( CRWV -3.17%) and 4% was to Arm Holdings ( ARM 1.52%).

Nvidia's (NVDA) upcoming quarterly results on August 27 are likely to be another “positive catalyst” for investors, Wedbush Securities said. Read for more.

NVIDIA's next-gen Rubin AI GPUs rumored to be delayed, redesigns happening to better compete with AMD's upcoming Instinct MI450 AI accelerators.

Nvidia is far and away the main supplier of AI-focused GPUs, with an estimated market share of over 90%. This virtual monopoly has paid off for Nvidia (quite literally), increasing its revenue from $8.3 billion in its 2023 fiscal first quarter to $44 billion in its 2026 fiscal first quarter (ended April 27).

The Allen Institute for AI (Ai2) will receive $152M from Nvidia and the NSF to lead a five-year project building fully open AI models for science.