The tech giants are keeping capital spending plans in line as DeepSeek raises questions about future computing needs.
Key tech stocks were a mixed bag in early trading Thursday after executives at Meta and Microsoft said they plan to keep pouring billions of dollars into AI – despite lingering anxiety over the
Retail investors bought a net $562 million of Nvidia stock on Monday, the largest single-day inflow in at least 10 years, VandaTrack said.
When OpenAI released ChatGPT in 2022, companies started spending billions on GPUs to train AI models. Nvidia led the market for graphics processing units (GPUs), so it was the right company at the right time to deliver monster returns to investors.
Microsoft, MSFT, CEO Satya Nadella is expected to talk about DeepSeek, Stargate, Azure, Copilot, AI, GenAI and more on the tech vendor’s 2Q 2025 earnings call.
Nvidia shares' 9% recovery Tuesday was the second-best day in terms of market cap added for any company ever—but the company faced another selloff Wednesday.
Distilled R1 models can now run locally on Copilot Plus PCs, starting with Qualcomm Snapdragon X first and Intel chips later. This brings a lot more AI capabilities to Windows, and it’s something Microsoft was already working on with its Phi Silica language models.
Nvidia is launching its next-gen RTX 5090 and RTX 5080 GPUs today, but it’s also releasing an exciting update for existing RTX GPU owners. A new GPU driver (572.16) allows you to force DLSS 4 inside games or apps that don’t currently support it, providing improved image quality and even less VRAM usage in some cases.
The tech giant’s revenue was up 12 percent to $69.6 billion, but investors are showing their nerves after a long boom for tech stocks.
In its own research, DeepSeek said it had “distilled” models from its R1 system based on other open-source systems. Unlike OpenAI’s closed systems, some models such as Meta’s Llama are open-source and freely available for use.
Nvidia is the gold standard and leading provider of the graphics processing units (GPUs) used to train and run AI systems. The company is believed to control as much as 98% of the data center GPU market, according to semiconductor analyst firm TechInsights. If AI models can be trained on lower-cost, inferior chips, Nvidia has a lot to lose.