Nvidia is a US chip company that designs GPUs and AI computing platforms, and its CUDA software stack is widely used to train and run AI models. Recent coverage has centered on its stock and valuation: Apple overtook Nvidia as the world's most valuable company on Oct. 30, and Nvidia shares fell as much as 5.3% that day, with FQ2 revenue of $96 billion, up 106% year over year. Nvidia also plans a $1 billion investment in Naver for a 4.54% stake.
London-based Basecamp Research has raised $140 million from investors including Nvidia and Anthropic's Anthology Fund. The startup trains AI models on genetic material from rainforests, oceans and hot springs to design antibiotics and cell-therapy tools. Its CTO says biology is a far harder problem for AI than language, and that good benchmark scores do not guarantee good molecules.
NVIDIA released Nemotron 3 Diarization, an open-weight 100M-parameter model that ranks first on VoiceArena's diarization leaderboard with a 14.72% Diarization Error Rate. It supports up to eight speakers in live and recorded conversations, handles overlapping speech, and offers customizable streaming latency.
Maria Angelicoussis, heir to Greece's biggest shipping fortune, has scored big gains outside her maritime empire by betting on Nvidia through her family office, which shifted away from private markets.
Australian AI startup Firmus Technologies is in talks with lenders for about $10 billion to buy Nvidia chips for its Indonesian data center. If completed, it could be one of Asia's largest AI infrastructure deals.
At AI Day Singapore, NVIDIA and partners showcased AI advancements across Southeast Asia, highlighting moves from pilot to production for public sector AI. Singapore's HTX is researching public safety uses with NVIDIA Nemotron 3 Super and Nemotron 3 Nano Omni models.
Enterprises should own their intelligence.
That means bringing AI to their sensitive data while protecting both business data and proprietary models.
NVIDIA’s @j_boitano and @VAST_Data Renen Hallak discuss how NVIDIA Confidential Computing makes this possible.
TechCrunch Disrupt 2026 will host five AI safety sessions across its AI Stage and Real World AI Stage, featuring speakers from Anthropic, NVIDIA, AWS and Waabi. The sessions focus on how enterprises can safely deploy AI agents into production, with passes discounted up to $200 before Sept 25.
A paper finds open-weight inference costs about one-fifth of comparable closed models, with self-hosting at $0.12-$0.35 per million output tokens. On gpt-oss-120b, the A100 is cheaper than the H100, and A100 five-year rental prices retain 80% of one-month prices, showing older GPU families keep multi-year earning life.
At the G20 Innovation Ministerial, @JensenHuang joined U.S. Commerce Secretary @howardlutnick to discuss the infrastructure the Intelligence Age requires.
A gigawatt-scale AI factory is a $50–60 billion investment. At that cost, the architecture cannot be so…
British AI data center developer Nscale is listing on the NYSE at an expected $35B valuation, seeking $3B. It holds over $103B in contracts, but about 85% depends on Microsoft and Anthropic; Anthropic's deal is contingent on financing and can be cancelled if milestones are missed. Revenue hit $140.6M for the six months to June 30, with net losses of $1.02B.
At ROSCon, NVIDIA released Isaac ROS 5.0, a collection of GPU-accelerated ROS packages serving nearly 1.3 million ROS users. It adds agentic workflows, supports ROS Lyrical and Ubuntu 24.04, and contributes a standard data-handling interface with the Open Source Robotics Alliance.
Armenia, once an electronics and tech hub of the Soviet Union, is now on track to become one of the world's top hubs for American AI infrastructure, driven by Nvidia chips and Donald Trump.
Alibaba is rolling out what it calls China's most powerful AI chip, an accelerator aimed at competing with Nvidia and underpinning a major expansion of data-center capacity in coming years. The move highlights Chinese tech giants' push to build in-house AI silicon amid computing supply constraints.
NVIDIA introduced DSX Ready, a qualification program initially covering battery energy storage systems and cooling distribution units, with Tesla, LG Energy Solution and Hitachi Energy among qualified partners. It aims to help builders evaluate power and liquid-cooling options against AI factory reference designs and cut integration risk.
Nvidia is buying an additional $1.5 billion in shares of SB Energy, a SoftBank-backed data center provider, ahead of its US IPO, underscoring Nvidia's continued push into data center and energy infrastructure that supports AI computing.
Grok 4.7 has landed. 🚀
Congrats to @SpaceXAI on its most capable model yet for coding and knowledge work.
Proud to support the team with NVIDIA accelerated computing.
[Quoting @elonmusk]: Grok 4.7 is a strong combination of intelligence, speed & low cost
NVIDIA highlights that physical AI is rapidly moving from research to large-scale deployment. ABI Research projects 49 million level 3-5 autonomous vehicles by 2035, while Omdia estimates roughly 60 million industrial robots will be deployed between 2026 and 2035. Safety must span hardware, software, AI, operating environment, and deployment lifecycle—not a one-time check—and emerging standards like ISO/IEC TS 22440 are beginning to address AI behavior assurance.
At an event at the Grand Egyptian Museum, NVIDIA executives and Egypt's AI ecosystem participants discussed the country's AI growth. The NVIDIA Deep Learning Institute learner base in Egypt grew more than tenfold in a year, and Hassan Allam Data Centers received a license to build and operate data centers. Hassan Allam Utilities and A15 agreed to develop a new data center with an estimated $400 million investment.
An NVIDIA security blog argues AI security is fundamentally an engineering problem requiring defined requirements, enforceable controls, named owners and verification. Because AI agents reason and use tools, risk spans the model, harness and runtime layers—for example, malicious document instructions could push an agent to exfiltrate data, requiring network policy blocks and auditable logs.
Congratulations to @einrideofficial on bringing autonomous trucking to highways and suburban roads with the next generation of Einride Driver.
Built on NVIDIA Hyperion.
[Quoting @einrideofficial]: Einride enters a strategic collaboration with @NVIDIADRIVE to…
Microsoft raised its quarterly dividend 8% to $0.98 per share, a cumulative increase of more than 151% over a decade; its 0.8% yield is low, but stock gains have shifted investor focus to its AI growth prospects.
NVIDIA highlights five companies using its AI for clean energy at NY Climate Week. For instance, ThinkLabs AI reduced grid interconnection evaluation from 30-45 days to 2 minutes using digital twins, showcasing AI's potential in energy transition.
Hugging Face released a v1 release candidate of tokenizers focused on performance, saying it is often tens of times faster than v0.23. The team says tokenization can bottleneck large-scale training, high-concurrency serving and long inputs, leaving GPUs idle. IBM, NVIDIA and the ExecuTorch team contributed patches and cross-hardware testing.
A Swedish startup's attack drones run a small AI model on Nvidia's Jetson Orin Nano to independently select and bomb targets, requiring no human input and zero external communications.
Nvidia estimates it shipped over a billion RISC-V cores in 2024, placed in small management processors inside its GPUs rather than shader cores; each GPU has 10 to 40 depending on model. The cores are not user-programmable and are cryptographically verified, and one has handled much graphics-driver work since 2018, after a decade of Nvidia's proprietary Falcon microcontrollers.
GameGPU reports that AMD's next-gen Radeon RX 10800 XT may outperform Nvidia's RTX 5090 by 15-25% in 4K gaming and local AI workloads, per a Reddit share. No official confirmation yet.
The Motley Fool predicts Nvidia-backed Marvell Technology could 10X by 2033. Its fiscal 2026 revenue hit a record $8.2B, up 41% year over year, with data center revenue up 46% to $6.1B, driven by custom silicon demand.
A Motley Fool comparison of AI stocks Nvidia and Micron notes Nvidia's $5.3 trillion valuation versus Micron's $1.1 trillion, with Micron DRAM chips used in Nvidia GPUs. It cites forecasts that the big five hyperscalers will spend nearly $800 billion on data center capex in 2026 and $1.3 trillion in 2027, while warning Micron's memory price gains may fade as new supply comes online.
NVIDIA launched AIPerf, a ground-up rewrite replacing GenAI-Perf, using a multiprocessed ZMQ architecture to bypass the Python GIL for accurate LLM inference benchmarking. It supports over 15 endpoint types and datasets like ShareGPT.
Nvidia CEO Jensen Huang told CBS that AI development should not slow down over others' concerns, while stressing products would not ship before they are ready or safe. His remarks follow an Anthropic researcher's resignation and CEO Dario Amodei's warnings on AI risk, with Nvidia now worth over $5 trillion.
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Basecamp Research raises $140M to train AI on evolution data
