Jetson Orin Nano 2 is the module NVIDIA announced on 25 August 2026 to put physical AI inside delivery drones, inspection drones, home robots and factory vision systems. The headline everyone ran was the same one NVIDIA led with: twice the inference performance of the outgoing Jetson Orin Nano Super, in the same form factor, […]
Ternus era began at Apple on 1 September 2026, and it began in the same week that Nvidia agreed to spend $12.93 billion buying the world’s largest open model hub. Two of the most valuable companies on earth answered the same question — how do you win artificial intelligence? — and gave opposite answers within […]
Hugging Face acquisition rumours ended on Thursday 3 September 2026, when Jensen Huang published a blog post confirming that Nvidia has agreed to buy the platform for $12,930,300,000. Not “roughly $13 billion” — that exact figure, down to the hundred thousand. It is the second-largest deal in Nvidia’s history, behind only the $20 billion it […]
RTX Spark superchip laptops go on sale this autumn, and they are not another spin on the Copilot+ badge. Nvidia has taken the Grace CPU and Blackwell GPU pairing it built for desk-side AI boxes, shrunk it into a chassis as thin as 14mm, and persuaded six of the largest PC makers in the world […]
Acer used IFA 2026 to show off the SFF RTX Spark, a small-form-factor desktop concept built on NVIDIA’s RTX Spark superchip: up to a 20-core Grace CPU, a 6,144-core Blackwell GPU, 128 GB of unified memory and one petaflop of AI compute in a vertical shell with a fold-out stand. Alongside it, the palm-sized Veriton RI110 mini workstation ships first, from Q4 2026. This article breaks down the specs, the local agentic AI pitch, the vendor ecosystem shipping from fall 2026, and what a petaflop on the desk means for creators, developers, gamers and business buyers.
Nvidia is investing $3.5 billion in MediaTek through convertible bonds, announced 31 August 2026, deepening a partnership spanning AI data centres, RTX and DGX Spark-class PCs and automotive platforms. MediaTek will adopt Nvidia’s NVLink Fusion and NVHBM interconnects to design custom chips for AI companies and hyperscalers that plug straight into Nvidia-based data centres. This analysis covers what the deal includes, why it lands as Amazon, Google, Microsoft, OpenAI and Anthropic build their own silicon, MediaTek’s $2 billion-to-$12 billion data-centre ambition, the risks, and what it means for businesses buying AI services.
Nscale has agreed to sell Anthropic roughly $45 billion of AI computing capacity over six years, according to Bloomberg and CNBC reporting on 26 August 2026. The capacity amounts to about 460 megawatts at a West Virginia campus, fitted out with Nvidia Vera Rubin systems arriving from late 2027. This breakdown covers the reported terms, what 460 megawatts actually means, who Nscale is and how a $45 billion contract reshapes its September listing plans, the Monarch Compute Campus and its off-grid gas microgrid, the Vera Rubin generation-on-generation numbers, where the deal sits alongside Anthropic’s Google, Broadcom, Amazon, Microsoft and SpaceX commitments, the price per megawatt-year, the risks nobody is pricing, and what any of it means for organisations that buy AI rather than build it.
New Cornell research answers the AI bubble question with a statistical test rather than an opinion, and the answer is neither yes nor no. Using a stochastic-volatility-robust augmented Dickey-Fuller framework, Abir Sarkar and Martin Wells date-stamp the start and end of explosive price behaviour for twelve AI-exposed firms across 2018 to 2026. The sector as a whole shows no exuberance, and neither does the NASDAQ Composite; Alphabet, TSMC, Micron, Nvidia, Broadcom and Palantir do. This breakdown reads every date stamp the model produced, compares them with the standard test that flags eleven of the same twelve companies, sets the result against the Bank of England’s warnings on concentration and leverage, and translates the whole thing into the only question most businesses actually need to answer about their AI suppliers.
Perplexity announced Portable Computer on 25 August 2026, built in close partnership with Nvidia: the full agentic Computer stack — model, inference engine, agent harness, tools, connectors and sandbox — running on your own hardware, where local work consumes no billing credits. It needs an Nvidia RTX GPU with at least 24GB of VRAM or a DGX Spark, runs on DGX OS or Ubuntu with Windows due in September 2026, and offers Qwen 3.8 27B, Perplexity’s post-trained PPLX 27B and, soon, Nvidia’s Nemotron 3.5 Lightning. This breakdown covers the hardware floor, the per-step cloud escalation flow, Perplexity’s own benchmark numbers, what zero token costs actually excludes, and who should pilot it now.
At the Hot Chips conference on 25 August 2026, OpenAI published the first benchmark results for Jalapeño, the custom inference chip it built with Broadcom. On SemiAnalysis’s InferenceX benchmark, OpenAI reported 1.5x to 1.9x more work per watt and 1.7x to 3.6x lower end-to-end latency than an Nvidia Blackwell system, rising to 4.1x faster on highly interactive workloads. Here are the numbers, the architecture behind them, what OpenAI still has not disclosed, and what it means for anyone buying AI capacity.
