Key M&A deals this week include DoubleVerify, AMD, Visa, Prologis

Microsoft announced on the 7th that it will release the Surface Laptop Ultra, a notebook computer specialized for artificial intelligence processing, on the 16th. Equipped with the new RTX Spark AI chip from major U.S. semiconductor maker Nvidia, it can run high-performance AI models on the device itself. Because data can be processed within the device without being sent to clouds operated by AI companies, it suits highly confidential work such as preparing tax documents, and it can also handle games that demand high processing power. It runs Windows 11 as its operating system. Its retail price in Japan starts at 513,480 yen. At the announcement event on the 7th, Nvidia Chief Executive Officer Jensen Huang said, "We have completely reinvented the personal computer."

Microsoft on Wednesday unveiled its Nvidia-powered Surface Laptop Ultra, a laptop designed to let users run AI models at home without relying on the cloud. Starting at $2,599, the Surface Laptop Ultra runs on Nvidia's Arm-based RTX Spark, which offers upwards of 128GB of onboard memory. Microsoft and Nvidia, along with rivals Apple, Intel, and AMD, are increasingly pushing the concept of running AI software in the home, where users install an app, download an open-weights model, and work without usage limits while keeping their data private. But local AI is not for everyone: it demands heavy system resources, and a Google AI subscription, for example, gives access to Gemini 3.1 Pro and Deep Research in Gemini plus 400GB of cloud storage for $4.99 per month. The Surface Laptop Ultra can likely handle local AI workloads with ease, but its price tag is a bit high for all but the biggest AI boosters and enthusiasts.

ASUS has opened global pre-orders for its new ProArt RTX Spark Windows PCs, a lineup of creator laptops and a mini PC powered by NVIDIA RTX Spark, with pre-orders starting October 7 and shipping estimated to begin October 16, 2026. The lineup comprises the ProArt P16 and P14 laptops and the compact ProArt GR1X mini PC, all built on NVIDIA RTX Spark, which combines an NVIDIA Blackwell RTX GPU, an NVIDIA Grace CPU, fifth-generation Tensor Cores with FP4 support and NVIDIA NVLink-C2C interconnect technology, delivering up to 1 petaflop of AI performance and up to 128GB of high-bandwidth unified memory. In Canada, the ProArt P14 will initially be offered with 24GB or 128GB of LPDDR5X memory and the ProArt P16 with 32GB or 128GB, with 48GB ProArt P14 and 64GB ProArt P16 configurations arriving later this year; the ProArt P14 starts at C$3,499 and the ProArt P16 starts at C$4,999. ASUS is pairing the hardware with an agent-and-application ecosystem that includes its preloaded MuseTree and StoryCube apps, its Zenni Claw assistant, and partnerships with ComfyUI and Hermes Agent by Nous Research, alongside Adobe Creative Cloud bundles and a Google AI bundle on eligible laptops. The ProArt RTX Spark PCs sit within a broader ASUS local AI portfolio that also includes systems equipped with GeForce RTX 50 Series GPUs, the ASUS Ascent GX10 powered by NVIDIA DGX Spark, and the ASUS ExpertCenter Pro ET900 powered by NVIDIA DGX Station.

Cerebras Systems has secured a deal with Gimlet Labs, which agreed to use its wafer-scale chips inside a new disaggregated inference cloud targeting ultrafast agentic and real-time AI workloads for paying customers. The partnership lands after a volatile stretch for Cerebras, during which conflicting headlines around its OpenAI relationship swung sentiment and short-term trading. Even with recent rebounds on Altman's public backing, the stock's share price return is still down 15.7% over 30 days and 43.1% year to date. Cerebras last closed at $177.10, while the most followed narrative values the stock at $415.54, framing a large gap between trading price and perceived long-term potential. The story could still unravel quickly if OpenAI pulls back on spending or if the mid November share unlock floods the market with selling.

Elon Musk agreed with a Tesla AI engineer's argument that the automaker's early decision to develop and deploy custom inference computers across its vehicle fleet could look unprecedented as demand for artificial-intelligence compute accelerates. "Yes," Musk wrote on X on Sunday in response to Tesla engineer Yun-Ta Tsai, who said Tesla's years of iterating and scaling its own inference computers for each car sold could prove unusually important before the superintelligence era, adding that the current compute shortage is only the tip of the iceberg and that when autonomy becomes indispensable, the real shortage will follow. Tesla has spent years designing its own inference hardware to run neural networks inside vehicles rather than relying entirely on general-purpose processors, and that strategy is now advancing through AI5 and AI6, with the company saying in January that development of both custom inference chips had progressed and production was then planned for 2027 and 2028, respectively. Musk has separately said AI5 will punch far above its weight and is primarily optimized for edge computing in Robotaxi and Optimus, and during the second-quarter earnings call he said the company's planned Terafab is necessary because Tesla otherwise simply won't have enough AI chips to scale Optimus. Reuters reported in April that Tesla, SpaceX and xAI are pursuing Terafab partly because Musk expects outside suppliers cannot satisfy their long-term chip requirements, with Tesla's Austin development fab alone expected to cost roughly $3 billion.