Nvidia Expands AI Agent Toolkit for Engineering Design

UBS now expects artificial intelligence capital expenditure to reach nearly $1 trillion in 2026 before climbing to around $1.4 trillion in 2027, with surging memory costs accounting for most of the increase. The bank's updated estimates put total AI capex at $998 billion this year, almost double the $506 billion recorded in 2025, and forecast spending of $1.447 trillion next year. Memory is emerging as the main source of that growth, with UBS estimating memory spending will climb from $71 billion in 2025 to $367 billion this year and $923 billion in 2027, while other AI-related costs are estimated at $631 billion in 2026 before declining to $525 billion next year. That means higher memory costs will account for about 60% of the increase in AI capex this year and more than the entire net increase in 2027, and across the two years UBS calculates that roughly 90% of the nearly $1 trillion increase in AI capital expenditure between 2025 and 2027 will come from higher memory spending. Memory represented about 14% of total AI capex in 2025, a share the bank estimates will rise to 37% this year and reach 64% in 2027, and UBS said price-driven increases would add relatively little to real U.S. gross domestic product, instead representing a transfer of income and profits toward memory producers in Asia.

Qualcomm has joined Advantech and other partners in the new WEDA edge AI ecosystem, an alliance aimed at supporting scalable deployments across varied hardware by standardising tools and reference designs for industrial and enterprise use cases. Qualcomm is also participating in up to 29 cross-sector agreements between US and Vietnamese firms announced during a recent state visit. The company develops and licenses wireless technologies that underpin mobile devices and connected equipment, and the moves tie its core wireless IP to new industrial and enterprise computing uses. Whether the WEDA ecosystem projects and Vietnam partnerships turn into disclosed design wins or revenue targets in segments like industrial IoT and AI edge devices over the next few reporting periods, rather than staying at the memorandum of understanding stage, remains to be seen.

Microchip Technology has been selected by AnalogAI to supply its memBrain SAGE neuromorphic hardware IP for use in new edge AI processors. The collaboration centers on compute-in-memory technology targeting training and inference for adaptive robots, drones and vehicles, with AnalogAI planning to integrate memBrain SAGE into real-world, low-power AI systems designed for deployment at the network edge. Microchip Technology is a US-based semiconductor supplier with a roughly $38.5b market cap focused on smart, connected and secure embedded control solutions. The design win supports the edge-computing catalyst in the company's narrative, though analysts flag execution risk from competition, including edge-AI platforms from Nvidia and Qualcomm.