Microsoft CEO Satya Nadella laid out how the company is scaling its AI infrastructure and platform to keep pace with demand. He outlined these plans during an earnings call on July 29, when he also announced record revenue above US$331 billion for fiscal year 2026 (ending on June 30), with Microsoft Cloud earnings surpassing US$214 billion and Azure earnings surpassing US$100 billion.
Italy and the US are set to sign a cooperation agreement tied to the US-led Pax Silica initiative on July 31, as Rome expands efforts to secure critical raw materials and semiconductor supply chains.
Meta Platforms' second-quarter results showed a widening gap between its fast-growing advertising business and the cost of building AI infrastructure. Free cash flow fell to US$784 million, while the company lifted the lower end of its 2026 capital expenditure forecast to US$130 billion.
Microsoft reported stronger-than-expected fiscal fourth-quarter results, driven by accelerating Azure cloud growth and rising adoption of its AI products, reinforcing investor confidence that the company's heavy investments in AI are generating commercial returns. Robust guidance for the current quarter and continued enterprise demand also eased concerns over spending on AI infrastructure.
Global automakers are facing slower market growth, the rapid rise of Chinese carmakers, and sustained EV investment, with Volkswagen, BMW, and Mercedes-Benz under strain in recent years. While German automakers still lead the global auto industry, revenue and profitability have come under broad pressure over the past two years as competition shifts from volume growth to product value and operating efficiency.
Artificial intelligence is rapidly expanding the capabilities of robotics. Yet while industrial robots have become commonplace on factory floors, service robots operating alongside people in hospitals, homes and other public environments still lack widely accepted benchmarks for real-world performance.
The robotics industry is moving from AI demonstrations to commercial deployments as vendors push Physical AI into factories, logistics, retail, food service and homes. The shift centers on whether robots can be built as repeatable products that customers will buy, rather than as machines that simply walk, recognize environments or follow commands.
While humanoid robots have yet to achieve meaningful economies of scale, service robots have already entered an intensely competitive phase.
A Taiwan startup says it has found a way to hide advanced eye-tracking technology inside what looks like an ordinary pair of glasses — using just one camera and a single LED light source.
Aewin Technologies has introduced a four-product server lineup built around AMD's newly launched EPYC 9006 processor family, targeting AI, general-purpose computing and storage workloads. The launch comes as demand for server architectures continues to fragment across training, inference, enterprise IT and data storage use cases.
Nvidia CEO Jensen Huang once again voiced his support for open-weight and open-source AI, a form of model that has caught official attention in Washington after the release of the powerful Kimi K3 model from Chinese startup Moonshot AI. His comments added another voice to the ongoing debate over closed-source versus open-source approaches as the US considers restrictions on Chinese AI.
