Portugal's National Health Service has entered into an agreement with digital health firm Sword Health to implement AI-assisted virtual physical therapy across the country, aiming to enhance patient care and accessibility.

Clive Meanwell, chairman of Population Health Partners, once skeptical about AI, now views it as a powerful catalyst in advancing biotechnologies designed for improving population health.

Germany is advancing its capabilities in air warfare by commissioning the Munich-based AI company, Helsing, to develop a central software system. This high-tech program, backed by a €580 million contract, aims to integrate fighters, drones, satellites, and sensors into a cohesive network. The initiative represents a significant effort to modernize Europe’s defense technology, as revealed in documents obtained by Politico.

Uber announced it is planning to launch a new autonomous vehicle partnership in Phoenix, without revealing the identity of its new partner. This development follows the quiet end of its previous collaboration with Waymo in the city.

Investor Chamath Palihapitiya’s new AI coding startup has attracted significant interest, raising $135 million in its Series A funding round. This move highlights the strong appetite among venture capitalists for innovative AI-driven coding solutions.

The second quarter of 2026 has marked the highest number of billion-dollar startup exits since 2021, according to Crunchbase data. This period featured the largest venture-backed exit ever with SpaceX's historic IPO, which raised about $75 billion and achieved a $2.1 trillion market cap on the first day. Alongside SpaceX, several other startups made significant exits through acquisitions and IPOs, including Cursor’s $60 billion acquisition by SpaceX, Cerebras Systems’ $5.55 billion IPO, and Quantinuum raising $1.7 billion in its Nasdaq debut. While the total number of big exits remains below the peak seen during the IPO and SPAC boom five years ago, the size and value of these deals are notably larger. This trend suggests that although fewer billion-dollar exits are happening, their magnitude and impact are growing, with upcoming IPOs from Anthropic and OpenAI expected to further reshape the market.

China's Zhipu AI (Z.ai) has launched its latest open-weight model, GLM-5.2, which some experts believe matches the capabilities of Mythos in specific bug detection and cybersecurity tasks. Though GLM-5.2 trails behind models from Anthropic and OpenAI in more generalized functions, this development signals a significant narrowing of the technology gap between Chinese AI models and their American counterparts. This rapid advancement has raised concerns within the US government, which has imposed restrictions on China's access to advanced AI models like Mythos and Fable, as well as the technology needed for their development. The issue highlights the broader geopolitical tensions in AI innovation and security.

Firmus Technologies, an Australian AI infrastructure firm valued at $5.5 billion, is set to establish its inaugural data centre in Indonesia through an eight-year collaboration with Nvidia. The new 360-megawatt Nvidia DSX AI Factory campus will be located in Batam, near Singapore, and developed alongside Singapore's DayOne. This facility aims to enhance AI capabilities and is expected to commence operations soon.

Ford initially believed that simply implementing artificial intelligence would automatically result in a superior product. However, this expectation proved mistaken, leading the company to rehire experienced, senior engineers—referred to as 'gray beards'—to ensure quality and reliability in their work.

Anthropic's growth team was recently advised to hire more product managers to keep pace with a significant shift caused by Claude Code, which has essentially tripled engineering productivity. The bottleneck in software development has shifted from coding speed to deciding what to build, necessitating a deeper product focus within engineering teams.

Historically, engineers followed a linear process: learning deeply about technology, writing code, and escalating issues as needed, while product managers managed the project funnel. This traditional division is now outdated as recent innovations compressed and transformed the engineering workflow through several eras—from relying on Stack Overflow to AI-enabled IDEs and spec-driven development.

Today, engineers produce code faster than ever, but the need for clear product direction and decision-making has intensified. Companies like LinkedIn and Anthropic are adapting by blending product management skills with engineering roles.

Fundamental technical skills remain critical in verifying and reviewing AI-generated code to prevent costly mistakes. Furthermore, successful engineers now engage directly with product funnels—interacting with customers, understanding use cases firsthand, and proactively contributing to idea generation and prioritization.

The future rewards engineers who can identify valuable projects, validate them, and manage rapid delivery through AI-assisted workflows. Those who rely solely on traditional tickets risk being left behind.