April 11, 2026 • 5 min read
Tech News Roundup — April 11, 2026
NASA’s Artemis II Crew Returns Safely After Historic Lunar Mission
SPACE TECHNOLOGY
NASA’s Artemis II astronauts have splashed down safely in the Pacific Ocean, completing the first crewed mission to travel around the Moon in more than 50 years. The Orion spacecraft, built by Lockheed Martin, endured a dramatic 13-minute re-entry through Earth’s atmosphere, with exterior temperatures reaching approximately 2,760 degrees Celsius before parachutes guided it to a gentle ocean landing.
The four-person crew — NASA astronauts Reid Wiseman, Victor Glover, and Christina Koch, alongside Canadian astronaut Jeremy Hansen — launched from Kennedy Space Center on April 1 and spent ten days journeying around the Moon’s far side. The mission tested critical systems including Orion’s heat shield, navigation, and life-support technology, all essential for the planned Artemis IV lunar landing mission.
NASA chief Jared Isaacman confirmed from a US Navy recovery ship that the agency is now firmly back in the business of sending astronauts to the Moon and returning them safely, with further missions already in the pipeline.
TSMC Posts 35% Revenue Jump as AI Chip Demand Continues to Surge
HARDWARE
TSMC, the world’s largest contract chipmaker, reported first-quarter revenue of approximately $35.7 billion, a 35% increase year over year that surpassed market expectations. The figures reinforce the view that demand for AI-related semiconductors remains robust despite ongoing market debate about whether infrastructure spending might cool.
As the central manufacturer for companies producing data-centre accelerators, smartphone processors, and AI training chips, TSMC’s performance serves as a key barometer for the broader technology sector. The strong results indicate that hyperscalers and device makers continue to invest heavily in compute capacity, placing growing pressure on supply chains for packaging, memory, and power infrastructure.
Harvard AI Decoder Reduces Quantum Errors by Up to 17 Times
QUANTUM COMPUTING
A Harvard University-led study published on arXiv reports that a neural-network-based decoder named Cascade can reduce quantum computing error rates by up to 17 times while operating fast enough for real-time use. The system achieved logical error rates orders of magnitude lower than existing decoding techniques, with throughput improvements ranging from thousands to 100,000 times faster depending on configuration.
The researchers identified what they describe as a “waterfall” effect, where error rates fall much more steeply than traditional models predict as physical error rates improve. This finding suggests that practical quantum computers may require significantly fewer qubits than previously estimated, potentially accelerating the timeline for useful quantum computation across fields such as cryptography, materials science, and drug discovery.
CPUID Supply Chain Attack Serves Malware Through Popular Hardware Tools
CYBERSECURITY
The website of CPUID, developer of widely used hardware monitoring tools HWMonitor and CPU-Z, was breached by unknown attackers during the night of April 9–10. For approximately six hours, visitors downloading these tools received trojanised installers containing a fake CRYPTBASE.dll file designed to blend in with legitimate Windows components and deploy STX RAT, a remote access trojan.
The attack highlights persistent vulnerabilities in software distribution channels, even for well-established developer tools used by millions of PC enthusiasts and IT professionals. Security researchers from Cyderes and vx-underground analysed the breach and urged anyone who downloaded CPU-Z or HWMonitor during the affected window to scan their systems immediately and reinstall from verified sources.
OpenAI Signals Approach of Research-Intern-Level AI Agent Capabilities
ARTIFICIAL INTELLIGENCE
OpenAI’s chief scientist has indicated that the company is getting closer to one of its long-standing milestone goals: AI systems capable of functioning as research interns, performing complex multi-step tasks with limited supervision. The announcement comes amid a period of rapid model development, with the recent releases of GPT-5.4 and competing models from Anthropic, Google DeepMind, and Meta all pushing the boundaries of agent-style capabilities.
The development carries significant implications for knowledge work, scientific research, and software development. If achieved, research-intern-level AI agents could autonomously perform literature reviews, run experiments, and synthesise findings, dramatically accelerating workflows across academia and industry. OpenAI recently secured $122 billion in funding to support this next phase of development.
ZY Media Productions
IT • Music • Technology