What’s New Today: Alibaba has introduced its new AI chip, Zhenwu M890, to reduce reliance on Nvidia, while UK startup Imperagen has raised $5 million to speed up enzyme development using quantum computing and AI.
Fast-Track Insights: Army Public School Recruitment 2026 has opened teaching vacancies across India, and AI coding tools are moving toward goal-driven systems that can handle coding tasks with less manual input.
Here’s a quick roundup of the biggest headlines making waves today. Let’s dive into the top stories, from AI chips and quantum computing to teaching jobs, coding automation, and Bitcoin security risks.
Alibaba introduced its new AI chip, Zhenwu M890, as China pushes to reduce reliance on Nvidia amid tighter US export limits. The company said the chip is three times stronger than its earlier version and can handle advanced AI tasks more smoothly. Alibaba also shared future chip plans and new AI software upgrades. The move is part of its broader investment in AI and cloud technology to drive long-term growth.
UK-based startup Imperagen has raised $5 million in seed funding to improve enzyme development using quantum computing and AI. The company aims to accelerate drug discovery and reduce the time required to design enzymes for medicines and industrial applications. Its platform combines machine learning with quantum methods to study complex biological systems more accurately. The funding will support team growth, research work, and product development.
Army Public School Recruitment 2026 has announced openings for PGT, TGT, and PRT posts in different schools across India. The recruitment drive is for the 2026–27 academic session. Prospective candidates can apply according to the qualifications mentioned in the notification itself. The selection process will primarily involve interviews and document verification. For anyone who’s actually interested, key details are there in the official notice.
AI coding tools are slowly shifting from prompt-based systems to goal-driven agents. Instead of asking for every step, users may only need to give a final goal. These agents can plan tasks, write code, test results, fix errors, and improve output independently. The change could reduce manual coding work and help developers focus more on ideas, design, and problem-solving rather than writing every line of code.
Glassnode said around 1.92 million Bitcoin are structurally exposed to future quantum computing risks. Another 4.12 million BTC are at operational risk due to address reuse and wallet practices. In total, over 30% of Bitcoin’s issued supply may be vulnerable if quantum systems become powerful enough. The report added that better wallet management and post-quantum security upgrades could reduce part of the risk over time.