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After setting a new world speed record for humanoid robots earlier this month, China’s Unitree is now claiming another. Its latest H1 bipedal takes the title for first to perform a standing backflip without the use of hydraulics.

Yes, humanoids like Boston Dynamics’ Atlas have been nailing backflips for a few years now but they make use of heavy, potentially leaky hydraulics to launch into the air, somersault backwards and then land on both feet.

Impressively, Unitree’s H1 relies on in-house M107 electric joint motors only, each of which boasts 360 Nm (265.5 lb.ft) of peak torque and can also be found on the company’s B2 quadruped. Each leg has three degrees of freedom at the hip plus one at the knee and another at the ankle, and all cabling is routed internally for snag-free clean lines.

Indoor positioning is transforming with applications demanding precise location tracking. Traditional methods, including fingerprinting and sensor-based techniques, though widely used, face significant drawbacks, such as the need for extensive training data, poor scalability, and reliance on additional sensor information. Recent advancements have sought to leverage deep learning, yet issues such as low scalability and high computational costs remain unaddressed.

The software development sector stands at the dawn of a transformation powered by artificial intelligence (AI), where AI agents perform development tasks. This transformation is not just about incremental enhancements but a radical reimagining of how software engineering tasks are approached, executed, and delivered. Central to this shift is introducing AI-driven frameworks that transcend traditional code assistance tools, marking a leap toward more autonomous, efficient, and secure software development methodologies.

The integration of AI in software development has been confined largely to providing code suggestions and aiding in file manipulation. This approach, while beneficial, barely scratches the surface of what is technologically feasible. AI-powered tools operate within a constrained scope, missing out on Integrated Development Environments (IDEs)’ vast capabilities, such as comprehensive code building, testing, and version control operations. This limitation underscores a critical gap in the software development toolkit, where the potential for AI to contribute more profoundly to the development lifecycle remains largely untapped.

Microsoft researchers present AutoDev, which empowers AI agents to tackle a broad spectrum of software engineering tasks autonomously, from intricate code editing and comprehensive testing to advanced git operations. This framework is designed to focus on autonomy, efficiency, and security. By housing operations within Docker containers, AutoDev ensures that development processes are streamlined and secure, safeguarding user privacy and project integrity through meticulously designed guardrails.