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New approach uses generative AI to imitate human motion

An international group of researchers has created a new approach to imitating human motion by combining central pattern generators (CPGs) and deep reinforcement learning (DRL). The method not only imitates walking and running motions but also generates movements for frequencies where motion data is absent, enables smooth transition movements from walking to running, and allows for adaptation to environments with unstable surfaces.

Cloud Security is Broken: SentinelOne Aims to Fix It

Cloud security traditionally revolves around detection rather than protection. SentinelOne intends to change that by introducing a potentially game-changing solution—Singularity Cloud Native Security. This new offering moves the needle towards proactive, offensive measures that aim to protect as much as […]

The post Cloud Security is Broken: SentinelOne Aims to Fix It appeared first on TechSpective.

Teaching robots to move by sketching trajectories

Getting robots to perform even a simple task requires a great deal of behind-the-scenes work. Part of the challenge is planning and executing movements, everything from turning wheels to lifting a robotic arm. To make this happen, roboticists collaborate with programmers to develop a set of trajectories—or pathways—that are clear of obstacles and doable for the robot.
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