Modern science advances fastest when thought meets action. LabOS represents the first AI co-scientist that unites computational reasoning with physical experimentation through multimodal perception, self-evolving agents, and Extended-Reality(XR)-enabled human-AI collaboration. By connecting multi-model AI agents, smart glasses, and robots, LabOS allows AI to see what scientists see, understand experimental context, and assist in real-time execution. Across applications -- from cancer immunotherapy target discovery to stem-cell engineering and material science -- LabOS shows that AI can move beyond computational design to participation, turning the laboratory into an intelligent, collaborative environment where human and machine discovery evolve together.

This paper introduces an innovative approach for the autonomous landing of Unmanned Aerial Vehicles (UAVs) using only a front-facing monocular camera, therefore obviating the requirement for depth estimation cameras. Drawing on the inherent human estimating process, the proposed method reframes the landing task as an optimization problem. The UAV employs variations in the visual characteristics of a specially designed lenticular circle on the landing pad, where the perceived color and form provide critical information for estimating both altitude and depth. Reinforcement learning algorithms are utilized to approximate the functions governing these estimations, enabling the UAV to ascertain ideal landing settings via training. This method's efficacy is assessed by simulations and experiments, showcasing its potential for robust and accurate autonomous landing without dependence on complex sensor setups. This research contributes to the advancement of cost-effective and efficient UAV landing solutions, paving the way for wider applicability across various fields.

Established in Pittsburgh, Pennsylvania, US -- Towards AI Co. is the world's leading AI and technology publication focused on diversity, equity, and inclusion. We aim to publish unbiased AI and technology-related articles and be an impartial source of information. We have thousands of contributing writers from university professors, researchers, graduate students, industry experts, and enthusiasts. We receive millions of visits per year, have several thousands of followers across social media, and thousands of subscribers. All of our articles are from their respective authors and may not reflect the views of Towards AI Co., its editors, or its other writers.

Established in Pittsburgh, Pennsylvania, US -- Towards AI Co. is the world's leading AI and technology publication focused on diversity, equity, and inclusion. We aim to publish unbiased AI and technology-related articles and be an impartial source of information. We have thousands of contributing writers from university professors, researchers, graduate students, industry experts, and enthusiasts. We receive millions of visits per year, have several thousands of followers across social media, and thousands of subscribers. All of our articles are from their respective authors and may not reflect the views of Towards AI Co., its editors, or its other writers.

While great thinkers like Dieter Rams and George Nelson offered their own design principles in past eras, industrial designer Yves Béhar points out that there are no comparable manifestos or guidelines for designers working with AI, robotics, and connected technology today. Last week, in a talk delivered at the inaugural A/D/O/ Design Festival in Brooklyn, Béhar presented his vision for what those guidelines should look like–in the form of 10 principles for design in the age of AI. What problem are you trying to solve with AI? Considering the multitude of "smart" products that are actually quite stupid, it's a question worth asking. "At CES there was a lot of mundane automation that is more part of what I would call gadgetry–versus automation that truly improves people's lives or delivers considerable amounts of service or value," Béhar says. "What is our intent in the world? For a company, for a product, for a service, I think it's an important question to ask ourselves."