CES 2026 showed that humanoid and embodied AI systems still have a long way to go before delivering real-world value, particularly in homes. At the same time, there is a growing sense that the path to deployment is becoming clearer. A consensus has emerged across platforms: multi-camera perception, often wrist-mounted, paired with VLA models, is sufficient for most tasks. Increasingly, tactile hands and VTLA software are added. There was a clear split between industrial and home-care humanoids.

What could possibly go wrong? The 4-foot-tall humanoid robot that's in front of me seems, quite honestly, a bit drunk. After 30 seconds or so it abruptly stops, then strides toward me with an arm outstretched. The little robot is at the World Artificial Intelligence Conference, on the banks of the Huangpu river in Shanghai. The convention center is teeming with humanoids --dancing ones, box-toting ones, robot dog-walking ones doing circuits around trade show booths. A few lie slumped in a corner as their batteries recharge. A Unitree humanoid robot modified for experimental purposes at the BAAI.

CES always has its share of attention-grabbing robots. But this year in particular seemed to be a landmark year for robotics. The advancement in AI technology has not only given robots better "brains," it's enabled new levels of autonomy and given rise to an ambitious, if sometimes questionable, vision for our robot-filled future. From sassy humanoids to AI-powered pets and chore-handling assistants, we sought out as many cute, strange and capable robots as we could find in Las Vegas. These are the ones that made the biggest impression.

Sharpa's ping-pong playing, blackjack dealing humanoid is working overtime at CES 2026 The company's super dexterous robotic hand, SharpaWave, allows it to pull individual playing cards from a deck. There were no idle hands at Sharpa's CES booth. The company's humanoid may have been the busiest bot at show, autonomously playing ping-pong, dealing blackjack games and taking selfies with passersby. The hand has 22 active degrees of freedom, according to the company, allowing for precise and intricate finger movements. It mirrored my gestures as I wiggled my hand in front of its camera, getting everything mostly right, which was honestly pretty cool.

We tackle the challenges of synthesizing versatile, physically simulated human motions for full-body object manipulation. Unlike prior methods that are focused on detailed motion tracking, trajectory following, or teleoperation, our framework enables users to specify versatile high-level objectives such as target object poses or body poses. To achieve this, we introduce MaskedManipulator, a generative control policy distilled from a tracking controller trained on large-scale human motion capture data. This two-stage learning process allows the system to perform complex interaction behaviors, while providing intuitive user control over both character and object motions. MaskedManipulator produces goal-directed manipulation behaviors that expand the scope of interactive animation systems beyond task-specific solutions.

The development of athletic humanoid robots has gained significant attention as advances in actuation, sensing, and control enable increasingly dynamic, real-world capabilities. RoboCup, an international competition of fully autonomous humanoid robots, provides a uniquely challenging benchmark for such systems, culminating in the long-term goal of competing against human soccer players by 2050. This paper presents the hardware and software innovations underlying our team's victory in the RoboCup 2024 Adult-Sized Humanoid Soccer Competition. On the hardware side, we introduce an adult-sized humanoid platform built with lightweight structural components, high-torque quasi-direct-drive actuators, and a specialized foot design that enables powerful in-gait kicks while preserving locomotion robustness. On the software side, we develop an integrated perception and localization framework that combines stereo vision, object detection, and landmark-based fusion to provide reliable estimates of the ball, goals, teammates, and opponents. A mid-level navigation stack then generates collision-aware, dynamically feasible trajectories, while a centralized behavior manager coordinates high-level decision making, role selection, and kick execution based on the evolving game state. The seamless integration of these subsystems results in fast, precise, and tactically effective gameplay, enabling robust performance under the dynamic and adversarial conditions of real matches. This paper presents the design principles, system architecture, and experimental results that contributed to ARTEMIS's success as the 2024 Adult-Sized Humanoid Soccer champion.