According to AI News on X, humanoid robots in 2026 are demonstrating two notable advances: Sharpa Wave robotic hands featuring 22 degrees of freedom and over 1,000 tactile sensors per fingertip are shown assembling PC components and peeling apples, indicating significant gains in dexterous manipulation and fine force control; and real-time humanoid tennis rallies trained via latent learning from imperfect human motion data, suggesting robust imitation learning that tolerates noisy datasets and enables high-speed, closed-loop control (source: AI News post linking to YouTube demo). As reported by AI News, these demos point to near-term business opportunities in electronics assembly, delicate food handling, and sports robotics training systems, where high-DoF tactile manipulation and resilient policy learning can reduce labor costs and expand automation to unstructured tasks.