Carolina Parada
Senior Director and Head of Robotics at Google DeepMind, where she leads work on Gemini Robotics, embodied intelligence, robot mobility, robot vision, and safe autonomous robots in human-centered environments.
Robotics Still Lacks Its ChatGPT Moment
Google DeepMind’s head of robotics, Carolina Parada, says recent advances in language and vision models have moved robots beyond treating their surroundings as meaningless coordinates toward understanding instructions, environments and tasks. But she argues robotics has not yet reached its “ChatGPT moment”: a system that can reliably respond to a person’s request in an unfamiliar setting. Humanoids may help deploy such intelligence in spaces built for people, she says, though many tasks will call for other robot forms.
AI Infrastructure Spending Is Driving Valuations Across Tech Markets
Tech investors are pricing not only AI models but the infrastructure, financing and execution needed to turn heavy spending into returns, according to Bloomberg Technology’s May 29 coverage. The program tied Dell’s raised outlook and AI server forecast, Anthropic’s reported $965 billion valuation and private-credit financing, and SpaceX’s lower reported $1.8 trillion IPO target to a broader question of whether demand can become durable revenue and profit. Its SpaceX segment framed the revised target as a test of investor willingness to underwrite Elon Musk’s operating record and ambitions at valuation multiples far beyond current sales.
Dexterity, AI, and Cost Still Separate Humanoids From Mass Adoption
Bloomberg Tech: Asia’s Humanoid Summit segment presents humanoid robotics as an industry trying to move from demonstrations to deployment, with forecasts far ahead of current adoption. Shery Ahn’s interviews with Google DeepMind’s Carolina Parada, Honda’s Takahide Yoshiike and Bloomberg Intelligence’s Ian Ma frame the central test as whether humanoids can become useful, safe and affordable machines rather than theatrical prototypes. Their arguments converge on the same bottlenecks: embodied AI, dexterous manipulation, cost, standards and a business model that can support scale.