Why the World's Best AI Systems Are Still So Bad at Pokémon Pillay is an editorial fellow at TIME. Pillay is an editorial fellow at TIME. Right now, live on Twitch, you can watch three of the world's smartest AI systems-- GPT 5.2, Claude Opus 4.5, and Gemini 3 Pro --doing their best to beat classic Pokémon games. At least by human standards, they are not very good. The systems are slow, overconfident, and often confused.

By how much, if at all, will AI boost the U.S. economy? New research by Anthropic, seen exclusively by TIME in advance of its release today, offers at least a partial answer to that question. By studying aggregated data about how people use Claude in the course of their work, Anthropic researchers came up with an estimate for how much AI could contribute to annual labor productivity growth--an important contributor to the total level of growth in the overall economy--as the technology becomes more widely used. Their answer: current-generation AI models could increase the U.S. annual labor productivity growth rate by 1.8%--doubling the average rate of growth since 2019. Assuming that labor makes up 60% of total productivity in the economy, and that AI reaches full diffusion in a decade's time, "this implies an overall total factor productivity increase of 1.1% per year," the researchers write.

Welcome back to, TIME's new twice-weekly newsletter about AI. If you're reading this in your browser, why not subscribe to have the next one delivered straight to your inbox? What to Know: Testing LLMs' ability to control a robot A couple of weeks ago, I wrote in this newsletter about my visit to Figure AI, a California startup that has developed a humanoid robot. Billions of dollars are currently pouring into the robotics industry, based on the belief that rapid AI progress will mean the creation of robots with "brains" that can finally deal with the messy complexities of the real world. Today, I want to tell you about an experiment that calls that theory into question.