Google is shaking up the leadership of its consumer AI apps as the focus of the AI race shifts from the underlying models to the products built around them, according to memos reviewed by Semafor. Sissie Hsiao, who led Google’s effort to create an AI chatbot, originally called Bard and now dubbed Gemini, will step down immediately. Josh Woodward, who leads Google Labs and oversaw the launch of NotebookLM, the company’s popular tool that turns text into a podcast-like show, will replace her. Google/YouTubeIn a memo to the staff, Google DeepMind CEO Demis Hassabis said the move will “sharpen our focus on the next evolution of the Gemini app.” He said Woodward will remain head of Google Labs while shaping the next chapter of Gemini. Hsiao, in a separate staff memo, called her time as head of the team “chapter 1” of the Bard story, and said she was optimistic in handing the baton to Woodward for “chapter 2.” Hsiao plans to take a “short break” and return to Google in a new role. Hsiao, Woodward, and Hassabis declined to comment through a spokesperson. Hsiao, a 19-year veteran of Google, jumped into action after ChatGPT upended the tech industry, forcing Google to accelerate the rollout of AI technology it had created. While Google researchers had pioneered the transformer-based architecture that allowed the creation of large language models that powered ChatGPT, its unpredictable nature led the company to keep its chatbot experiments mostly under wraps. In the competitive rush, mishaps illustrated why. The launch of Bard was criticized for “hallucinations,” and its Gemini image creation tool became a target of conservatives when it generated embarrassing results, inserting photos of women or people of color when prompted to create images of Vikings, Nazis, and the Pope. But Google quickly moved past those early errors with successful product launches. Last week, Gemini 2.5 blew away AI benchmarks held by competitors like OpenAI and Anthropic. It took the lead in Chatbot Arena, where users vote on their favorite large language model responses. |