Demis Hassabis Steps Down as DeepMind CEO

Demis Hassabis, co-founder of DeepMind and its former CEO, is transitioning to a newly created role as the Chair of Google DeepMind and Chief Scientist at Alphabet, as announced by Google CEO Sundar Pichai in a company memo on Wednesday. In this new capacity, Hassabis will also continue to lead Isomorphic Labs, Alphabet's drug discovery company that originated from DeepMind's research. Koray Kavukcuoglu, who previously served as DeepMind's chief technology officer, will assume the position of Senior Vice President of DeepMind, while retaining his existing role as Google's chief AI architect. Hassabis stated that his new role will enable him to "focus on the big picture and help influence what is to come," particularly in the pursuit of artificial general intelligence (AGI), which he has predicted could be achieved by 2030. Pichai emphasized the importance of this work for Alphabet and humanity, expressing confidence in Hassabis's ability to shape the future of AGI. Hassabis, a Nobel Prize laureate in chemistry, co-founded DeepMind in 2010, and the company was subsequently acquired by Google for up to $650 million. Following the widespread adoption of OpenAI's ChatGPT, Google merged its DeepMind and Google Brain divisions, the latter co-founded by Jeff Dean in 2011, into a single entity named Google DeepMind. Hassabis was appointed CEO of this merged entity, with Jeff Dean serving as its chief scientist. Jeff Dean, one of Google's earliest employees, is also departing from his leadership role. Dean, along with other senior Google colleagues, is launching Discovery Loop, a public benefit corporation focused on automating machine learning, science, and engineering. Google has committed to being a "founding investor" in this new venture. These leadership shifts occur amidst ongoing developments in AI, including the anticipated launch of Google's Gemini 3.5 Pro model, which was announced at Google I/O in May but has experienced delays, raising concerns within the industry about the pace of AI model deployment and competitive pressures.