"A lot of it was assembling together all the ingredients we already had," Hassabis said about changes Google DeepMind made. Bloomberg/Getty Images Google DeepMind's CEO said the lab merged resources…

Google DeepMind has announced the appointment of Jasjeet Sekhon as its new Chief Strategy Officer, aiming to strengthen its AI innovation and R&D efforts. Sekhon brings experience as a former professor and Chief Scientist at Bridgewater.

Ten years after his historic game against Google DeepMind’s AlphaGo transformed global perceptions of artificial intelligence, Go legend Lee Se-dol returned to the same venue. This time, the encounter was not a contest between human and machine but a demonstration of how the two might work together. The event held at the Four Seasons Hotel Seoul in central Seoul was organized by Korean AI startup Enhans, which showcased a system designed to coordinate multiple AI “agents” to carry out complex ta

Leading AI figures Satya Nadella and Demis Hassabis believe the current AI era is not the final one, anticipating one or two more major breakthroughs. While scaling current models is crucial, they suggest new architectures, improved reasoning, and memory are needed for true Artificial General Intelligence, which Hassabis estimates is still five to ten years away.

Google's AI boss Demis Hassabis said the memory market came down to "a few suppliers of a few key components." PONTUS LUNDAHL/TT NEWS AGENCY/AFP via Getty Images Google DeepMind CEO Demis Hassabis said that the "whole supply chain" for memory chips is constrained. "You need a lot of chips to be able to experiment on new ideas," Hassabis told CNBC. Google produces its own TPUs, but Hassabis said that there were still "key components" that were supply-constrained. The memory shortage takes no prisoners. Even Google isn't immune. AI companies are duking it out for greater and greater quantities of memory chips. The problem? The industry is heavily supply-constrained. Costs have skyrocketed, products have been tied up, and some companies — especially those in consumer electronics — are increasing prices. On the AI front, Google DeepMind CEO Demis Hassabis told CNBC that physical challenges were "constraining a lot of deployment." Google sees "so much more demand" for Gemini and its other models than it could serve, he said. "Also, it does constrain a little bit the research," Hassabis said. "You need a lot of chips to be able to experiment on new ideas at a big enough scale that you can actually see if they're going to work." Researchers want chips, whether they work at Google, Meta, OpenAI, or other Big Tech companies, and memory is a key component. Mark Zuckerberg said that AI researchers demanded two things beyond money: the fewest number of people reporting to them, and the most chips possible. Hassabis said that wherever there was a capacity constraint, there was a "choke point." "The whole supply chain is kind of strained," Hassabis said. "We're lucky, because we have our own TPUs, so we have our own chip designs." Google has long built TPUs — Tensor Processing Units — for internal use. The company also leases them to external customers through its cloud, which has also put Nvidia on edge. But even access to their own TPUs won't save Google from having to navigate the highly competitive memory market. "It still, in the end, actually comes down to a few suppliers of a few key components," Hassabis said. Three suppliers dominate memory chip production: Samsung, Micron, and SK Hynix. These companies are struggling to meet demand for chips from AI hyperscalers without dropping their longtime electronics customers. It doesn't help that AI companies mainly want a different type of memory chip than PC manufacturers do. Large language model producers want HBM (high-bandwidth memory) chips. Don't expect Google's spending on AI infrastructure and chips to go down anytime soon. On its fourth-quarter earnings call, the company projected capital expenditures of $175 billion to $185 billion for 2026. Read the original article on Business Insider

Leading AI companies like OpenAI, Google DeepMind, and Anthropic are focusing on advanced mathematics to demonstrate the true capabilities of their AI models.

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Google DeepMind CEO Demis Hassabis cautioned at the Athens Innovation Summit that AI must avoid repeating the toxic patterns seen in social media, highlighting concerns about its potential impact on critical thinking skills.

Google DeepMind CEO Demis Hassabis forecasts that artificial intelligence will primarily revolutionize human health and accelerate drug discovery, rather than solely focusing on job displacement.

Google DeepMind is significantly increasing its involvement in national security contracts, a shift confirmed by a VP, and has revised its AI principles to remove previous restrictions on weapons development and surveillance.

Google’s artificial intelligence program AlphaGo defeated South Korean Go master Lee Se-dol 4-1 in a five-game match in Seoul in 2016, marking a historic milestone in AI development. Developed by Google DeepMind, AlphaGo used deep neural networks and reinforcement learning, improving through self-play rather than relying solely on brute-force calculation. Given Go’s complexity and its demand for human intuition, experts had predicted such a breakthrough was still years away. The result stunned b

Alibaba Group Holding has recruited a research scientist from Google DeepMind to bolster development efforts for its Qwen artificial intelligence models, in an internal restructuring that has seen the departure of previous technical lead Lin Junyang. While no successor to Lin was announced, former Google senior staff research scientist Zhou Hao was joining Alibaba as head of post-training research, replacing Yu Bowen, who also departed this week, two sources said. Zhou, who holds a PhD from t...

Demis Hassabis, director ejecutivo de Google Deepmind, promete que la AGI está a punto de llegar, pero es un discurso con cada vez menos impacto

The CEO of Google DeepMind has issued a warning about the potential dangers associated with AI-assisted research, despite acknowledging a 'golden era' for such advancements.