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Read full article about: Google Deepmind launches interdisciplinary institute to tackle the big questions around AGI

Google Deepmind has founded the Deepmind Institute (DMI), a platform for interdisciplinary research and debate around artificial general intelligence (AGI). The institute brings together researchers from Google Deepmind, Google, and the global scientific community to tackle questions about safety, governance, and risks like cyberattacks or loss of control. The answers shouldn't come from technologists alone but also from the arts, humanities, and policy, according to directors Shane Legg, James Manyika, and Nobel laureate Demis Hassabis.

There's no agreed-upon definition of AGI. Deepmind describes it as a system with all the cognitive abilities of the human brain and says AGI is close, even though today's AI systems still fail at simple tasks and lack creativity. Hassabis sees it coming within a few years, Legg recently said a precursor could arrive by 2028. OpenAI focuses on economic value, and CEO Altman believes AGI could come by year's end. AGI shouldn't be confused with "ASI", an artificial superintelligence that would far surpass humans in every respect, though AGI is likely a necessary step toward it.

Read full article about: Former Deepmind PR staffer says the lab once banned public discussion of AI extinction risk

Not surprising, but still telling. Vishal Maini, who worked on Deepmind's communications and policy team from 2018 to 2022, says "external communication about the possibility of human extinction was not permitted, by anyone, at any level of the organization." Researchers were coached to dismiss those risks as alarmism, compare them to "movies like Terminator," and pivot to positive applications in healthcare or climate instead.

Internally, the team knew the AI alignment problem was not solved and "there were far too few people working on the problem." After months of pushing back, Deepmind loosened the rule. Positively framed safety content got the green light, including a blog post that wrapped extinction risk in friendly language. Maini says the gap between internal knowledge and public messaging is shrinking "because the evidence is harder to dismiss now."

His account comes as a growing number of AI safety researchers are speaking out publicly, warning about unsecured models that could enable dangerous actions or advanced systems that could slip beyond human control. Researchers at Deepmind itself are among those raising their voices.

Google's DiffusionGemma proves you don't need to train from scratch to build a text diffusion model

Instead of training a new model from scratch, Google DeepMind retrofitted Gemma 4 into a diffusion model using less than 10 percent of the original training budget. DiffusionGemma generates 256 tokens in parallel instead of one at a time, hitting about 1,500 tokens per second. Quality still trails the original autoregressive model in benchmarks, especially on reasoning tasks.

Read full article about: Deepmind's talent drain likely comes down to chip shortages, a conflict of interest, and Google's bureaucracy

As prominent AI researchers continue to leave Google DeepMind, details about the reasons behind the departures are starting to emerge. Semafor reports that CEO Demis Hassabis stepped back from daily operations about a year ago and turned those duties over to new DeepMind chief Koray Kavukcuoglu. Hassabis wasn't forced out but reportedly found management unfulfilling and sees himself more as a visionary scientist than an executive.

CNBC reports that many researchers are frustrated by limited access to Google's TPU chips. At the same time, Google Cloud sells those chips to rivals like Anthropic, the very competitors Google's own researchers are expected to beat. Google allocates computing capacity years in advance among research teams, product operations, and cloud customers, but priorities can shift with little notice, a source told CNBC. Google's bureaucracy also reportedly makes younger companies more appealing.

As if to prove the point, Google announced today that "exciting frontier AI lab" Mirendil will use more than $100 million worth of TPUs and Nvidia GPUs through a Google Cloud partnership.

Deepmind CEO Hassabis says "nobody in the world knows what happens next" so "cautious optimism" means building guardrails now

Google Deepmind CEO Demis Hassabis has published a sweeping proposal for how to handle advanced AI. He wants a new US standards body modeled after financial regulator FINRA that would develop evaluation protocols for frontier models and could coordinate a slowdown in AI development if needed. Startups and research models would be exempt.

Google Deepmind treats its own AI agents like rogue employees with office keys

Google Deepmind treats its own AI agents as potential insider threats. The company’s new “AI Control Roadmap” ties security measures to measurable AI capabilities, and an analysis of one million coding tasks shows most problems stem from overzealous agents, not malicious intent. Deepmind warns the window for global security standards is closing fast.