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Demis Hassabis, who has spent much of this year saying AGI may be close, stepped down as DeepMind CEO last week.
Wait, Demis. Aren’t you supposed to be here to build AGI?
Not quite. The Nobel Prize winner isn’t leaving the AI race – he will still serve as chairman of DeepMind and chief scientist of Alphabet. He also continues to lead Isomorphic Labs, Alphabet’s subsidiary focused on accelerating drug discovery using AI.
Put simply, he’s back to tinkering with AI and science, leaving the managerial stuff – we all know what that can do to creativity – to someone else.
Other reshuffles of humans within Google point to a similar trend. Jeff Dean, Google’s 30th employee and former chief scientist, has left the company to establish Discovery Loop, a science-focused AI startup, with three other senior Google fellows.
With some of AI’s biggest brains turning their attention to science, you could argue that chatbots have passed their novelty phase. Using AI for scientific discovery isn’t new, but whether it can become a viable business remains unproven.
Hypotheses alone won’t cut it. The test is whether AI systems can reduce the number of experiments, shorten development cycles, and produce discoveries that make it beyond the lab – the ChatGPT moment, if you will, but for science.
Image credit: Made by Ulla/Tech in Asia with the help of AI
If science represents AI’s long-term ambition, wearables represent its most immediate commercial opportunity. AI glasses, AI headphones, AI watches – you name it – these things are here already, but as my colleague Melissa reported in this piece, they still need a good reason to exist.
At least one player believes AI glasses will replace smartphones in the future. Others, like Razer, believe headphones are the more ideal form factor. We’ll see how that goes over the next couple of years, as even Apple is reportedly working on both AI glasses and earphones.
I also wrote an opinion piece examining ByteDance’s reverse cloud strategy, anchoring on one hit AI model. Its video generation model Seedance has attracted enterprise demand, but converting that into a wider customer relationship is a different story.
Whether in laboratories, on our faces, or inside the enterprise tech stack, AI is running into the same test: turning an initial breakthrough or burst of demand into something people keep using – and paying for.
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