Beep beep boop. Beep beep – boop. This could be how we’ll all talk one day if Google’s predictions about humanity’s future come true.
Well, kind of. Metro attended the tech giant’s annual developer conference, Google I/O, in Mountain View, California, last week.
To gasps from the audience – Metro included – Demis Hassabis, the CEO of Google’s AI lab, DeepMind, said: ‘When we look back at this time, I think we will realise that we were standing in the foothills of the singularity.’
But those gasps also came from Google’s product lead for science AI, Lizzie Dorfman.
Wait, what is the ‘singularity’?
The singularity is the theoretical moment when AI – that tech that currently spits out Love Island fruit videos – becomes smarter than humans.
This would open up a world where people could augment themselves with millions of times more computational power than their brains ever could.
‘That word, “singularity”, really registered with me,’ says Dorfman.
‘Singularity means, mathematically, that you spew off into infinity all of a sudden.
‘It will be the inflection point where we move into a different regime of how quickly we can do the work that would have historically taken years or even decades, now only taking months or even shorter.’
Dorfman, who has been with Google for nearly two decades, has already seen this in action.
Most science isn’t pouring colourful liquids into beakers – it’s coding tests on powerful computers, now often using AI tools.
‘What is the slowest, most laborious part of what we do? That’s what we were trying to focus on,’ she says.
‘I’ve watched scientists go, “I used to have to code this myself, and now I have this tool, I tell it what I want it to do, and then I go to sleep. When I wake up in the morning, it’s explored 1,000 different things”.’
The future is ‘exciting’ to people like Dorfman because the singularity means people could try out ’10 different things’ in a flash.
‘I think that there’s also going to be an expected fundamental shift in the productivity and outputs of science,’ she adds.
The biggest things from Google I/O
Google unveiled a raft of new shiny gadgets at its conference last week.
For the first time in 25 years, Google is overhauling its search bar – that little white box where you once typed simple things like ‘movie times’.
Soon, AI will do the Googling for you. An ‘intelligent’ search box will expand as you type and ask follow-up questions on the search page.
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These features will be powered by a new AI model, Gemini 3.5 Flash.
It will also let users build graphics when Googling complex things – when we gave it a whirl by asking how cats see, it generated an interactive diagram of a feline eye.
Gemini is even slipping into your glasses. A new model of the smart specs, Android XR, will come with a camera, a microphone and speakers, allowing people to ask Gemini about their surroundings or to order coffee online from a cafe.
When we tried out a prototype of the glasses, a Google worker spoke Spanish.
From our bespectacled POV, the glasses translated his words to English, appearing like holographic subtitles. (Said Google staffer also laughed when we gasped as it did this.)
We also saw a live demo of Wing, the delivery unit of Google’s parent company, Alphabet. These buzzy drones lowered packages filled with Google-branded badges to us on a hook.
A Google employee told us that the company wants to eventually roll out Wing in more places – it’s already being trialled in some suburbs of Ireland and as a service for NHS hospitals.
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Mapping our brain – with the help of an artificial one
As brainy as AI is right now, it would easily struggle to generate an image of a human brain.
‘I’ve asked Gemini to create an image of a brain, just to see what it looked like,’ Dorfman says. (It needed a few more wrinkles.)
But in the tech’s defence, she stresses, neither can we.
Making a map of the brain is no easy feat. It took a decade for scientists to sketch out the poppy seed-sized brain of a fruit fly, its electrical wiring and neurons stretching as large as four blue whales.
The human brain is made of billions of nerve cells alone and there are thousands of cells that we still have no clue what they do.
Dorfman says that, when you know how every part of a car engine works, you know what to do when it breaks down in the middle of the road.
So having a map of the brain could help us treat neurodegenerative diseases like Alzheimer’s and Parkinson’s, or conditions like depression.
This is why Dorfman has spent the better part of a decade working on the technology that can map things a billionth of a metre in size.
‘You fix the brain in resin to make it hard, then slice it thin – a couple of nanometres – and image it in a microscope,’ she says.
‘Our team takes all the data and structures it in three dimensions.’
Researchers want to map the 75 million neurons that make up a mouse brain next.
‘Then, one day, a human brain, which has about 80 billion neurons,’ Dorfman says.
The irony that scientists are using machines, like Gemini for Science, to understand what makes people human isn’t lost on Dorfman.
She points to a study that saw people living with epilepsy have their brains scanned while listening to a podcast.
The researchers fed the podcast to an AI, comparing how the brain hears a word to how AI processes one.
Both humans and AI ‘predicted’ the next words in similar ways – so maybe the singularity isn’t all that far off then.
‘I think there are many more opportunities that look like that,’ Dorfman adds.
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