In the last few months Baker’s team has been working with biologists who were previously stuck trying to figure out the shape of proteins they were studying. “There’s a lot of pretty cool biological research that’s been really sped up,” he says. A public database containing hundreds of thousands of ready-made protein shapes should be an even bigger accelerator.
“It looks astonishingly impressive,” says Tom Ellis, a synthetic biologist at Imperial College London studying the yeast genome, who is excited to try the database. But he cautions that most of the predicted shapes have not yet been verified in the lab.
In the new version of AlphaFold, predictions come with a confidence score that the tool uses to flag how close it thinks each predicted shape is to the real thing. Using this measure, DeepMind found that AlphaFold predicted shapes for 36% of human proteins with an accuracy that is correct down to the level of individual atoms. This is good enough for drug development, says Hassabis.
Previously, after decades of work, only 17% of the proteins in the human body have had their structures identified in the lab. If AlphaFold’s predictions are as accurate as DeepMind says, the tool has more than doubled this number in just a few weeks.
Even predictions that are not fully accurate at the atomic level are still useful. For more than half of the proteins in the human body, AlphaFold has predicted a shape that should be good enough for researchers to figure out the protein’s function. The rest of AlphaFold’s current predictions are either incorrect, or are for the third of proteins in the human body that don’t have a structure at all until they bind with others. “They’re floppy,” says Hassabis.
“The fact that it can be applied at this level of quality is an impressive thing,” says Mohammed AlQuraish, a systems biologist at Columbia University who has developed his own software for predicting protein structure. He also points out that having structures for most of the proteins in an organism will make it possible to study how these proteins work as a system, not just in isolation. “That’s what I think is most exciting,” he says.
DeepMind is releasing its tools and predictions for free and will not say if it has plans for making money from them in future. It is not ruling out the possibility, however. To set up and run the database, DeepMind is partnering with the European Molecular Biology Laboratory, an international research institution that already hosts a large database of protein information.
For now, AlQuraishi can’t wait to see what researchers do with the new data. “It’s pretty spectacular,” he says “I don’t think any of us thought we would be here this quickly. It’s mind boggling.”
Yann LeCun has a bold new vision for the future of AI
Melanie Mitchell, an AI researcher at the Santa Fe Institute, is also excited to see a whole new approach. “We really haven’t seen this coming out of the deep-learning community so much,” she says. She also agrees with LeCun that large language models cannot be the whole story. “They lack memory and internal models of the world that are actually really important,” she says.
Natasha Jaques, a researcher at Google Brain, thinks that language models should still play a role, however. It’s odd for language to be entirely missing from LeCun’s proposals, she says: “We know that large language models are super effective and bake in a bunch of human knowledge.”
Jaques, who works on ways to get AIs to share information and abilities with each other, points out that humans don’t have to have direct experience of something to learn about it. We can change our behavior simply by being told something, such as not to touch a hot pan. “How do I update this world model that Yann is proposing if I don’t have language?” she asks.
There’s another issue, too. If they were to work, LeCun’s ideas would create a powerful technology that could be as transformative as the internet. And yet his proposal doesn’t discuss how his model’s behavior and motivations would be controlled, or who would control them. This is a weird omission, says Abhishek Gupta, the founder of the Montreal AI Ethics Institute and a responsible-AI expert at Boston Consulting Group.
“We should think more about what it takes for AI to function well in a society, and that requires thinking about ethical behavior, amongst other things,” says Gupta.
Yet Jaques notes that LeCun’s proposals are still very much ideas rather than practical applications. Mitchell says the same: “There’s certainly little risk of this becoming a human-level intelligence anytime soon.”
LeCun would agree. His aim is to sow the seeds of a new approach in the hope that others build on it. “This is something that is going to take a lot of effort from a lot of people,” he says. “I’m putting this out there because I think ultimately this is the way to go.” If nothing else, he wants to convince people that large language models and reinforcement learning are not the only ways forward.
“I hate to see people wasting their time,” he says.
The Download: Yann LeCun’s AI vision, and smart cities’ unfulfilled promises
“We’re addicted to being on Facebook.”
—Jordi Berbera, who runs a pizza stand in Mexico City, tells Rest of World why he has turned to selling his wares through the social network instead of through more conventional food delivery apps.
The big story
“Am I going crazy or am I being stalked?” Inside the disturbing online world of gangstalking
Jenny’s story is not linear, the way that we like stories to be. She was born in Baltimore in 1975 and had a happy, healthy childhood—her younger brother Danny fondly recalls the treasure hunts she would orchestrate. In her late teens, she developed anorexia and depression and was hospitalized for a month. Despite her struggles, she graduated high school and was accepted into a prestigious liberal arts college.
There, things went downhill again. Among other issues, chronic fatigue led her to drop out. When she was 25 she flipped that car on Florida’s Sunshine Skyway Bridge in an apparent suicide attempt. At 30, after experiencing delusions that she was pregnant, she was diagnosed with schizophrenia. She was hospitalized for half a year and began treatment, regularly receiving shots of an antipsychotic drug. “It was like having my older sister back again,” Danny says.
On July 17, 2017, Jenny jumped from the tenth floor of a parking garage at Tampa International Airport. After her death, her family searched her hotel room and her apartment, but the 42-year-old didn’t leave a note. “We wanted to find a reason for why she did this,” Danny says. And so, a week after his sister’s death, Danny—a certified ethical hacker—decided to look for answers on Jenny’s computer. He found she had subscribed to hundreds of gangstalking groups across Facebook, Twitter, and Reddit; online communities where self-described “targeted individuals” say they are being monitored, harassed, and stalked 24/7 by governments and other organizations—and the internet legitimizes them. Read the full story.
The US Supreme Court has overturned Roe v. Wade. What does that mean?
Access to legal abortion is now subject to state laws, allowing each state to decide whether to ban, restrict or allow abortion. Some parts of the country are much stricter than others—Arkansas, Oklahoma and Kentucky are among the 13 states with trigger laws that immediately made abortion illegal in the aftermath of the ruling. In total, around half of states are likely to either ban or limit access to the procedure, with many of them refusing to make exceptions, even in pregnancies involving rape, incest and fetuses with genetic abnormalities. Many specialized abortion clinics may be forced to close their doors in the next few days and weeks.
While overturning Roe v Wade will not spell an end to abortion in the US, it’s likely to lower its rates, and force those seeking them to obtain them using different methods. People living in states that ban or heavily restrict abortions may consider travelling to other areas that will continue to allow them, although crossing state lines can be time-consuming and prohibitively expensive for many people facing financial hardship.
The likelihood that anti-abortion activists will use surveillance and data collection to track and identify people seeking abortions is also higher following the decision. This information could be used to criminalize them, making it particularly dangerous for those leaving home to cross state lines.
Vigilante volunteers already stake out abortion clinics in states including Mississippi, Florida and North Carolina, filming people’s arrival on cameras and recording details about them and their cars. While they deny the data is used to harass or contact people seeking abortions, experts are concerned that footage filmed of clients arriving and leaving clinics could be exploited to target and harm them, particularly if law enforcement agencies or private groups were to use facial recognition to identify them.
Another option is to order so-called abortion pills to discreetly end a pregnancy at home. The pills, which are safe and widely prescribed by doctors, are significantly less expensive than surgical procedures, and already account for the majority of abortions in the US.