How DeepMind thinks it can make chatbots safer
Some technologists hope that one day we will develop a superintelligent AI system that people will be able to have conversations with. Ask it a question, and it will offer an answer that sounds like something composed by a human expert. You could use it to ask for medical advice, or to help plan a holiday. Well, that’s the idea, at least.
In reality, we’re still a long way away from that. Even the most sophisticated systems of today are pretty dumb. I once got Meta’s AI chatbot BlenderBot to tell me that a prominent Dutch politician was a terrorist. In experiments where AI-powered chatbots were used to offer medical advice, they told pretend patients to kill themselves. Doesn’t fill you with a lot of optimism, does it?
That’s why AI labs are working hard to make their conversational AIs safer and more helpful before turning them loose in the real world. I just published a story about Alphabet-owned AI lab DeepMind’s latest effort: a new chatbot called Sparrow.
DeepMind’s new trick to making a good AI-powered chatbot was to have humans tell it how to behave—and force it to back up its claims using Google search. Human participants were then asked to evaluate how plausible the AI system’s answers were. The idea is to keep training the AI using dialogue between humans and machines.
In reporting the story, I spoke to Sara Hooker, who leads Cohere for AI, a nonprofit AI research lab.
She told me that one of the biggest hurdles in safely deploying conversational AI systems is their brittleness, meaning they perform brilliantly until they are taken to unfamiliar territory, which makes them behave unpredictably.
“It is also a difficult problem to solve because any two people might disagree on whether a conversation is inappropriate. And even if we agree that something is appropriate right now, this may change over time, or rely on shared context that can be subjective,” Hooker says.
Despite that, DeepMind’s findings underline that AI safety is not just a technical fix. You need humans in the loop.
IBM wants to build a 100,000-qubit quantum computer
Quantum computing holds and processes information in a way that exploits the unique properties of fundamental particles: electrons, atoms, and small molecules can exist in multiple energy states at once, a phenomenon known as superposition, and the states of particles can become linked, or entangled, with one another. This means that information can be encoded and manipulated in novel ways, opening the door to a swath of classically impossible computing tasks.
As yet, quantum computers have not achieved anything useful that standard supercomputers cannot do. That is largely because they haven’t had enough qubits and because the systems are easily disrupted by tiny perturbations in their environment that physicists call noise.
Researchers have been exploring ways to make do with noisy systems, but many expect that quantum systems will have to scale up significantly to be truly useful, so that they can devote a large fraction of their qubits to correcting the errors induced by noise.
IBM is not the first to aim big. Google has said it is targeting a million qubits by the end of the decade, though error correction means only 10,000 will be available for computations. Maryland-based IonQ is aiming to have 1,024 “logical qubits,” each of which will be formed from an error-correcting circuit of 13 physical qubits, performing computations by 2028. Palo Alto–based PsiQuantum, like Google, is also aiming to build a million-qubit quantum computer, but it has not revealed its time scale or its error-correction requirements.
Because of those requirements, citing the number of physical qubits is something of a red herring—the particulars of how they are built, which affect factors such as their resilience to noise and their ease of operation, are crucially important. The companies involved usually offer additional measures of performance, such as “quantum volume” and the number of “algorithmic qubits.” In the next decade advances in error correction, qubit performance, and software-led error “mitigation,” as well as the major distinctions between different types of qubits, will make this race especially tricky to follow.
Refining the hardware
IBM’s qubits are currently made from rings of superconducting metal, which follow the same rules as atoms when operated at millikelvin temperatures, just a tiny fraction of a degree above absolute zero. In theory, these qubits can be operated in a large ensemble. But according to IBM’s own road map, quantum computers of the sort it’s building can only scale up to 5,000 qubits with current technology. Most experts say that’s not big enough to yield much in the way of useful computation. To create powerful quantum computers, engineers will have to go bigger. And that will require new technology.
How it feels to have a life-changing brain implant removed
Burkhart’s device was implanted in his brain around nine years ago, a few years after he was left unable to move his limbs following a diving accident. He volunteered to trial the device, which enabled him to move his hand and fingers. But it had to be removed seven and a half years later.
His particular implant was a small set of 100 electrodes, carefully inserted into a part of the brain that helps control movement. It worked by recording brain activity and sending these recordings to a computer, where they were processed using an algorithm. This was connected to a sleeve of electrodes worn on the arm. The idea was to translate thoughts of movement into electrical signals that would trigger movement.
Burkhart was the first to receive the implant, in 2014; he was 24 years old. Once he had recovered from the surgery, he began a training program to learn how to use it. Three times a week for around a year and a half, he visited a lab where the implant could be connected to a computer via a cable leading out of his head.
“It worked really well,” says Burkhart. “We started off just being able to open and close my hand, but after some time we were able to do individual finger movements.” He was eventually able to combine movements and control his grip strength. He was even able to play Guitar Hero.
“There was a lot that I was able to do, which was exciting,” he says. “But it was also still limited.” Not only was he only able to use the device in the lab, but he could only perform lab-based tasks. “Any of the activities we would do would be simplified,” he says.
For example, he could pour a bottle out, but it was only a bottle of beads, because the researchers didn’t want liquids around the electrical equipment. “It was kind of a bummer it wasn’t changing everything in my life, because I had seen how beneficial it could be,” he says.
At any rate, the device worked so well that the team extended the trial. Burkhart was initially meant to have the implant in place for 12 to 18 months, he says. “But everything was really successful … so we were able to continue on for quite a while after that.” The trial was extended on an annual basis, and Burkhart continued to visit the lab twice a week.
The Download: brain implant removal, and Nvidia’s AI payoff
Leggett told researchers that she “became one” with her device. It helped her to control the unpredictable, violent seizures she routinely experienced, and allowed her to take charge of her own life. So she was devastated when, two years later, she was told she had to remove the implant because the company that made it had gone bust.
The removal of this implant, and others like it, might represent a breach of human rights, ethicists say in a paper published earlier this month. And the issue will only become more pressing as the brain implant market grows in the coming years and more people receive devices like Leggett’s. Read the full story.
You can read more about what happens to patients when their life-changing brain implants are removed against their wishes in the latest issue of The Checkup, Jessica’s weekly newsletter giving you the inside track on all things biotech. Sign up to receive it in your inbox every Thursday.
If you’d like to read more about brain implants, why not check out:
+ Brain waves can tell us how much pain someone is in. The research could open doors for personalized brain therapies to target and treat the worst kinds of chronic pain. Read the full story.
+ An ALS patient set a record for communicating via a brain implant. Brain interfaces could let paralyzed people speak at almost normal speeds. Read the full story.
+ Here’s how personalized brain stimulation could treat depression. Implants that track and optimize our brain activity are on the way. Read the full story.