Teaching AI to be Sociable

Humans can already form social bonds with robots, but the real trick may be getting AI equally interested in us

3 min read

In the recent superhero film Iron Man , there’s a scene where Robert Downey Jr.’s character struggles to reach a device to power his failing heart. He stretches an arm up to the device, but collapses before he can grab it. Lucky for him, his trusty robot is nearby—it manages to anticipate what he wants and hand him the device just in time.

In the real world, we’ve yet to create artificial intelligences that can respond so intuitively to our needs. The quest to do so has pushed two groups of researchers in nearly opposite directions. One group, at Rensselaer Polytechnic Institute (RPI), in Troy, N.Y., has built Eddie, an AI that resides in the virtual world of Second Life and harnesses the power of a supercomputer to analyze a library of rules about human thinking. The other, MIT Media Lab’s Personal Robots Group, has built Leonardo, a furry, animatronic robot that learns as a child does, by interacting with people in the physical world. Within the last two years both Eddie and Leonardo have demonstrated a basic social ability that is the first step toward AI that understands how humans think.

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An IBM Quantum Computer Will Soon Pass the 1,000-Qubit Mark

The Condor processor is just one quantum-computing advance slated for 2023

4 min read
This photo shows a woman working on a piece of apparatus that is suspended from the ceiling of the laboratory.

A researcher at IBM’s Thomas J. Watson Research Center examines some of the quantum hardware being constructed there.

Connie Zhou/IBM

IBM’s Condor, the world’s first universal quantum computer with more than 1,000 qubits, is set to debut in 2023. The year is also expected to see IBM launch Heron, the first of a new flock of modular quantum processors that the company says may help it produce quantum computers with more than 4,000 qubits by 2025.

This article is part of our special report Top Tech 2023.

While quantum computers can, in theory, quickly find answers to problems that classical computers would take eons to solve, today’s quantum hardware is still short on qubits, limiting its usefulness. Entanglement and other quantum states necessary for quantum computation are infamously fragile, being susceptible to heat and other disturbances, which makes scaling up the number of qubits a huge technical challenge.

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