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IBM Unveils a New Brain Simulator

A big step forward in a project that aims for thinking chips

4 min read

18 November 2009—Scientists and engineers at IBM’s Almaden Research Center, in San Jose, Calif., announced today at the Supercomputing Conference (SC09) in Portland, Ore., that they have created the largest brain simulation to date on a supercomputer. The number of neurons and synapses in the simulation exceed those in a cat’s brain; previous simulations have reached only the level of mouse and rat brains. Experts predict that the simulation will have profound effects in two arenas: It will lead to a better understanding of how the brain’s architecture leads to cognition, and it should inspire the design of electronics that mimic the brain’s as-yet-unmatched ability to do complex computation and learn using a small volume of hardware that consumes little power.

The cortical simulator, called C2, integrates research from the fields of computation, computer memory, communication, and neuroscience to re-create 1 billion neurons connected by 10 trillion individual synapses. C2 runs on “Dawn,” a BlueGene/P supercomputer at Lawrence Livermore National Laboratory, in Livermore, Calif.

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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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