neuromorphic

Novel Synaptic Architecture for Brain Inspired Computing

IBM scientists developed an artificial synaptic architecture, a significant step towards large-scale and energy efficient neuromorphic computing technology.

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Publishing in The Lancet’s EBioMedicine: New research in AI pushes frontiers in epileptic seizure prediction

Today, The Lancet’s EBioMedicine journal will publish a study led by scientists from IBM Research-Australia and the University of Melbourne marking important progress in personalized seizure forecasting with AI. The findings, described in a paper titled ‘Epileptic Seizure Prediction using Big Data and Deep Learning: Toward a Mobile System,’ present new results in epileptic seizure […]

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IoT neurons go macro, go global with DyBM

Imagine covering the globe with a sheet of artificial, internet-enabled neurons. And these Internet of Things (IoT) neurons could send their local information to other neurons just like the synapses in our brains. For example, a ground temperature neuron at one location gets collected and shared with air quality neurons, and vice versa. This spatio-temporal […]

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Grad student wins IBM Fellowship to Mimic Brain Architecture

S. R. Nandakumar, a graduate student in electrical engineering, has won a coveted IBM Ph.D. fellowship to support his work on computer systems that mimic the architecture of the human brain. He is currently interning at IBM’s Zurich Lab and we had the chance to ask him a few questions. Q. Last August IBM scientists published […]

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The brain’s architecture, efficiency… on a chip

2016 was a big year for brain-inspired computing. My team and I proved in our paper “Convolutional networks for fast, energy-efficient neuromorphic computing” that the value of this breakthrough is that it can perform neural network inference at unprecedented ultra-low energy consumption. Simply stated, our TrueNorth chip’s non-von Neumann architecture mimics the brain’s neural architecture […]

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Deep learning inference possible in embedded systems thanks to TrueNorth

Scientists at IBM Research – Almaden have demonstrated that the TrueNorth brain-inspired computer chip, with its 1 million neurons and 256 million synapses, can efficiently implement inference with deep networks that approach state-of-the-art classification accuracy on several vision and speech datasets. This will open up the possibilities of embedding intelligence in the entire computing stack […]

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Unsupervised learning with artificial neurons

Inspired by the way the human brain functions, a team of scientists at IBM Research in Zurich, have imitated the way neurons spike, for example when we touch a hot plate. These so-called artificial neurons can be used to detect patterns and discover correlations in Big Data with power budgets and at densities comparable to […]

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