AI

IBM Research AI: Advancing AI for industry and society

IBM Research AI at CVPR 2019

The annual conference on Computer Vision and Pattern Recognition (CVPR 2019) takes place June 16–20 in Long Beach, CA. There, IBM Research AI will present technical papers describing our latest results in our quest to give AI systems sight.

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Beyond Backprop: Online Alternating Minimization with Auxiliary Variables

IBM researchers, in collaboration with NYU and MIT, propose a novel alternative to backprop at ICML 2019 that offers competitive performance.

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Estimating Information Flow in Deep Neural Networks

Understanding of the macroscopic behavior of deep learning neural networks.

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Unveiling Analog Memory-based Technologies to Advance AI at VLSI

At the 2019 VLSI, IBM researchers will present three papers that provide novel solutions to AI computing based on analog devices.

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GANs for Good: Digitizing Sketches of the Earth’s Surface with the AI Behind Deep Fakes

Scientists in IBM Research-Brazil developed a method based on GANs and hand sketches to generate realistic synthetic seismic images.

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IBM Research AI Moves Machine Learning Forward at ICML 2019

At the 36th International Conference on Machine Learning (ICML 2019), June 10–15 in Long Beach, CA, IBM Research AI will present recent technical advances in machine learning for AI and data science. We’ve led the exploration and development of machine learning technologies for decades, and now we’re progressing the AI field through our portfolio of […]

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IBM Sets New Transcription Performance Milestone on Automatic Broadcast News Captioning

IBM sets new performance records for automatic captioning of broadcast news audio, with error rates of 6.5% and 5.9% on two broadcast news benchmarks.

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Ultra-Low-Precision Training of Deep Neural Networks

IBM researchers introduce accumulation bit-width scaling, addressing a critical need in ultra-low-precision hardware for training deep neural networks.

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Leveraging Temporal Dependency to Combat Audio Adversarial Attacks

A new approach to defend against adversarial attacks in non-image tasks, such as audio input and automatic speech recognition.

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Unifying Continual Learning and Meta-Learning with Meta-Experience Replay

Meta-Experience Replay (MER) integrates meta-learning and experience replay to achieve state-of-the-art performance on continual learning benchmarks.

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Will Adam Algorithms Work for Me?

A simple and effective approach to monitor the convergence of Adam algorithms, a generic class of adaptive gradient methods for non-convex optimization.

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IBM Project Debater Visits the UN

Can AI capture the narrative of a global population on a controversial topic? IBM brings Project Debater to the AI for Social Good summit to find out.

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