AI

AI Enables Foreign Language Study Abroad, No Travel Required

A student learning to speak Mandarin wanders into a marketplace on the streets of China on a sunny summer afternoon. Before long, two vendors approach and begin hawking products, trying to outbid one another. The student must now grasp what’s being said and formulate an appropriate response using proper pronunciation to avoid being misunderstood. It’s […]

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Hypertaste: An AI-assisted e-tongue for fast and portable fingerprinting of complex liquids

For the rapid and mobile fingerprinting of beverages and other liquids less fit for ingestion, our team at IBM Research is currently developing Hypertaste, an electronic, AI-assisted tongue that draws inspiration from the way humans taste things.

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Text2Scene: Generating Compositional Scenes from Textual Descriptions

At CVPR 2019, IBM researchers introduce techniques to interpret visually descriptive language to generate compositional scene representations from textual descriptions.

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Overcoming Challenges In Automated Image Captioning

At CVPR 2019, IBM researchers introduce an improved method to bridge the semantic gap between visual scenes and language to produce diverse, creative and human-like captions.

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Label Set Operations (LaSO) Networks for Multi-Label Few-Shot Learning

Data augmentation is one of the leading methods to tackle the problem of few-shot learning, but current synthesis approaches only address the scenario of a single label per image, when in reality real life images may contain multiple objects. The IBM team came up with a novel technique for synthesizing samples with multiple labels.

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RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection

Deep neural networks have demonstrated good results for few-shot learning. However, very few works have investigated the problem of few-shot object detection. A team of IBM researchers developed a novel approach for Distance Metric Learning (DML).

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SpotTune: Transfer Learning through Adaptive Fine-Tuning

New techniques make fine tuning an AI model more efficient when doing transfer learning

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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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AI Offers Hope for Earlier Screening for Type 1 Diabetes

IBM researchers launch the first in-depth, large scale study of time courses when different antibodies appear, and their correlations to type 1 diabetes.

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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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