AI

IBM Research AI: Advancing AI for industry and society

IBM Researchers Receive Aegis Graham Bell Award for Work in Digital Agriculture

The earth’s population is 7.6 billion and will rise to 11 billion by the turn of the century. Somehow, we must feed this 45 percent larger population with 10-20 percent less farmable land, and far less farmers. At the same time, a significant fraction of land and productive crop yield will be converted into bioenergy […]

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Charity Models Supply Chain Performance with IBM

I’ve always sought out challenging applied research problems and am particularly attracted to applications of technology in the social sector. That’s why I was thrilled to work on a supply chain-focused project with the non-profit organization St. John’s Bread & Life (SJBL) within IBM’s Science for Social Good program in 2017. Based in Brooklyn, SJBL […]

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Deep Learning Training Times Get Significant Reduction

IBM researchers developed a novel compression algorithm that could significantly improve training times for deep learning models in large-scale AI systems.

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Tapping Machine Learning to Foster Greater Use of Biomimicry for Innovation

Knowledge transfer across domains leads to significant breakthroughs in science and technology. For example, through biomimicry, innovators get inspiration from nature/biology to solve complex engineering problems. An exciting example of biomimicry is the recent creation of artificial materials that imitate the surface of cicada’s wings and gecko’s skin, which have antibacterial properties due to their […]

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Automating Code Generation for Deep Learning Models from Research Papers

In an upcoming presentation at the 2018 AAAI Conference, our team of deep learning experts at IBM Research India propose a new and exploratory technique that automatically ingests and infers deep learning algorithms in published research papers and recreates them in source code for inclusion in libraries for multiple deep learning frameworks (Tensorflow, Keras, Caffe). With […]

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End-to-End Open-Domain QA via Multi-Passage Reading Comprehension

Recently, impressive progress has been made in neural network question answering (QA) systems which can analyze a passage to answer a question. These systems work by matching a representation of the question to the text to find the relevant answer phrase. But what if the text is potentially all of Wikipedia?  And what if the […]

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IBM Research AI at the AAAI Conference on Artificial Intelligence

At the 32nd AAAI conference on artificial intelligence, IBM will share significant progress from its AI research team, including technical papers as well as results from the company’s ongoing collaboration with academic institutions through the MIT IBM Watson AI Lab and the AI Horizons Network. Among the featured IBM AI research projects that will be […]

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Prediction of psychotic onset with AI: words portend the future

Psychiatrists characterize schizophrenia, a mental condition with devastating effects on those who suffer it, by a set of intuitively understandable concepts including “poverty of speech” and “flight of ideas.” These concepts, however, are subjective in the sense that their quantification depends significantly on the particular training and ultimate judgment of individual psychiatrists. The evaluation of […]

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How AI can help enterprise workers automatically triage conversations

Knowledge workers spend an average of 28 hours in a typical work week on email and messaging, conversations and collaboration. Much of these communications are centered around getting organized and getting work done — define actions or tasks, make requests and commitments of each other, and exchange updates on the status of the work in progress. However, information overload remains a […]

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ROMEO Seeks to Improve Wind Farms with Machine Learning and IoT at the Edge

This past summer a five-year, €16 million EU Horizon 2020 project kicked off to reduce the maintenance cost of wind turbines using predictive machine learning algorithms, the Internet of Things and cloud computing. The project called ROMEO, or “Reliable Operations & Maintenance Decision tools and strategies for high LCoE reduction on Offshore wind”, and not […]

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Pruning AI networks without performance loss

In a spotlight paper from the 2017 NIPS Conference, my team and I presented an AI optimization framework we call Net-Trim, which is a layer-wise convex scheme to prune a pre-trained deep neural network. Deep learning has become a method of choice for many AI applications, ranging from image recognition to language translation. Thanks to […]

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