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IBM Research AI: Advancing AI for industry and society

IBM Federated Learning – machine learning where the data is

IBM Research recently announced the community edition of a framework for federated learning.

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IBM Research and The Michael J. Fox Foundation Develop Modeling Methodology to Help Understand Parkinson’s Disease Using Machine Learning

In collaboration with The Michael J. Fox Foundation for Parkinson’s Research, our team of researchers at IBM is aiming to develop improved disease progression models that can help clinicians understand how the disease progresses in relation to the emergence of symptoms, even when those patients are taking symptom-modifying medications.

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Image Captioning as an Assistive Technology

IBM Research's Science for Social Good team recently participated in the 2020 VizWiz Grand Challenge to design and improve systems that make the world more accessible for the blind.

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Reducing Speech-to-Text Model Training Time on Switchboard-2000 from a Week to Under Two Hours

Published in our recent ICASSP 2020 paper in which we successfully shorten the training time on the 2000-hour Switchboard dataset, which is one of the largest public ASR benchmarks, from over a week to less than two hours on a 128-GPU IBM high-performance computing cluster. To the best of our knowledge, this is the fastest training time recorded on this dataset.

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IBM & MIT Roundtable: Solving AI’s Big Challenges Requires a Hybrid Approach

At IBM Research’s recent “The Path to More Flexible AI” virtual roundtable, a panel of MIT and IBM experts discussed some of the biggest obstacles they face in developing artificial intelligence that can perform optimally in real-world situations.

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Bringing IBM NLP capabilities to the CORD-19 Dataset

To assist in the fight against the COVID-19 pandemic, prominent research institutes led by Allen Institute for AI (AI2) released earlier this year the COVID-19 Open Research Dataset (CORD-19). Comprised of scientific articles related to COVID-19, Sars-Cov-2, and related coronaviruses, the dataset (which at the time of writing this contains more than 75,000 full text scientific papers) is […]

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IBM Research AI Advances Speaker Diarization in Real Use Cases

In a recent publication, IBM researchers describe a novel speaker diarization algorithm that can consider not only speaker information, but also identifying clues about individual recording environments that help differentiate between the speakers, resulting in improved diarization accuracy for our in-house, real test cases as well as public benchmark data.

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Bio-Inspired Hashing for Unsupervised Similarity Search

In a new paper, researchers use the inspiration of the fruit fly olfactory network and a biologically plausible method for representation learning to propose a data-driven hashing algorithm for approximate similarity search.

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IBM Research at ICML 2020

At ICML 2020, IBM Research wll present several demos, talks, and papers related to trusted AI, including the topics of fairness, robustness and explainability.

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IBM FactSheets Further Advances Trust in AI

IBM Research released a new, informative website that shares the latest on AI FactSheets, designed to foster increased levels of trust in AI by increasing transparency and enabling governance. 

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IBM Research at ACL 2020

The 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), the premiere annual conference on AI and language, takes place July 5-10. As is the case with most events currently, ACL will be virtual this year due to COVID-19. At IBM Research AI, we’re excited to share with you — wherever you might be in the world — all the work […]

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