AI

IBM Releases Novel AI-Powered Technologies to Help Health and Research Community Accelerate the Discovery of Medical Insights and Treatments for COVID-19

IBM Research is making available multiple novel, free resources to help healthcare researchers, doctors and scientists around the world accelerate COVID-19 drug discovery.

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Moving Beyond the Lab: IBM Research Powers Pipeline of AI Advances for the Enterprise

IBM AI researchers are responsible for developing many of the NLP capabilities IBM has brought to market. With the announcement that IBM will begin integrating NLP features developed for Project Debater into Watson, IBM Research once again delivers unique technology from the lab to the enterprise.

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Female IBM Researchers are helping AI overcome bias and find its voice

This month, we are highlighting the work of four women researchers at IBM who are pushing the frontiers of AI technology. Their efforts extend from work process automation to the design of ever more intelligent chatbots to the discovery of new, more effective antibiotics.

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Characterizing the Evolution of Tasks Within Occupations

The team at the IBM-MIT Watson AI Lab presented a new study at the AAAI Conference on AI, Ethics, and Society on “Learning Occupational Task-Shares Dynamics for the Future of Work” that shows how to predict changes in the economy’s demand for different tasks.

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IBM Research at SPIE 2020: New Architectures and Fabrications for AI Hardware

IBM Research had 21 papers accepted to SPIE, and throughout the four-day conference IBM researchers will present on topics ranging from EUV lithography, patterning materials, etch, selective deposition, and novel device integration.

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Deriving Complex Insights from Event-driven Continuous Time Bayesian Networks

Real-world decision making often involves situations and systems whose uncertain and inter-dependent variables interact in a complex and dynamic way. Additionally, many scenarios are influenced by external events that affect how system variables evolve. To address these complex scenarios for decision making, together with colleagues at the IBM T. J. Watson Research Center, we have developed a new dynamic, probabilistic graphical model called - Event-driven Continuous Time Bayesian Networks.

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Bringing AI to the Command Line

For decades, developers and researchers have been using the command line interface (CLI) to build, execute, and deploy the software that runs the world around us. Users have come to love, hate and, eventually, embrace the unique, idiosyncratic, and sometimes antiquated challenges associated with using the terminal shell; and have adapted their behaviors and usage […]

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IBM Research AI Hardware Center marks first birthday with explosive gains in AI computation

One year ago, we announced the creation of the IBM Research AI Hardware Center, a global research hub headquartered in Albany, New York. Building on work of the last few years, the launch of the Center initiated the next phase in a long-term effort to combine evolving, fundamental advances in AI with new computing accelerators, […]

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Helping Advance Huntington’s Disease Research by Using AI to Map the Human Brain

In a new study, IBM and CHDI researchers studied the relationship between the pace of subtle cognitive decline in patients before full-fledged symptoms and their brain activity, as shown by a functional MRI. The results demonstrate that measuring the potential progression of HD could eventually be done from a single brain scan, acquired in one visit.

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2020 AI Predictions from IBM Research

In 2020, three themes will shape the advancement of AI: automation, natural language processing, and trust. From this lens, IBM Research is unveiling its annual five predictions for AI in 2020.

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The path to the “perfect” analog material and system: IBM at IEDM and NeurIPS

Researchers from the IBM AI Hardware Center will showcase at IEDM and NeurIPS new analog devices, algorithmic and architectural solutions, a novel model training technique, and a full custom design.

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Quantum-Inspired Logical Embedding for Knowledge Representation

In our new paper, to be presented at NeurIPS 2019, we develop a new knowledge representation, which we call “quantum embedding”, that represents conceptual knowledge using a vector space representation that preserves its logical structure and allows reasoning tasks to be solved accurately and efficiently.

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