AI

IBM Research AI: Advancing AI for industry and society

The era of AI — and the technologies that will deliver it

I recently participated in a panel at Applied Materials’ 2017 Analyst Day to talk about artificial intelligence (AI). Yes, a materials company asked me, an executive overseeing semiconductor research, to join other technologists to give our view of AI – demonstrating how interest in AI has permeated all aspects of the IT industry! To lead […]

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AI-based financial advisor for low-wage workers

Workers with lower-than-median wages are often prone to financial instability and affected by bank policies such as penalty and overdraft fees, leading to a vicious cycle of debt and poor credit. During 2016 alone, banks made over $30 billion from overdraft fees. The workers with the least financial cushion are typically the most vulnerable in […]

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Using Deep Learning to Forecast Ocean Waves

IBM Research-Ireland is using AI techniques such as deep learning to forecast a physical process; namely, ocean waves.

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Using AI to help Aging Populations Live Better

The world’s population is rapidly aging: today there are 617 million people over the age of 65. By 2050, that number will jump to 1.6 billion. The population of seniors over 80 is expected to triple in that timeframe, and in some Asian and Latin American countries, it’s expected to quadruple. People might be living […]

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Demystifying Social Entrepreneurship: A Data-Driven Approach

Social enterprises present solutions to major social challenges such as climate change, global inequities, educational gaps, and many others through social innovation[1]. In fact, social enterprises attract a growing amount of talent, with an estimated 3.2{ccf696850f4de51e8cea028aa388d2d2d2eef894571ad33a4aa3b26b43009887} (global average) of adults between 18 to 64 attempting to start a social enterprise[2].  However, many get lost early […]

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The Best of Minds: IBM’s Commitment to Advancing AI Research with University Partners

IBM’s Cognitive Horizons Network produced more than 70 peer-reviewed AI publications in its first year With over two decades of AI research expertise across our global labs, our scientists take pride in their ability to explore, invent and uncover new innovations, but we also understand that the solutions to the most complex AI problems will […]

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MIT and IBM: putting our “minds and hands” together to create the future of AI

As an MIT graduate and senior leader within IBM Research, I have always felt a close kinship between these two institutions. Both are renowned for their technical excellence, and both are strongly committed to pushing the frontiers of science and technology to solve problems that matter to the world. MIT’s motto “Mens et Manus” (Latin […]

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Solving AI’s moving-target search problem at IJCAI 2017

As we look to get from point A to point B, people increasingly have options that go beyond the typical bus or taxi. Various flavours of ride and car sharing are now available in cities worldwide, making getting around more convenient than ever. Yet, as anyone that uses such services knows, it can be difficult […]

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Two IBM Researchers to Speak at TEDGlobal 2017 in Africa

This week in Arusha, Tanzania, hundreds will gather for one of the most highly anticipated events of the year: TEDGlobal. The sold out event brings together entrepreneurs, business leaders,  technologists, dreamers and doers to talk about the challenges and opportunities on the African continent. Representing IBM’s Africa Labs scientists Drs. Abdigani Diriye and David Moinina […]

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Brain-Inspired AI: How Neuroscience Helps to Advance Machine Learning

While building artificial systems does not necessarily require copying nature — after all, airplanes fly without flapping their wings like birds — the history of AI and machine learning convincingly demonstrates that drawing inspirations from neuroscience and psychology can lead to significant breakthroughs, with deep neural networks and reinforcement learning being perhaps the two most […]

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Removing the hunch in data science with AI-based automated feature engineering

For data scientists, predictive modeling is the practice of predicting future outcomes using statistical models. Its increasing adoption in the field of AI includes diagnosing cancer, predicting hurricanes and optimizing supply chains, amongst other areas. However, the value of predictive modeling comes at the cost of practicing it. The cornerstone of successful predictive modeling, known […]

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