A team of researchers at the MIT Computer Science & Artificial Intelligence Lab (CSAIL) recently released a framework called TextFooler which successfully tricked state-of-the-art NLP models (such as BERT) into making incorrect predictions.
Source: infoq.com
We’ve recently launched good first issues recommendations to help new contributors find easy gateways into open source projects. Read about the machine learning engine behind these recommendations. GitHub is leveraging machine learning (ML) to help more people contribute to open source.
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A new study co-authored by an MIT economist shows that improved translation software can significantly boost international trade online — a notable case of machine learning having a clear impact on economic activity. The research finds that after eBay improved its automatic translation program in 2014, commerce shot up by 10.9 percent among pairs of countries where people could use the new system. To put the results in perspective, he adds, consider that physical distance is, by itself, also a significant barrier to global commerce.
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The AI Index 2019 Report takes an interdisciplinary approach by design, analyzing and distilling patterns about AI’s broad global impact on everything from national economies to job growth, research and public perception. We’re excited to release the AI Index 2019 Report, one of the most comprehensive studies about AI to date. Because AI touches so many aspects of society, the Index takes an interdisciplinary approach by design, analyzing and distilling patterns about AI’s broad global impact on everything from national economies to job growth, research and public perception.
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