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Artificial intelligence – the greatest opportunity for women? - Welcome to the WISE Campaign

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Sarah Burnett, Vice President at Everest Group, Computer Weekly top 30 influential women in IT, chair of BCS Women and founder of WISE members, BCSWomen AI Accelerator In March this year, I launched the new Artificial Intelligence (AI) Accelerator for WISE members, BCSWomen to make AI more relevant to women and encourage more females into computing. Just … Continue reading "Artificial intelligence – the greatest opportunity for women?"


How Machine Learning Will Affect Software Development - DZone AI

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Modern software systems emit a tremendous amount of "machine data" (logs, metrics, etc.) that can be crucial to identifying and understanding misbehavior, but the quantity and complexity of this data is outpacing the human ability to do the required analysis and take timely action. For this reason, I think we will see a lot of opportunities to build automated systems that analyze (and even act) on this machine data in order to improve the security, performance, and reliability of economically critical software services. That said, there's also a lot of exciting research around "ML on code": automatically identifying risky pull requests, automated bug localization, intelligent IDE assistance, and so on. Given the well-known challenges of building and operating software systems, there is likely to be plenty of room for improvement across the entire lifecycle. Overall, I think we're heading into a really interesting time for the application of ML techniques to software development, security, and operations.


Executive Insights on Artificial Intelligence and All of Its Variants - DZone AI

@machinelearnbot

This article is featured in the new DZone Guide to Artificial Intelligence. Get your free copy for more insightful articles, industry statistics, and more! To gather insights on the state of artificial intelligence (AI) and all its variants -- machine learning (ML), deep learning (DL), natural language processing (NLP), predictive analytics, and neural networks -- we spoke with 22 executives who are familiar with AI. The key to having a successful AI business strategy is to know what business problem you are trying to solve. Having the necessary data, having the right tools, and having the wherewithal to keep your models up-to-date are important once you've identified specifically what you want to accomplish.