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5 Big Myths of AI and Machine Learning Debunked

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Scaling AI in your organization should be deliberate, not rushed

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TechRepublic's Karen Roby talked with Greg Douglas of Accenture, an artificial intelligence (AI) company, about the myths surrounding scaling AI. The following is an edited transcript of their conversation. Karen Roby: As the pandemic continues, many companies are looking to scale AI projects, and there are a lot of myths out there about how you actually take this technology to scale. You guys have put together a really interesting study that looked at a real cross section when it comes to AI. Let's talk a little bit about the most important findings and what really jumped out to you from this study. Greg Douglas: We interviewed 1,500 executives across 16 different industries around the world, so a really vast survey, to see where our clients and where companies were at in terms of scaling and deploying artificial intelligence.


5 Big Myths of AI and Machine Learning Debunked - Communal News

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AI has been with us in one form or another for over 60 years and yet it seems to be more misunderstood today than ever. Venture capital investment in AI now tops $3 billion annually, and the number of active startups in the U.S. that are developing AI technologies has gone up by a factor of 14 since 2000. A huge number of consumer products are now being built with AI, from smartphones that understand what we say to smart dolls that can understand how your child feels. But in the enterprise, the sentiment surrounding AI still seems to stress caution. First-movers aside, executives are hesitant to implement AI and machine learning systems in their organization and that's if they even understand the difference between the two.