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Conversational AI: How It Works and Where It s Headed

Emotion Detection in Tech: It s Complicated

Informationweek Emotion Detection in Tech: It’s Complicated The advancement of human-machine partnerships requires emotion detection and appropriate responses in context, but it s a tough problem. Image: olly - stock.adobe.com Of all the potential types of analytics, emotion analytics is one of the toughest to perfect because human emotions are complex. For example, there are genuine reactions and fabricated ones as well as cultural and individual differences that shape our perceptions and behaviors. There are also other things to consider such as context. While emotion analytics is clearly important to the future of analytics, AI, robotics, intelligent automation and applications, the early-stage excitement can lead to unrealistic expectations.

4 Ways to Overcome AI Obstacles - InformationWeek

Informationweek Commentary Four out of five organizations haven t scaled their AI. Here are some ways to change that. Even as the pandemic tightens technology budgets, there are plenty of companies eager to leverage the highly beneficial capabilities of AI. They hire data scientists, identify use cases, and build proofs of concept. Yet, according to a recent research report from Capgemini, four out of five organizations fail to successfully scale these AI programs from the pilot and initial production stages. Image: sakkmesterke - stock.adobe.com When scaled effectively, AI programs can provide payback that is several times greater than the initial investment, all within the first six months. But without scaling their programs, most organizations aren’t reaping the benefits and showing the value of their AI implementations. This lack of value during difficult economic times results in less additional funding to continue to expand the AI program even though the returns could

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