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""AI can pick up missed cues and suggest nudges to bridge the gap in emotional intelligence and communication styles. It can identify optimal ways to discuss common problems and alleviate common misunderstandings based on these different priorities and ways of viewing the world. We could be looking at a different gender dynamics in a decade.""

"Personalized pricing, which is also known as price discrimination or price optimization, depending on whether you're an economist or an online marketer, is a growing trend. According to a recent Deloitte and Salesforce report, 40% of brands that currently use AI to personalize the customer experience have used it to tailor pricing and promotions in real time. "

"It's like turning the clock back to a more earnest time on the web, when the novelty of having a voice or being able to connect with anyone still filled us with a sense of boundless opportunity and optimism. It harkens back to the late 1990s and early 2000s-before social media, before smartphones-when going online was still a valuable use of time to seek community."

"or its latest update, which it released Wednesday, the COVID-19 Scenario Modeling Hub combined nine different mathematical models from different research groups to get an outlook for the pandemic for the next six months. "Any of us who have been following this closely, given what happened with delta, are going to be really cautious about too much optimism," says Justin Lessler at the University of North Carolina, who helps run the hub. "But I do think that the trajectory is towards improvement for most of the country," he says. The modelers developed four potential scenarios, taking into account whether or not childhood vaccinations take off and whether a more infectious new variant should emerge. "

"Generational differences in learning techniques are apparent in how people of different ages approach technology. It has been said that we, the Net Generation, are closer to our grandparents-the Greatest Generation-in our work ethic and optimism about the future than to our parents' generation. But how we approach problems is totally different."

"Green Light uses machine learning systems to comb through Maps data to calculate the amount of traffic congestion present at a given light, as well as the average wait times of vehicles stopped there. That information is then used to train AI models that can autonomously optimize the traffic timing at that intersection, reducing idle times as well as the amount of braking and accelerating vehicles have to do there. It's all part of Google's goal to help its partners collectively reduce their carbon emissions by a gigaton by 2030."