The Artificial Intelligence Podcast Dr. Tony Hoang

Online reviews have become an essential tool for consumers to make informed decisions about purchases, restaurants, and movies. However, not all reviews can be trusted, as there are both honest and deceptive ones. Fake reviews can harm a product's reputation, with negative ones potentially submitted by competitors and positive ones posted by individuals with a financial interest. Companies like Amazon are using artificial intelligence (AI) to identify and prevent fraudulent reviews. Consumers can protect themselves by trusting their instincts, paying attention to language and tone, validating reviewers, and looking for patterns in reviews. AI technology can help websites flag potential fake reviews, maintaining the credibility of their review systems.


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A recent survey conducted by Callvu, a customer experience platform, revealed that despite the prevalence of AI chatbots in customer service, 81% of respondents still prefer to speak with a human representative. The survey also highlighted desired wait times, with the majority of respondents indicating a willingness to wait between one and 11 minutes for a human agent. The survey suggests that while AI chatbots excel at simple tasks, human agents are perceived as better equipped for complex problem-solving and effective issue resolution. Additionally, customers expressed a desire to vent frustrations to human representatives and were skeptical about the deployment of chatbots, believing it was primarily to save money and eliminate jobs.


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AEYE Health, a leading company for AI retinal imaging and diagnostics, has received FDA clearance for the first fully autonomous AI that diagnoses referable diabetic retinopathy. The breakthrough technology uses retinal images obtained by a handheld camera to screen for the leading cause of blindness in the working-age population. The combination of a fully autonomous AI with a portable handheld device allows for an affordable screening solution that can be used anywhere, making it particularly suitable for point-of-care screening. With over 99% of images being usable and the option for patients to be screened at home, AEYE Health's innovation could prevent blindness in millions of people.


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Ford Motor Co. has launched Ford University, an AI-powered platform aimed at enhancing training for dealership employees. The platform takes a more interactive and cinematic approach, improving memory retention and enabling employees to better respond to customer queries. Ford spent a year assembling a team of experts to develop the platform, which covers product knowledge, competitor analysis, sales techniques, and more. While not mandatory, the website features video content and assessments to gauge employee understanding and areas for improvement. Ford intends to expand the platform internationally and is also exploring AI technology to simulate customer conversations for enhanced support.


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Scientists at The Ohio State University have developed an AI model called CURE that can predict treatment outcomes for preventing stroke in heart disease patients. The model, based on data from millions of patients, was pre-trained on general data and then fine-tuned with specific health conditions and treatments. The model outperformed existing models and made the same treatment recommendations as randomized clinical trials. By expediting clinical trials and personalizing patient care, the model aims to save time and money. The researchers also incorporated techniques to enhance the model's accuracy, including filling in gaps in patient records and using medical claims and knowledge graphs.


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Researchers at MIT Lincoln Laboratory have released a new artificial intelligence dataset called TorNet, which contains radar returns from thousands of tornadoes that have occurred in the United States over the past 10 years. The dataset aims to improve tornado detection and forecasting by enabling breakthroughs in machine learning algorithms. Along with the dataset, the researchers have also released models that have been trained on it, showing promise in their ability to detect tornadoes. Improved tornado detection and forecasting could help issue more accurate warnings, potentially saving lives. The dataset provides a benchmark for researchers and makes meteorology more accessible to data scientists.


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