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Technology-savvy students, on the other hand, see this as an opportunity and use it to their advantage. With the development of artificial intelligence, it has been discussing whether homework will be done entirely with the help of artificial intelligence in the near future. However, many students interested in technology have already started using artificial intelligence to do their homework. According to students who use artificial intelligence in their homework, the "system" works like this: They transfer the assignment given as an idea to artificial intelligence, usually GPT-3, and the artificial intelligence then create a text for them. As such, it seems inevitable to take new actions in the education world.
Algorithms developed in Cornell's Intelligent Systems and Controls Lab can predict volleyball players' in-game movements with more than 80% accuracy. Now the lab is collaborating with the Big Red hockey team to see the situation in other sports. These algorithms are unique because they bring a holistic approach to actions by combining visual data, such as an athlete's position on the field, with more implicit information, such as the athlete's specific role in the team. By watching volleyball matches, researchers train algorithms to reveal hidden variables in the same way people gain sports knowledge. The algorithms use machine learning to extract data from videos of volleyball games and then use that data to help make predictions when a new set of games is shown. The results show that the algorithms can infer the roles of players (for example, distinguishing a defender from a blocker) with an average accuracy of 85%
The new research published in the British Journal of Ophthalmology provides a machine learning-based method for developing quick and cheap cardiovascular screenings. If the findings from this study are validated in future clinical trials, it could mean that individuals could find out their risk of stroke and heart attack without needing blood tests or blood pressure measurements. This would be a huge breakthrough in cardiovascular health and could help save lives by catching risk factors early. The study shows that the predictions made by the AI tool are as accurate as the predictions made by current tests.
Research by the Bank of England and the Financial Conduct Authority shows an increasing number of UK financial services firms using machine learning (ML). Overall, 72% of firms report using or developing machine learning applications. This trend is likely to continue, and companies expect average machine learning applications to increase 3.5 times over the next three years. In addition, companies think that machine learning provides a number of benefits. The most commonly identified benefits at this time are enhanced data analytics capabilities, increased operational efficiency, and better detection of fraud and money laundering.
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