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AI, machine learning and advanced data science techniques have been used for some time now to achieve some amazing results. Artificial intelligence and machine learning are interlinked in many ways and one of the most important roles they play is to build AI-based systems for themselves to accelerate their learning. Thus, knowing the latest trends and technology is not only beneficial, but it also saves a lot of time and resources.
Machine learning and AI are often used in tandem and often in conjunction with other technologies, and they also work together to solve problems. Machine learning is the process of teaching a computer system to recognize things in images, videos, or sounds. Once the computer system is trained, it can learn from that data it has collected and work with it later. In contrast, AI involves computer programs being able to perform operations and perform them well, such as playing video games or translating between languages.
Deep learning is an innovative technique that’s been used to improve AI, both on the level of data science and technology. It was first used to identify patterns in images and videos, and then was applied to speech recognition and translation. It’s one of the more advanced sub-fields of AI, and if you’re interested in learning more about it, you can get started by checking out the top deep learning courses on Coursera.
Humans are able to perform tasks that machines are incapable of performing, however, one of the biggest challenges facing AI is the consistency of its approach to a particular problem. While machine learning and AI are capable of being very specific in their approach to a given task, sometimes that specificity leads to unintended consequences. For instance, a trainable AI system may have been created with the intention of limiting the amount of damage caused by a driver, but as a side effect it may result in drivers having less control over their cars than they’d like.
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