![]() ![]() There is increasingly widespread interest in AI, partly because of a combination of new methods and powerful computers becoming more widely accessible. Deep learning methods build on work done on artificial neurons developed as an idea back in the 1940s to model real biological brains. Deep Learningĭeep learning is a further subset of machine learning that seeks to mimic the way humans handle information and draw conclusions using a ‘neural network’. In machine learning, algorithms are ‘trained’ to build a model based on sample data, enabling them to make subsequent predictions or decisions. Machine learning enables computers to learn from data effectively without being specifically programmed. Figure 1 summarizes how these subsets relate. ![]() It is an over-arching term that includes two subsets: machine learning and deep learning. What is Artificial Intelligence?ĪI is a subset of computer science that enables machines to carry out tasks traditionally done by humans. In a research world of less funding and more competition, AI can be vital to staying ahead of the game. In big data, problems are getting harder to solve due to the enormity of the data that needs processing-AI helps with this! Also, researchers can focus on the bigger picture rather than analyzing hundreds or thousands of individual images or data. Why Should Researchers Care About Artificial Intelligence? I’ve also highlighted some resources you may find helpful if you want to learn more about these topics. That’s why I’ve pulled together a gentle introduction to AI, its sub-methods, machine learning, and deep learning and how they can enhance your data analysis, simplify your image processing, predict your protein structures, and more! However, as an emerging concept and tool, the application of artificial intelligence (AI) in your biology research can be challenging to grasp. Researchers are increasingly turning to artificial intelligence in biology to address complex problems. In biology, AI helps to automate and simplify image analysis, predict protein structures, and aid drug discovery. ![]() Machine learning (ML) is a subset of AI that enables computers to learn from data, while deep learning is a subset of ML that seeks to process information similarly to humans. Artificial intelligence (AI) allows machines to perform tasks traditionally done by humans. ![]()
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