Modern technologies like artificial intelligence, machine learning, data science have become popular but no one completely understands it. They appear to be extremely complicated to a layman. All these popular terms sound like a business executive or a student from a non-technical background. People often get confused by words like AI, ML and data science. In this blog, we clarify these technologies in basic words so you can easily distinguish them and how they are being used in business. Let us discuss Artificial Intelligence vs Machine Learning vs Data Science.
What’s Artificial Intelligence?
The main purpose for artificial intelligence is to impart human intelligence to machines. Artificial intelligence can relate to anything – from applications for playing chess to speech recognition systems. Just like the Amazon Alexa voice assistant, which recognizes speech and answers questions. Artificial intelligence focuses on making smart devices that think and act like people. These devices are trained to solve issues and learn in a superior manner than humans do.
AI application examples include:
- Game-playing algorithms (like Deep Blue)
- Robotics and control theory (motion planning, walking a robot)
- Optimization (like Google Maps creating a route)
- Natural language processing
- Reinforcement learning
Best example of AI implementation is self-driving cars and robots. What’s more, here’s the manner by which Amazon utilizes brilliant robots. Amazon Prime used to be fueled by individuals whose occupations rotated around getting items from distribution centers to clients’ doorsteps. Artificial intelligence specialists work with AI frameworks like Pytorch and Torch, TensorFlow, Caffe, Chainer, and lots of others.
What is Machine Learning?
Machine learning is one of the areas of artificial intelligence. It’s the science of getting computers to learn and also act like people do and improve their learning after some time in an autonomous fashion. Rather than writing code, you feed information to the generic algorithm, and it builds its logic based on that information. Basically, in ML, computers learn to program themselves. ML makes programming more scalable and helps us to deliver better results in a shorter time.
How companies use machine learning?
Read more at- http://artificial.digital/data6-src_blogger
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