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A Beginners Guide to Artificial Intelligence For Web Developers
Artificial Intelligence has significantly transformed the way we work and interpret information. With technologies such as OCR, machine learning, deep learning, natural language processing, and computer vision; machines are now able to provide greater insights and perform tasks that typically required hours and hours of work from humans.
What is artificial intelligence?
A.I. or artificial intelligence is the technology that enables machines to perform tasks that usually require human intelligence. But instead of using human brains, A.I. uses different technologies such as computers, or even software algorithms, to perform tasks. Some of the most common A.I. technologies include speech recognition, voice recognition, machine translation, natural language processing, computer vision, and predictive analytics. The term artificial intelligence comes from the combination of artificial and intelligence. While artificial intelligence is a property of the physical world, intelligence is the property of the mind. How does it make sense in Web Development? As mentioned earlier, A.I. has significantly transformed the way we work and interpret information.
How is AI applied to web development?
In the majority of cases, AI is used to assist a developer in a number of functions: Automatically format existing content, analyze images for semantic meaning Break down complex tasks into smaller pieces Example applications of AI in web development Example image compression algorithms. Tools such as image recognition and machine learning have been key factors in the development of new image processing algorithms. Traditionally, manually processing an image was a lengthy and tedious process, but when computer vision was introduced into the process it drastically decreased the amount of time required to complete this task. Now, programs such as image recognition can identify objects in images and classify them based on both visual and metadata attributes.
Machine learning
When data is fed into a machine learning algorithm, the machine learns to understand it. For instance, if you provide a machine learning algorithm examples of dogs versus blueberries, the machine will learn to identify what a picture of a blueberry looks like, versus a picture of a dog. Natural Language Processing Natural language processing is a sub-field of machine learning. You can apply natural language processing for reading emails, chatting, or writing blog posts (such as this one!). A good example of natural language processing in action can be found in Microsoft’s Cortana. Deep learning This is the most popular type of artificial intelligence today.
Deep learning
Deep learning algorithms are very similar to how the human brain works, with its built-in mechanisms to learn and memorise a vast amount of information. It’s these connections that enable machines to be able to recognise patterns and learn from them. An example of this is Google Translate, which recognises more than 1,000 languages. This isn’t an example of AI but it shows how useful these programs can be. Deep learning is one of the hottest technologies in the field of machine learning and this explains why almost all of the major technology companies are pushing these advances forward.
Natural language processing
For example, your phone can understand you better when you speak to it. If you say “Hey, Siri,” your phone will listen to you and respond to your questions. In general, it means that the system has been trained and is able to better understand the context of what you’re trying to communicate. This type of Natural Language Processing is used in the majority of companies today, including the likes of Google and Apple, to improve the user experience, provide better customer service, and to aid in the effective execution of processes. Machine learning is an extremely powerful technique used to further improve the knowledge of artificial intelligence, as well as to make machines smarter by discovering patterns and generalities in vast amounts of data.
Computer vision
Computer vision is a technology that has been able to recognize objects in images and video for aeons. A popular example is Apple’s Siri, which was one of the first software to use computer vision to provide contextual awareness. AI is built on this technology, providing the capability to recognize various images and videos. The industry is still in its infancy, but what we have seen so far has been incredibly incredible. What’s amazing is that just a few years ago we thought that vision was completely under our control, but now, it has evolved to understand the nuances of objects.
