AI & ML in Web Development

Web Development

Artificial intelligence and machine learning or ‘AI & ML’, is a phrase that gets thrown around a lot these days. Anything that is even remotely related to technology has a risk of being overtaken by these. But what do they actually mean? Artificial intelligence is a new field of good old-fashioned science, which mimics the cognitive abilities of the human mind to solve more complex problems within a short period of time. Now, to do so, it must ‘learn’, similar to how we train the human mind, i.e., via previous experiences, which we can call ‘data’ in technical terms. But it certainly is not possible to record all sorts of data, because we cannot predict all types of problem statements, and that’s where machine learning comes in.

Machine learning enables AI to ‘learn’ from past experiences, or information in this case, to adapt to novel situations, if and when they arise. It is still a matter of dispute, as to whether AI is a part of ML or the other way around. Either way, they immensely aid in boosting the performance of any specific task.

How is AI & ML affecting Web Dev?

AI is a rapidly advancing technology, to such an extent that today, an AI is fully capable of building a whole website from pure air, provided the necessary conditions. Artificial intelligence uses various effective algorithms to track consumer choices, superior user interface, and excellent data management. This makes it easy for upcoming start-ups and companies to attract the market towards them, no matter the product they are focusing on selling. Today, various establishments prefer to hire web developers who have expertise in the field of AI & ML over hiring website designers.

Machine learning, on the other hand, is proving to be much more efficient in domains such as client segregation, sales, marketing and advertising, and also database management, compared to conventional methods. For example, you must have observed that when you search for a particular product on your browser, you start to see more adverts for similar products, even when you’re looking for something else. This happens due to Google’s search algorithm which factors many variables for its recommendation system such as the time you spent on that page, the products you searched for, the filters you used for searching a certain price, brand, and size, etc. This is not only for Google but for most of the gigantic tech conglomerates, like Amazon.

Where & how are Artificial Intelligence and Machine Learning implemented in Web Dev?

Integration of AI into your website can greatly improve the overall client experience with your company. For instance, AI chatbots are widely used on the 24/7 customer support front, where they can solve any queries that might arise. This also lessens the workload on humans working the same job. Machine learning is also extremely useful to automate redundant and repetitive tasks, eventually saving time and resources that can be invested elsewhere. It can easily be implemented to improve business demographics and sales statistics to provide better options for a wider customer base and maximum profit margin respectively. AI & ML also promise a tighter security system, avoiding any sensitive data leaks.

The most common tools that you can use to implement AI are –

  • adding pre-programmed AI chatbots to any platform and tailoring it to its needs
  • augmenting machine learning frameworks such as TensorFlow with a high-level API to network your website
  • complementing your old websites with dynamic web applications with the help of tools viz. Microsoft Cognitive Toolkit or Apache Mahout

Final Thoughts

“We don’t need AI to make art. We need AI to write e-mails, clean the house, and deliver the groceries so that humans can make more art.” ~ Anonymous

AI for sure is useful, but it must be deployed in the right direction, to get the maximum benefits without replacing humans for the jobs. Like in the case of strategy making, AI & machine learning can forecast conditions based on actions of the clientele, competition in the market, pattern recognition, etc. It also finds use in the optimal visualization of clean data. AI and ML, being extremely versatile, can be adopted in many various languages in accordance with the requisites of the system. Big data, deep learning, sentiment analysis, efficient database management systems, interactive graphical user interface, etc. are some of the latest related technologies. These help in facilitating machine learning algorithms to better understand and solve real-world problems.

Images via Dreamstime Stock Photos

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