Looking at the rapid acceleration of the Artificial Intelligence field today, one might not believe that it was stagnant for decades altogether. AI has so much more to evolve into, and we’re only at the stage of “weak AI” now, but the phase of “self-aware AI” (machines that outperform humans in cognitive tasks and are near-equal to humans in thinking terms if not better) is not so far away. With the number of job opportunities skyrocketing and the ever-increasing demand in skills for AI, it has become one of the most important career options for data science aspirants and software engineers.
If you’re an engineer/engineer-to-be and are looking to learn more about the field of AI, here’s a starting point for practical learning and putting some AI knowledge to good use. There are various p rogramming languages that people code in, but what’s the best out there? And why is it the best? Read on to know more. Oh, but before that, here are some applications of AI, which might give you a sense of the importance of AI in today’s world:
- Virtual assistants like Siri, Cortana, or Bixby
- Email spam filters
- Entertainment recommender systems (Netflix, Amazon Prime Video, etc.)
- Chatbots, smart searches
- Personalized ad targets
- Photo recognition etc.
There are several factors at play when it comes to determining the best programming languages for AI. There is no best programming language because there are several shortcomings in every language, which brings us to talk about the best programming languages (in plural). Here are some of the factors that are considered –
One of the most important things when it comes to coding for AI is the standard libraries that programming languages have. These are in-built blocks of code that need not be typed in again and can be accessed by valid syntaxes in each programming language. Standard Libraries have the definitions of most commonly used algorithms, data structures, and mechanisms for input and output, among other complex computations. Having an abundance of standard libraries makes coding for AI much easier and faster.
Programming languages back in the day were extremely long and complex. With the progress of time, however, they’ve become easier, and today we have a huge number of languages that are extremely easy to learn/understand and short to code in. It is important for people to not have difficulty in understanding the syntaxes since the logical part when it comes to AI is difficult in itself.
Most programming languages that are widely popular today are open-source and free. We need to be able to develop the language too as time progresses and keep it up-to-date by adding newer libraries, for instance, and tweaking other aspects of it. This can only be possible if the language is open-source. If it isn’t, the language is going to go out-of-date soon which isn’t desirable considering the rapidity of the growth of AI.
The user community of a programming language plays a crucial role in determining the best language. Sharing of code, asking doubts to peers/colleagues if any, completing projects quickly, coordinating with other programmers, among many other things can be extremely easy if the programming language is popular and common.
Python (learn Python here) can easily be called the best programming language for AI, thanks to its massive user community and in-built libraries like TensorFlow, NumPy, Pybrain, etc. Even for coding unrelated to AI, Python is heavily used. Its syntaxes are one of the easiest to understand and super short. Python is free, open-source, and platform-independent. One shortcoming that most people who code in Python can relate to is the fact that Python is an interpreter based language (line by line error correction).
Java (here’s a Java course for you) is another on the list of best programming languages for AI. It’s known for its user-friendliness, fast debugging, and production of amazing graphics which might be highly important in the field of AI. The Virtual Machine Technology that Java has, makes it easier to implement the code in various Java-supported platforms. The main part of AI where Java is highly used is Data Analytics. Most search engine algorithms are also coded in Java. One major downside when it comes to Java is that it takes up more memory because of the huge Virtual Machine.
LISP is one of the oldest programming languages ever. It was developed in 1959 when it was the “winter” period for AI (the field was stagnant between the 1950s and 1980s). And when AI came into the picture again, it was first coded in LISP. Many people who love things vintage still code in this language. It doesn’t have a massive standard library collection and has a weird syntax because it’s been there for a long time, but it still has a massive user community, which is why it’s on the list.
R is a fairly new programming language and is often compared to Python. It’s gaining following and is even better than Python in a lot of aspects like handling large data better, for instance. R isn’t used for general purposes because it was developed to solve statistics-related problems in particular and therefore is curated just for AI. No other programming language is as efficient as R in this regard. Here’s an R course that you need to check out!
Prolog stands for “programming in logic” and is again another old programming language. This language mainly focuses on pattern matching, which can prove highly useful in the Deep Learning part of AI. If you aren’t a procedural programmer and think extremely logically, you should give this language a shot. It might seem like a bizarre language if you’re from a C/C++ background, however.
Julia was developed by MIT, mainly to carry out complex numerical computations, which is extremely important in AI. One major advantage when it comes to Julia is the fact that you can transform algorithms from research papers into code effortlessly and without any loss. It’s gaining immense popularity right now and is open-source too, which makes it one of the best languages for AI.
If you noticed, each programming language mentioned in the list is better than the others in carrying out specific tasks and focuses on different challenges of executing AI concepts. Choose your best programming language for AI carefully based on your need and switch between languages to complete the projects that you have with better efficiency.