What are the Best Programming Languages to Develop your AI Solution on?

What are the Best Programming Languages to Develop your AI Solution on?

From humble chatbots on web pages to the conception of autonomous vehicles, Artificial Intelligence (AI) has been gaining importance over the past decade driving major changes across industries, businesses, and even our daily lives. It is undoubtedly an integral part of the disruptive digital transformation that we all talk about. 

What we have witnessed of AI up till now is just a teaser of its true potential, though. Even though in the last couple of years since the pandemic, AI penetration has been on the rise, it is still in its early stage. But it is poised for a big leap in the coming years with the global market for AI reaching $596 billion in revenues by 2025. 

There is no doubt that AI solutions are the need of the hour. Whether you want to transform your business, improve customer experience, or create ripples in the digital world, AI is the answer. But when it comes to developing cutting-edge AI solutions, which programming languages are in trend currently?

Over the years, programming languages have evolved making way for newer, more powerful languages. While this might continue, let us see which major programming languages are favored in today’s world for developing AI solutions. Here’s the top 10.

Python 

Python is the top choice of developers for AI solutions. Big names such as Google, Amazon, Instagram, Netflix, all use Python for their AI solutions. It is a high-level programming language that can deal with complex arithmetic expressions, arrays, objects, etc. It is also interpreted language. So, it does not need to be compiled/converted to machine language before executing the code.

Developers also love Python because it can be used across different domains and is available for all operating systems. It is platform-independent and supports both object oriented programming and scripting. This versatile programming language has pre-built specialist libraries such as Numpy, Pybrain, Pytorch, etc. which make it a great choice for complex AI projects.  

Lisp

Lisp, also written LISP, is derived from ‘List Processing’, which happens to be one of its applications. Developed back in 1958, it might surprise some that this programming language is still not only relevant but also useful for developing advanced AI solutions. 

The things that go against Lisp are its complex syntax and expensive libraries. Hence, despite a lot of potential, this language is often sidestepped. But that by no means undermines the capabilities of this programming language. 

Lisp is definitely a powerful language to have stood the test of time even as hundreds of other programming languages were lost in oblivion. It is an adaptable language that is designed to evolve. With smart functionality such as dynamic objects and rapid prototyping, Lisp is particularly useful in AI applications.

Java

The list of powerful programming languages would be incomplete without this popular, all-pervasive programming language. Used for server-side AI applications, Java is preferred for its cross-platform functionality. 

Java can be used to create neural networks, machine learning solutions, genetic programming, multi-robot systems, and complex algorithms. Also, its object oriented programming approach, scalability, and flexibility make it one of the top choices for AI development. 

Java’s popularity can also be attributed to it being a language that is easy to learn. Also with a reliable community of highly skilled Java developers, it is easy to get help making developers feel more confident in using this programming language.

R

More than anything else, R is preferred for the complex calculations that it supports. When we speak of AI, Big Data follows. And for handling calculations that involve a huge volume of complex data, R comes in pretty handy. 

R is used primarily when it comes to statistical computing. It is great at arriving at patterns, reporting changes, and predicting trends. It is an excellent choice for applications that involve NLP, reasoning, and databases. 

R is used extensively in industries such as medicine, finance, and education. Google, Twitter, Uber, Microsoft famously use R. However, R is a difficult language to learn, which kind of dents the popularity of this otherwise powerful language.

Prolog

Too bad that Prolog is rarely used in commercial AI applications. Developed half a century ago, it’s amazing how well-suited this language is for NLP and problem-solving. Prolog was the first programming language used in chatbot applications, thanks to its capability of handling rules, facts, and queries.

What Prolog lacks in versatility, it more than makes up in its ability to understand patterns and structure data. It is likely to bounce back and become a part of mainstream programming languages for AI solutions. About time, too. It has tremendous potential in developing advanced chatbots, virtual assistants, and other applications. 

Julia

Julia is new on the AI scene but it is full of promise. With a dynamic interface, amazing graphics for data visualization and powerful numerical analysis, it is gaining popularity. Even though it does not enjoy the following that Java and Python do, its loyal developer base is on the rise.

It supports macro programming, multiple dispatches, and strong computational ability. It is great for use in Machine Learning and supports probabilistic programming. It has pre-built packages which make it easy to use for several complex functions.

Scala

Scala is easy to use and is compatible with two other popular programming languages – Java and JavaScript. No wonder then that developers are drawn to Scala. But its ease is not its only redeeming quality. Scala is a very powerful programming language and is capable of performing higher-order functions and complex pattern matches. 

Scala’s other claim to fame is its scalability. It can handle complicated algorithms combined with increasing amounts of data making it an ideal choice for AI functions that involve high volumes of data. It is gaming popularity for creating Machine Learning models.

C++

C++ is known for its high performance. It is suitable for AI development because of the promise of high performance and also because of its ability to perform fast calculations. Agreed it is a low-level programming language. But that makes it apt for simple AI models.

C++ is also famously well-suited for gaming applications. With AI-ML libraries such as Shogun, DyNet, Caffe, etc., modern C++ can be used in AI apps. Used by Google, Lyft, Telegram, and several others, it is a strong contender for AI development.

JavaScript

With AI libraries, JavaScipt can be sued to build machine learning and deep learning applications. Programming in JavaScript might not be as easy as coding in Python. But skilled developers can work wonders with JavaScript making it possible to bring AI right into our web browsers. 

Above all, JavaScript is versatile and stable. Continuous developments and efficiency find this language becoming a preferred choice for AI development. It also promises better security, performance, and faster development time. Another thing going for JavaScipt is the increasing pool of highly skilled talent.

Haskell

Haskell is an efficient programming language. Whether it is the memory management, the reusability of the code, or the lines of code itself – everything is efficient and optimized. It is also a functional language making it a safe bet for using in AI solutions. 

Haskell can be used in neural networks and machine learning. It is also good with algorithms and logical reasoning. Due to its reliability and safety, developers are drawn to Haskell. But to be honest, it hasn’t yet realized its true potential, especially in the context of AI development. But this may soon change and Haskell might get its rightful due as a preferred programming language for AI development solutions.

Choosing the right programming language

Building a cutting-edge AI solution requires selecting the most well-suited technologies to support it. With new technologies, programming languages, and trends rocking the digital world, an expert opinion for selecting the right programming language is something everyone can appreciate. 

If you, too, want to get the best out of AI and develop advanced solutions, getting your requirements assessed by an expert can help. Contact TaAp Exchange for a free Gap Assessment and let our technology advisors chart your roadmap for disruptive, AI-assisted technology transformation.  

Samarth Gupta

Samarth Gupta

Disrupting Traditional Tech Recruitment | Transforming How Software Engineers Are Hired In Bulk

Follow Me:

Resources

What are the Best Programming Languages to Develop your AI Solution on?

/ by

From humble chatbots on web pages to the conception of autonomous vehicles, Artificial Intelligence (AI) has been gaining importance over the past decade driving major changes across industries, businesses, and even our daily lives. It is undoubtedly an integral part of the disruptive digital transformation that we all talk about. 

What we have witnessed of AI up till now is just a teaser of its true potential, though. Even though in the last couple of years since the pandemic, AI penetration has been on the rise, it is still in its early stage. But it is poised for a big leap in the coming years with the global market for AI reaching $596 billion in revenues by 2025. 

There is no doubt that AI solutions are the need of the hour. Whether you want to transform your business, improve customer experience, or create ripples in the digital world, AI is the answer. But when it comes to developing cutting-edge AI solutions, which programming languages are in trend currently?

Over the years, programming languages have evolved making way for newer, more powerful languages. While this might continue, let us see which major programming languages are favored in today’s world for developing AI solutions. Here’s the top 10.

Python 

Python is the top choice of developers for AI solutions. Big names such as Google, Amazon, Instagram, Netflix, all use Python for their AI solutions. It is a high-level programming language that can deal with complex arithmetic expressions, arrays, objects, etc. It is also interpreted language. So, it does not need to be compiled/converted to machine language before executing the code.

Developers also love Python because it can be used across different domains and is available for all operating systems. It is platform-independent and supports both object oriented programming and scripting. This versatile programming language has pre-built specialist libraries such as Numpy, Pybrain, Pytorch, etc. which make it a great choice for complex AI projects.  

Lisp

Lisp, also written LISP, is derived from ‘List Processing’, which happens to be one of its applications. Developed back in 1958, it might surprise some that this programming language is still not only relevant but also useful for developing advanced AI solutions. 

The things that go against Lisp are its complex syntax and expensive libraries. Hence, despite a lot of potential, this language is often sidestepped. But that by no means undermines the capabilities of this programming language. 

Lisp is definitely a powerful language to have stood the test of time even as hundreds of other programming languages were lost in oblivion. It is an adaptable language that is designed to evolve. With smart functionality such as dynamic objects and rapid prototyping, Lisp is particularly useful in AI applications.

Java

The list of powerful programming languages would be incomplete without this popular, all-pervasive programming language. Used for server-side AI applications, Java is preferred for its cross-platform functionality. 

Java can be used to create neural networks, machine learning solutions, genetic programming, multi-robot systems, and complex algorithms. Also, its object oriented programming approach, scalability, and flexibility make it one of the top choices for AI development. 

Java’s popularity can also be attributed to it being a language that is easy to learn. Also with a reliable community of highly skilled Java developers, it is easy to get help making developers feel more confident in using this programming language.

R

More than anything else, R is preferred for the complex calculations that it supports. When we speak of AI, Big Data follows. And for handling calculations that involve a huge volume of complex data, R comes in pretty handy. 

R is used primarily when it comes to statistical computing. It is great at arriving at patterns, reporting changes, and predicting trends. It is an excellent choice for applications that involve NLP, reasoning, and databases. 

R is used extensively in industries such as medicine, finance, and education. Google, Twitter, Uber, Microsoft famously use R. However, R is a difficult language to learn, which kind of dents the popularity of this otherwise powerful language.

Prolog

Too bad that Prolog is rarely used in commercial AI applications. Developed half a century ago, it’s amazing how well-suited this language is for NLP and problem-solving. Prolog was the first programming language used in chatbot applications, thanks to its capability of handling rules, facts, and queries.

What Prolog lacks in versatility, it more than makes up in its ability to understand patterns and structure data. It is likely to bounce back and become a part of mainstream programming languages for AI solutions. About time, too. It has tremendous potential in developing advanced chatbots, virtual assistants, and other applications. 

Julia

Julia is new on the AI scene but it is full of promise. With a dynamic interface, amazing graphics for data visualization and powerful numerical analysis, it is gaining popularity. Even though it does not enjoy the following that Java and Python do, its loyal developer base is on the rise.

It supports macro programming, multiple dispatches, and strong computational ability. It is great for use in Machine Learning and supports probabilistic programming. It has pre-built packages which make it easy to use for several complex functions.

Scala

Scala is easy to use and is compatible with two other popular programming languages – Java and JavaScript. No wonder then that developers are drawn to Scala. But its ease is not its only redeeming quality. Scala is a very powerful programming language and is capable of performing higher-order functions and complex pattern matches. 

Scala’s other claim to fame is its scalability. It can handle complicated algorithms combined with increasing amounts of data making it an ideal choice for AI functions that involve high volumes of data. It is gaming popularity for creating Machine Learning models.

C++

C++ is known for its high performance. It is suitable for AI development because of the promise of high performance and also because of its ability to perform fast calculations. Agreed it is a low-level programming language. But that makes it apt for simple AI models.

C++ is also famously well-suited for gaming applications. With AI-ML libraries such as Shogun, DyNet, Caffe, etc., modern C++ can be used in AI apps. Used by Google, Lyft, Telegram, and several others, it is a strong contender for AI development.

JavaScript

With AI libraries, JavaScipt can be sued to build machine learning and deep learning applications. Programming in JavaScript might not be as easy as coding in Python. But skilled developers can work wonders with JavaScript making it possible to bring AI right into our web browsers. 

Above all, JavaScript is versatile and stable. Continuous developments and efficiency find this language becoming a preferred choice for AI development. It also promises better security, performance, and faster development time. Another thing going for JavaScipt is the increasing pool of highly skilled talent.

Haskell

Haskell is an efficient programming language. Whether it is the memory management, the reusability of the code, or the lines of code itself – everything is efficient and optimized. It is also a functional language making it a safe bet for using in AI solutions. 

Haskell can be used in neural networks and machine learning. It is also good with algorithms and logical reasoning. Due to its reliability and safety, developers are drawn to Haskell. But to be honest, it hasn’t yet realized its true potential, especially in the context of AI development. But this may soon change and Haskell might get its rightful due as a preferred programming language for AI development solutions.

Choosing the right programming language

Building a cutting-edge AI solution requires selecting the most well-suited technologies to support it. With new technologies, programming languages, and trends rocking the digital world, an expert opinion for selecting the right programming language is something everyone can appreciate. 

If you, too, want to get the best out of AI and develop advanced solutions, getting your requirements assessed by an expert can help. Contact TaAp Exchange for a free Gap Assessment and let our technology advisors chart your roadmap for disruptive, AI-assisted technology transformation.  

To top