5 Best Programming Languages For AI Development
Technologies keep evolving constantly. With each advancement, they bring something new for their users. Artificial technology (AI) is one such technology. It focuses on making computers smart enough to work and think like humans. Benefits of Artificial Intelligence are numerous. With use of AI, enterprises can achieve great success. It has brought a high level of smart technology to many industries, and it is growing. Here are some statistics to show how famous AI is now or could be in near future.
- By 2025, the market for AI will increase by $190 billion (Source).
- A report by Forrester states cognitive technologies like robots, AI applications, and machine learning will develop 9% of new jobs in the U.S by 2025 (source).
- The below images will show a clear picture of how Artificial Intelligence is gaining fame.
Artificial Intelligence Programming LanguagesThere are five main languages that are used for AI development. They are Java, Python, C++, Lisp and Prolog. These programming languages for AI are capable of handling various need/requirement of a project. The ultimate choice regarding the language rests on the developer, product’s features and functionality, and what benefits of artificial intelligence they want in the app. Let’s take a look at the languages:
1. PYTHONPython is the best Artificial Intelligence programming language. It is the favorite language due to its syntax simplicity and versatility. For machine learning, Python is a better alternative than C++ and Java as it is less complex. It is best suited for AI development because:
- It is portable; you can use it on Linux, Windows, Mac OS, and UNIX.
- It is an interactive, modular, dynamic and high-level language which makes it a fan-favorite.
- Python is Multi-paradigm programming. It supports object-oriented, procedural and functional programming styles.
- It has a simple function library and ideal structure.
Pros• Python has an extensive range of library and tools. • You can test algorithm without implementing it • Python increases productivity of the programmer as it supports object-oriented design. • Python development process is quicker than Java or C++.
- Developers who are familiar with Python and love it find it difficult to adjust to other programming languages for AI.
- Python uses a translator which can make compilation slower in AI development.
- If you are using Python for mobile AI apps, then it is a waste of time. It is because of its weak mobile computing language.
2. C++Since, C++ is the fastest computer language; its speed is best suited for time-sensitive AI programming. C++ executes commands fast and has less response time. You can apply this to the development of search engines and video games. It is great for AI because:
- It allows extensive algorithm use and is efficient when it comes to using statistical AI techniques.
- It allows re-use of codes/programs due to inheritance and data hiding. It saves time and money.
- Another important factor is that C++ supports re-use of programs in development due to inheritance and data-hiding thus efficient in time and cost saving.
- It is efficient in solving complex AI problems.
- It has a rich programming tools collection.
- It can’t handle multitasking
- C++ follows the bottom-up approach. It makes the language complex. It means new developers will take time to learn it. It would be hard for them to write AI programs.
3. JAVAAnother popular Artificial Intelligence programming language is Java. It is a multi-paradigm language following object-oriented principles and WORA. It can run on multiple platforms that can support it without compilation requirement. Most developers globally use Java for AI and other application development. It is quite easy to learn and has a big community to help you.
- It is highly portable due to Virtual Machine Technology
- Easy to use, understand and debug.
- It eases the developer’s work with its automatic memory manager.
- Java is slower in execution, especially when compared to C++. Also, its response time is high.
- If using on older platforms, you would require installing new hardware and software.
- It is still developing when it comes to AI. So, it’s an immature programming language for AI.
4. LISPAnother language for AI development is LISP. It’s a computer programming language, and after FORTRAN, it is the second oldest language. It is a strong and dynamic AI programming language. Developers prefer it the most due to the liberty it offers to them. LISP is great for AI applications because:
- It is fast to prototype and experiment
- It has a unique macro system. It aids the exploration and implementation of different intellectual intelligence levels.
- It is quite efficient in providing a solution to a problem because it adapts easily to the code.
- It is best suitable for machine learning and inductive logic projects.
- It is Fast and efficient in coding
- It has a garbage collector as LISP has its own automatic memory manager
- It provides maximum use by having full control over systems.
- Not many developers know how to use LISP
- Since Lisp is a vintage artificial Intelligence programming language, it requires new software/hardware integration for working.
5. PROLOGProlog is another old language and is apt for use as a programming langue for AI. Similar to Lisp, this computer language primary function is AI development. It is a flexible framework which makes working with it easy and exciting for developers. Prolog is a rule-based and declarative language containing facts and rules that govern the AI coding language. It supports these features for AI programming:
- Pattern Matching
- Tree-Based data structuring and,
- Automatic backtracking
- It provides a built-in list that is essential for representing tree-based data structures.
- It is great for fast AI modules that are released frequently
- It lets you create a database simultaneously to a running program.
- It has no standard form. Thus, some features don’t look same after implementing, wasting the efforts of developer.