7 AI Programming Languages To Choose From
Artificial intelligence hasn’t developed its own language yet, but even with using existing programming languages humanity has achieved great results. Just recollect the 2015 breakthrough of AlphaGo. It was the first time when a machine managed to beat a human being in the most difficult board game Go, which demands a high level of abstract thinking.
Let’s have a closer look at means that make artificial intelligence real.
Initial release: 1991, latest release: 2017
Python takes the first place in the list of AI development languages due to its simple and seamless structure. Simple syntax and rich text processing tool allowed it to become a perfect solution for NLP problems. Programmers can build neural networks in Python, and machine learning with Python is also much easier. Learn what else you can do with Python in our article.
- short development time (as compared to Lips, Java or C++);
- large variety of libraries;
- high level sytax;
- supposrts object-oriented, functional and procedural styles of programming;
- good for testing algorithms without implementing them.
Initial release: 1983, latest release: 2104
Influenced: Java, Python
The major advantage of C++ for AI is its speed, and one can find C++ among the fastest programming languages in the world. Since AI development demands lots of calculation fast-running programs are of ultimate importance. C++ is highly recommended for machine learning and neural network building.
-high level of abstraction;
- good for high performance;
- organize data according to object oriented pricniples;
- STL collection.
Initial release: 1959
Lisp, being the second oldest programming language in the world (after Fortran), still holds a top position in AI creating due to its unique features. For example, Lisp has a special macro system which makes possible to develop a domain specific level of abstraction and build the next level on it. Lisp in artificial intelligence development is known for its unique flexibility as it adapts to the problem you need to solve on the contrary to the other languages that are chosen because they can complete this or that task. Developers opt for Lisp in machine learning and inductive logic projects.
- fast prototyping capabilities;
-support for symbolic expressions;
- automatic garbage collection which actually was invented for the Lisp language;
- library of connection types including dynamically-sized lists and hastables;
- efficient coding due to compilers;
- interactive evaluation of components and recompilation of files while the program is running.
Initial release: 1972
Influenced: Mercury, XSB
Dialects: Edinburgh Prolog, ISO Prolog
The name of Prolog speaks for itself; it’s one of the oldest logic programming languages. If we compare it with other ... READ MORE Choosing a Cross-Platform App Development Company
Native, Web & Hybrid App Development
App development can generally be divided into three types: native, web and hybrid, i.e. cross-platform. Because of this, many companies face a hard choice: what is better for us? What is better for our clients? Should we choose iOS or Android? Or Windows? Or cross-platform? Or should we outsource? To decide what is best for your company, you need to set your goals, see which platform best suits your requirements and also fits your budget. Of course, Qubit Labs can help you with these decisions and find a top-notch team of specialists for a reasonable price.
Why Choosing Cross-Platform App Development?
If you think of it, these aren’t the only advantages cross-platform apps offer:
- The most effective functionality and customization for users.
- The development process isn’t limited to or dependent on one certain OS platform - developers can build an application that will work on multiple platforms, thus, kill two (or even more!) birds with one stone.
- They are a great option for developers who work on visually-intensive applications like games.
- One single development team can build solutions for your organization regardless of the type of the mobile device. Moreover, learning how to use one development tool is easier than handling many of them, and this will help you keep your costs down.
And, thanks to all of the above, cross-platform apps can help companies maximize the potential of their mobile presence, as well as help put an end to the iOS vs. Android debate!
Choosing a Cross-Platform App Development Company
Let’s say you and your team have made up your minds and have set your goals. You decided that what you need is a high-quality cross-platform app. When choosing an app development company, you want to be sure to get the best developers for the project. You start looking for outsourcing companies to develop the application for you. The first thing you will probably do is check development companies’ portfolios and references. But you may want to go deeper and find out, what tools the companies work with. This can help you understand, what type of company can fulfill your ideas better. Cross-platform developers usually work with these tools:
- Codeless tools - a super user (has better computer skills than an organization's average end user) or business analyst can use them to create a mobile app rapidly.
- Developer cross-platform - advanced tools to create cross-platform enterprise solutions; use languages such as C#.
Outsourcing To a Cross-Platform App Development Company
We talked a ... READ MORE