The advent of Artificial Intelligence and Machine Learning has led to increased personalization, better engagement and customer-centric solutions. Earlier, the datasets were numbers in plain sight. However, with time, data became the norm as businesses unearthed hidden insights to help improve decision-making.
With AI, businesses are more productive. They have outsourced mundane jobs and tasks to intelligent software solutions. As a result, business owners can focus on their core jobs.
However, choosing the right programming language to support your next gen AI app development is crucial. Planning your tech stack and hiring developers will depend on this step. Python is, hands down, developers' favorite when it comes to building ML or AI applications. However, if given a choice, many would choose C++ owing to the in-depth coding and better performance capabilities.
What would you choose if you were given a choice between Python and C++ to build your next AI application? This article is a guide that will help you make the right decision concerning the technology stack.
Python or C++: What to Choose for Next Gen AI App Development?
While most people prefer Python, it does face some competition from C++. The developers belonging to the old school are tempted to choose C++.
Let’s compare to see which programming language you should choose for AI application development.
1. Availability of Libraries
Most businesses hire Python developers for AI application development. As a result, there are many pre-built libraries for Python programming language.
Whether you want to improve the personalization or enhance the app engagement, you can use these libraries to design the interface, plan the backend and streamline the communication.
The pre-built codes help the developer enhance their productivity. On the other hand, when you use C++ to build an AI application, you must build the code ground up. There are no pre-written codes or libraries that you can use to create the application.
Even the smallest and finest interface piece, such as login buttons, must be coded from scratch. Regarding libraries, Python offers a great range that can enhance productivity.
2. Runtime Code
This is where C++ wins against Python. The runtime is when your syntax is converted into machine-interpretable code.
C++ ensures faster runtime code as compared to Python. As a result, the code is well-optimized and efficient.
As C++ is a static language, it offers greater runtime efficiency. The type checking for C++ languages is done during compile time. As a result, you can ensure minimal errors during runtime.
It also helps optimise the application's overall performance, as the statically typed language provides faster startup times.
3. Learning Curve
When you opt for the next gen AI app development, you might prefer an easy-to-use and impactful programming language.
Python is an easy-to-learn and popular language. The syntax is simple and accessible. However, that is different from C++. You might need an experienced developer who is well-versed in the programming language to help with syntax development.
It has a steeper learning curve, which means if you don’t have the foundation or the time, you may not be able to ace the language.
4. Community Support
When developing an AI application, solid backing from the community is essential. There will be use cases where you need help from other developers. You might want people who have worked in this niche to help you when you are stuck with the application.
That’s when community support acts as a boon. If more developers have worked in the niche, they can ensure you get some solution.
Python has solid backing from the community. It helps ensure the developers get the right support and help at the right time. However, that is different from C++. You will notice that this is an expert’s only programming language. The community isn’t that wide and strong. You may not find too many people with the requisite expertise to develop AI applications with C++.
5. Code Length
When you are writing a program using Python, you can use fewer lines of code to design the task. However, the same task will require a long and more complex code if you are working with C++. Again the scope of variables is limitless in Python, while it is restricted in C++.
The number of lines you need to write would impact your debugging. As a result, debugging the code becomes complex in C++, while it is easier with Python.
Eventually, it can impact the developer’s efficiency and app development speed.
6. Platform Compatibility
When choosing a programming language for your next AI application, you might want to consider whether they are compatible with different platforms. Python can easily fit into different platforms. It is compatible with web and mobile operating systems and browsers. If you write the code once, you can compile it for all systems.
However, C++ requires a specific compiler to optimize the code. This could be specific to the platform. For instance, the compiler may not work on all platforms. So, you will need to compile the code individually for the different platforms and operating systems. This can become time-consuming and expensive for the business.
7. Testing and Quality Assurance
When launching an app, you need to be assured of the quality. It is equally important that you are satisfied with the speed and performance of the application. Testing is crucial to ensure a bug-free app launch.
With Python, you can easily test the application and debug it faster. There are fewer lines of code and simple syntax. This makes creating test cases and defining the test plan easier with Python.
However, that is different from C++. You have to debug complex and long code. This can take up a long while. Additionally, the testing team should be well-versed in C++ to debug the code.
The testing workflow is smooth and efficient when you code using Python.
8. Data Visualization
It is important to consider visualizing the data for better interpretation and seamless coding. Python offers a variety of libraries that support data visualization through plotting and charts. It helps interpret the solutions better, and improves the coding ability of the developer.
You can also use data visualization tools to support your interface development.
Conclusion
Python has emerged as a winner between Python and C++ for the next gen AI app development. It offers extensive readability, simple syntaxes and better debugging solutions. With strong and pre-written AI-specific libraries, Python extends great application development capabilities to the end user.
A low learning curve, better testing abilities and community support highlight that Python is better than C++. Hire python developer with suitable expertise and experience.
If they worked in your niche and created a similar application, you can accelerate launch times and deploy a robust solution.
