Clarks shoes steps into digital
The 10 Best Programming Languages For AI Development In 2023
Since its launch, Artificial Intelligence has drastically changed everything in our world in unexpected ways. To the younger generation, AI is normal, as they've tested its amazing features since birth. However, the older generation can attest to this invention's numerous impressive changes. Undoubtedly, AI has improved the quality of our lives by instigating positive transformations in numerous sectors affecting humankind.
Businesses are employing AI technology and have since improved customer experience, general operations, and productivity. Its remarkable features, such as data analytics, smart-decision making, reduced errors, and automation, have proven to increase the ROI for companies. Indeed, most multinational corporations cannot survive in this era without AI due to its impact and applicability in their daily operations.
Among the many questions trending about AI, programming languages seem to resurface all the time. There is a need to develop this technology in order to enjoy its maximum benefits. However, this development journey begins by using an appropriate programming language. In this article, we will explore some of the ten best programming languages for AI development in 2023.
What is Artificial Intelligence?Artificial intelligence (AI) is a broad-ranging part of computer science that focuses on creating machines with the ability to carry out tasks with human intelligence. Although this technology has a myriad of approaches, the continual advancements in deep learning and machine learning are instigating a paradigm shift in all areas within the tech industry.
Machines using AI can form or advance the potential of the human mind. From the inventions of smart assistants like Alexa and Siri to the creation of self-driving automobiles, AI will forever remain a part of our daily lives. It is now the most sought-after technology in the business world.
How Does Artificial Intelligence Work?AI works by using the data uploaded into the system by its users. Its margin of error will depend on the quality and accuracy of this data. Once uploaded, the system will analyze the data for patterns and correlations and use it for forecasting. Therefore, you can improve your AI system's capabilities, reliability, and accuracy by feeding it with adequate and accurate data often. AI also develops the following three cognitive skills to boost its performance:
AI is designed to make life easier, from planning appointments to running your office or household and driving your car. So, imagine a case where your devices are intelligent enough to know precisely what you want and meet your needs. This will make your life extraordinary and stress-free, and you will have more time to yourself, right? Now, that is what AI technology is out to achieve.
Here are the ten best programming languages you can use to build competent AI tools and applications.
#10. RustIf you want a programming language that is quick, secure, and high-performing, Rust is the perfect option. Most developers consider it a great alternative for developing AI. The syntax of Rust and C++ are comparable. However, Rust exempts garbage collection, and it offers additional memory safety.
Rust is used as the backend programming language for several renowned systems like Yelp, Azure, npm, Dropbox, Discord, Firefox, Cloudflare, and Polkadot. It is ideal for AI development because it is effective in scientific computing due to its easier expression, memory safety, and speed.
#9. HaskellHaskell is an adjustable and expressive programming language. Its readiness for abstraction alleviates the wastage of time to debug errors during programming. This language appeals to most developers due to its type of system, great memory management, and code reusability abilities. However, it is admittedly lazy because it only evaluates codes if necessary. That is an advantage or disadvantage depending on your perspective. AI experts generally prefer Haskell because it is efficient and doesn't involve excessive typing.
#8. JuliaJulia is among the latest languages for developing AI. However, don't let that fact discourage you from employing it in your AI development projects. Despite being new and having a very small community, this language has qualified to be a part of the list of the best programming languages for AI due to its impressive graphics for data visualization and dynamic interface.
Its metaprogramming, memory management, and debugging features have enhanced its reliability in developing AI. Other notable features of Julia include the dynamic type system, distributed and parallel computations, and C-functions support.
Julia also has algorithm help, premade models, and various packages for probabilistic programming needed for AI development, such as:
R is a renowned language among professional and budding statisticians. Although it isn't the best language for artificial intelligence, it is extremely good at crunching digits. AI development involves complex processes of describing and evaluating numerical data. R performs better than Python in such cases as it can deal with complex mathematical formulas seamlessly. The essential R packages needed for developing AI include:
C++ is a low-level programming language that functions effectively with machines and hardware, but not theoretical software. Practically, its low-level programming can successfully handle AI models in production. With C++, it is possible to make neural networks and convert human language into code that computers can understand. In addition, C++ is highly recognized in the world of AI because it is widely used to create most machine-learning libraries.
#5. LISPLISP is the oldest language used for AI development, as it originated in 1958. Over the years, this programming language evolved to deal with AI-related issues. Even in 2023, it can be integrated into AI development due to its complex libraries and syntax. Since it's complicated, only a few developers consider using it. LISP is a great option for various AI projects due to its exemplary expertise in performing the following tasks:
LISP is renowned for its versatility in turning thoughts and ideas into reality.
#4. PrologProlog has existed since 1972. It has stood the test of time by evolving with technology. Prolog is famous for its rational and declarative program that is essential in processing natural language. IBM Watson has used it to answer their clients' questions, thereby exposing Prolog's potential in dealing with such situations.
The outstanding qualities of this language include a tree-based data structuring feature, pattern-matching ability, and meta-level reasoning. Pattern matching is vital for smart database search, language processing, and computer vision.
With its in-built list-handling feature, Prolog is adept in analytics, problem-solving, and improving application performance. While using Prolog for AI programming, the developer will establish a set of regulations and objectives. Prolog, through pattern matching, will find the link between these two and generate the expected outcome.
#3. JavaScriptMost developers have used JavaScript to create more dynamic and secure websites. However, it is also an ideal programming language for AI development. JavaScript gives developers unlimited access to both the backend and frontend operations, making it easier to navigate the development of the AI software. This language guarantees a rapid AI development process, increased performance, and enhanced security.
JavaScript allows a synchronized operation and interaction with various source codes like CSS and HTML. That is a vital feature for AI development. Moreover, this programming language has a big community that can assist developers. The difficulty of developing AI is also lessened by JavaScript libraries such as Underscore.Js, React.Js, and jQuery.
#2. Java
© Provided by History Computer Java is an object-oriented language well suited for AI development. ©REDPIXEL.PL/Shutterstock.Com Java is a highly popular programming language with distinct qualities required for a successful AI development process. It is an object-oriented language with straightforward debugging and syntax. This programming language has an exemplary track record for delivering exceptional mobile apps, software, and AI development. Its simplicity also attracts many developers.
While programming AI, fast runtimes and quicker execution are essential. Fortunately for Java users, it has these abilities. It also provides a seamless integration of key analytic frameworks and an outstanding production value. Java's Virtual Machine Technology makes its implementation on multiple platforms quite simple. With the write once, run anywhere methodology, you can develop and compose your AI application on a single platform and implement it on others.
The advantages of using Java for AI programming include the following:
Additionally, Java can develop anything ranging from deep learning to data analysis, machine learning, and natural language processing. New developers can also get reliable guidance and assistance from the rich and active Java community that hosts seasoned developers worldwide.
#1. PythonPython is regarded as the most suitable programming language for Artificial Intelligence. It is widely employed in networking and desktop applications, web, scientific computing, data science, and AI machine learning. It has a rich library of Keras, MXNet, TensorFlow, PyTorch, Pybrain, and Scikit-learn, which equips it for AI development.
Furthermore, Python has enriched text processing features, scripting with modular designs, and simple syntax that functions best for AI programs and NPL (Natural Language Processing). It's also easy to learn and master the Python language, as it is short, clear, and straightforward. Additionally, it has a vast following of users with an active support base.
Most companies with a worldwide reputation prefer Python above every other programming language. Some of the businesses using it in their systems include Facebook, Google, Instagram, IBM, Netflix, Pinterest, Amazon, Google, and NASA. This, among many other reasons, makes Python the most popular programming language for AI development in 2023.
Final ThoughtsArtificial Intelligence is the future of technology as it is incorporated into everything touching our lives. AI technology has grown in popularity, and many people are adopting it to improve their businesses and personal lives. Fortunately, developers can use several programming languages to enhance AI tools and applications. The best language for you is the one that matches your competence and experience. As a beginner, it is best to opt for a language that will lessen the complexity of the development process.
The post These Are the 10 Best Programming Languages for AI Development in 2023 appeared first on History-Computer.
Programming Languages And Software Engineering
Improve existing software. Create technologies that make everyday life better. Use computer science, and smartphones to capture more data from citizen scientists. Software is everywhere: interfaces to make daily work more manageable on mobile devices, deliver medicine to cancer patients, and help airports run smoothly.
We develop computer science education software, citizen science software in the natural environment, and software synthesis and verification. Our research also focuses on communication for software engineers.
"The availability of smartphones make collection and sharing data easier, faster, and more accurate."Robert Pastel, associate professor, computer science
Current ProjectsProject Title: GIS App Development
Investigators: Robert Pastel, Don LaFreniere (Social Sciences)
Overview: Geographic Information Systems (GIS) has launched new era in mapping and map making. This project uses both commercial (esri) and open source GIS to develop web apps.
Project Title: Offline Web App Implementation
Investigator: Robert Pastel
Overview: Cloud computing is pervasive, but few tools and examples exist for working offline. This project develops offline web apps and tools for developing apps.
Project Title: Citizen Science App Development
Investigator: Robert Pastel
Overview: Citizen scientist are varied group, making design and development of citizen science apps a challenge. This project develops citizen science app for sponsoring scientists and non-profit organizations.
ResearchersExplore Computer Science Research
Research Groups What's NewThe Advantages Of Knowing Many Programming Languages
Sue Smith started writing in 2000. She has produced tutorials for companies including Apex Computer Training Software and articles on computing topics for various websites. Smith has a Master of Arts in English language and literature, as well as a Master of Science in information technology, both from the University of Glasgow.
Comments
Post a Comment