So, you use ChatGPT to code faster and more efficiently? That’s great, but why not take it one step further and upgrade your development game with artificial intelligence tools?
Artificial Intelligence (AI) technology is making strides in the world of software development. And ChatGPT is only one tool among the vast selection of AI-powered software designed for developers. With so many choices available, finding the right tools to fit your needs can be tough.
We’re here to help! This blog aims to cover 10 of the most powerful AI tools for software development. Whether you need a tool to manage large data sets or want to speed up your coding process, any one (or more) of these AI-powered solutions will surely help you reach your goals with ease.
How Can an AI Tool Help?
Before we jump in, let’s briefly discuss the benefits of using an artificial intelligence tool for software development. To put it simply, AI can make a significant difference in how quickly and accurately you can complete projects.
The areas in software development where AI tools can help include:
Automation
AI software and tools are revolutionizing automated debugging by detecting patterns to identify and categorize error types. With deep learning algorithms, errors can be quickly flagged, and the debugging process can be accelerated.
With such tools, developers don’t have to analyze code or detect issues manually—AI can take care of it for them. This increases the speed and accuracy with which software development projects can be completed.
Furthermore, AI can even compete with software developers and learn how to fix each type of bug. Post-training, the machine can automatically detect and correct numerous mistakes, similar to the text auto-correct feature found on smartphones.
Swift code generation
The amount of time your developers will save from coding is invaluable. ChatGPT, an AI assistant we all know (and love), can generate more robust code in a fraction of the time it would take a human coder.
The limited resources available to most developers make artificial intelligence software a must-have for any development team. AI software can generate code from natural language instructions, making it much easier and faster to program systems and applications.
You should not think that these solutions cannot handle ambiguity. However, once AI-based software masters the underlying patterns, it could generate programs by assembling predefined modules like LEGO pieces instead of merely completing code.
Smart testing
Testing a software product involves running multiple scenarios, identifying errors, and then fixing them. This can be a time-consuming process for developers, but it is essential to accomplish to develop a high-quality output.
This is when AI-powered tools come to the rescue!
AI software can learn how to test products in an automated manner using supervised learning algorithms and cloud-based platforms. Some tools can analyze previous logs to automatically generate a list of test cases to run through the system.
Moreover, the best AI tools can project the testing outcomes without actually performing the tests. This not only saves time but also reduces the risk of manual errors.
Strategic designing
Software developers invest significant time in discussing and selecting product features and functionalities. This involves brainstorming and assessing ideas, determining the best functionalities to meet user needs, and identifying efficient implementation methods.
That’s why using artificial intelligence tools is essential!
AI software development tools, trained on past projects and business factors, can analyze existing software and find solutions that satisfy both clients and software engineers. By considering user reviews of similar solutions and client feedback, these tools can even create a hierarchy of features to ensure the success of your software product.
Deployment and operations
The process leading to the launch of a software product is long and complex. It often involves the manual evaluation of each new feature, version, or component before its deployment, which can be time-consuming for developers.
By using AI tools integrated with DevOps, this process can be shortened significantly. The software will automate the comparison between versions and identify errors quickly with automated testing procedures.
On top of that, AI software can also reduce the complexity of configuration management and optimize infrastructure resources. As long as you find the right tool for your project, you should be able to deploy and operate your product in no time.
So, we move forward to the actual AI tools available to developers!
10 AI Tools for Software Development Process
Gartner reports that around 37% of companies implement AI to manage their operations. This number is expected to grow in the coming years, given that the usage of artificial intelligence by businesses increased by a huge 270% between 2015 and 2019.
To keep up with the tech industry’s trend, here are 10 of the top-notch AI tools that software developers should consider for their projects:
1. Microsoft Azure AI Platform
As you may know, Azure is already a well-established cloud platform, and its AI capabilities are no exception.
The Microsoft Azure AI Platform offers a comprehensive suite of tools and services to support various AI development needs. A standout feature of the product is its pre-trained neural networks that excel in tasks such as object and pattern recognition in video streams, language translation, text and sentiment analysis, and image tagging.
In addition to the neural networks, the platform provides a robust data layer with services tailored for structured and unstructured data. This means you can seamlessly integrate AI capabilities into your applications, regardless of the data type or format you’re working with.
What makes this tool great:
- Developing new open-source Machine Learning algorithms and software solutions is easy
- Provides cross-platform integration with data accessibility across a wide range of platforms
- Supports popular programming languages like Python
- Allows customizable AI apps and agents, including pre-trained AI models for Vision, Speech, and Language through Azure Cognitive Services.
2. TensorFlow
Right now, TensorFlow is the most popular deep learning library out there. It’s a machine learning framework by Google that’s super Python-friendly and open-source too.
It’s also one of the best AI development tools because it makes numerical computation a breeze and helps you make more accurate predictions about the future. Developers can also easily construct neural networks and create graphical visualizations using Tensorboard.
One of the most fascinating aspects of Tensorflow is that you can write a program in Python and run it seamlessly on your CPU or GPU. This eliminates the need to write your program in C++ or CUDA to run on GPUs.
What makes this tool great:
- TensorFlow Serving framework allows deploying trained models to production
- Developers can focus on application logic while TensorFlow handles the backend
- Offers a wealth of trained models, tutorials, and documentation
- Provides visualization capabilities for debugging and tracking the training process
3. H2O.AI
H2O.AI is an open-source deep learning platform that focuses on delivering valuable insights and aiding business decision-making through advanced analytics.
This versatile tool offers two versions: the standard H2O, which is open source, and Sparkling Water, a paid version with enhanced features. It provides a range of applications, including predictive modeling, risk and fraud analysis, insurance analytics, advertising technology, healthcare, and customer intelligence.
H2O.AI is a business-oriented AI software designed to help you extract meaningful insights from your data and make informed decisions. It supports multiple programming languages like Python, R, Java, Scala, CoffeeScript, and JSON, making it accessible and adaptable for developers.
What makes this tool great:
- Offers big data capabilities for accessing, analyzing, and processing large datasets
- Advanced security and data governance to ensure compliance and protect sensitive data
- Provides powerful machine learning algorithms
- Has a robust platform and supportive community that provides the necessary resources
4. BigML
BigML is designed to make it easy to create and train models using your data, generate valuable predictive insights, or utilize them directly in your business operations.
One of the notable strengths of BigML is its ability to efficiently train models on large datasets, providing quick results even with vast amounts of data. While it is a paid service, there are no limitations on data or features, and training times for datasets can be completed within minutes.
BigML is especially beneficial for companies that may not have extensive expertise in machine learning but still want to explore AI solutions, develop prototypes, and gain a deep understanding of large datasets at scale.
What makes this tool great:
- Offers specialized features such as the “Gallery” for showcasing models, “PredictServer” for programmatically making predictions, and the WhizzML programming language for advanced customization
- Easy integration with Google Sheets allows for seamless data integration and analysis
- Provides useful libraries and open-source command-line tools
- Offers interpretable and exportable machine learning models
5. IBM Watson
IBM Watson is a remarkable tool that brings question-answering capabilities to software development. Watson is designed to support the SUSE Linux Enterprise Server 11 OS using the Apache Hadoop framework, making it a powerful and versatile addition to our development toolkit.
One of the standout features of IBM Watson is its deep understanding of core concepts once the model is trained. This robust system is built to make business processes smarter and more efficient, leveraging the advanced AI capabilities of IBM, a technology giant renowned for its expertise in the field.
The availability of industry-specific AI solutions makes IBM Watson even more impressive. IBM has tailored Watson for various sectors such as healthcare, oil & gas, advertising, financial services, media, and Internet of Things (IoT).
What makes this tool great:
- Incorporates Natural Language Processing (NLP) capabilities known as Watson Natural Language Understanding (NLU) for advanced language understanding and analysis
- Speech-to-Text capabilities allow developers to integrate speech-recognition functionalities into their applications
- Watson Assistant allows for the creation of AI-powered conversational interfaces
- Watson Discovery, an AI-powered search technology, enables the retrieval of information from various data silos
6. Caffe
Developed by Berkeley AI Research, Caffe offers a powerful and open-source machine learning framework. It allows developers and coders to define, design, and deploy their software products with ease.
What sets Caffe apart is its focus on expression, speed, and modularity. Developed by the Berkeley Vision and Learning Center (BVLC) with contributions from the community, Caffe has become the foundation for various projects, including Google’s DeepDream. With a BSD license and a C++ library, it provides a Python interface, making it accessible and adaptable for both academic research projects and industrial applications.
Caffe’s impressive processing power, capable of handling over 60 million images per day, solidifies its position as one of the leading tools in the field of Artificial Intelligence.
What makes this tool great:
- Fast and code-free deep neural networks application for image classification and regression tasks
- Extensible codebase with contributions from over 1,000 developers
- Out-of-the-box support for common layer functions like convolutions, fully-connected layers, and ReLU activation
7. PyTorch
PyTorch, an AI system developed by Facebook, has gained significant traction since 2017 and continues to grow in popularity. With over 22k stars on GitHub, it is an open-source framework accessible to developers worldwide.
In the realm of AI tools, PyTorch stands as a strong contender. Built on Python, it shares similarities with TensorFlow, particularly in terms of project scope. However, PyTorch shines when it comes to faster development. If your priority is efficient and agile development, PyTorch is the ideal choice.
On the other hand, TensorFlow may be better suited for larger and more complex projects.
What makes this tool great:
- Supports debugging tools like pdb and ipdb, and its runtime computational graph enables debugging using Python IDEs like PyCharm
- Python interface and powerful APIs boost developer productivity, automating tasks and supporting Windows and Linux
- Vibrant community with libraries for computer vision, reinforcement learning, and NLP
8. Keras
Keras is a powerful and user-friendly AI model tool for building and training neural networks. Its simplicity and effectiveness make it an excellent choice for image recognition and natural language processing tasks.
If you prefer the Python way of doing things, Keras is the perfect fit. It provides a high-level interface for working with neural networks while utilizing the capabilities of TensorFlow or Theano as its backend.
Whether you need to select the right architecture, leverage pre-trained weights, or fine-tune your network for optimal results, Keras simplifies the process. It also offers an abstract structure that can be easily converted to other frameworks, ensuring compatibility and performance.
What makes this tool great:
- Easy-to-learn and user-friendly API to provide a simple start with deep learning
- Supports multiple backends, including TensorFlow, Theano, and Microsoft CNTK
- Provides a wide range of pre-trained models, including pre-trained weights
9. Infosys Nia
Infosys Nia is a platform that allows us to build AI-powered applications easily.
One of the standout features of Infosys Nia is its ability to accumulate and organize organizational data from legacy systems into a self-learning knowledge base. Business analysts and software developers can leverage this knowledge base to create high-performing and scalable machine learning models.
You can also build AI-powered chatbots using Nia, giving your app access to the enterprise knowledge repository and enabling automation through a conversational interface.
What makes this tool great:
- Nia Advanced ML offers a broad range of ML algorithms that operate at speed and scale
- Build AI-powered chatbots with access to the enterprise knowledge repository
- Integrate Nia data, a robust analytics solution, into your AI app
10. Google Cloud Platform
Google Cloud AI Platform revolutionizes AI capabilities for software dev with seamless integration to popular frameworks like TensorFlow. Effortlessly develop and deploy ML projects with its convenient toolchain and portable ML pipelines through Kubeflow for both on-premise and cloud environments.
This platform goes beyond ML, offering impressive capabilities in NLP. Its NLP API enables advanced text analysis, uncovering meaning and structure. It provides speech-to-text and text-to-speech functionalities, supporting over 120 languages for audio-to-text conversion and generating natural-sounding speech from text.
The platform also excels in vision capabilities, allowing you to derive insights from images. With its REST and RPC APIs, you can detect objects and faces and even read printed or handwritten text.
What makes this tool great:
- Provides the AI Hub, a catalog of reusable ML models based on popular frameworks
- Offers pre-configured Deep Learning VM images that can be quickly deployed on the cloud
- Deploying ML workflows becomes scalable and straightforward with Kubeflow Pipelines
Let’s Make Your AI App!
The buzz around artificial intelligence in the tech industry is only getting louder, and now is the perfect time to jump in.
With the right tools and team at your disposal, you can create amazing artificial intelligence software with ease. That’s where we come in!
Here at StarTechUP, we provide an experienced and motivated team of developers, data scientists, and AI experts to ensure your next project meets or exceeds your expectations. We take advantage of various tools to deliver the best possible custom software solution and make sure you get the most out of artificial intelligence!
Contact us today to get started!
