7 Best AI Software Development Tools (2022)
Software application is one of the most common activities distributed in organizations, and its use has only increased over the years. Software development is a complex and difficult task, the process requiring ideation, product definition, coding, strategic design, quality assessment, etc. If mistakes are made during these steps, it may mean that the whole process needs to be restarted.
Because of these challenges, many of today’s top organizations are turning to artificial intelligence (AI) and machine learning (ML) to drive better results.
Here are the top 7 AI software development tools:
Topping our list of the 7 best AI software development tools is Google Cloud AI Platform, which helps you train your machine learning models at scale, host your trained model in the cloud, and use your model to make predictions about new data.
The built-in toolchain provided by the platform speeds up the development and deployment of machine learning projects, and you can build portable ML pipelines with Kubeflow, an open-source platform from Google. The AI platform lets you deploy your machine learning project on-premises or in the cloud, and there are various options for storing data, such as cloud storage and BigQuery.
Another of AI Platform’s main offerings are preconfigured virtual machines (VMs), which help develop deep learning applications. It also has natural language processing (NLP) capabilities that help determine the meaning and structure of text. In addition to that, you can use the platform’s APIs for text-to-speech and text-to-speech capabilities, as well as vision capabilities to extract information from images.
Here are some of the main features of Google Cloud AI Platform:
- Help train, analyze and tune your ML models
- Get predictions, monitor predictions and manage your models
- Accelerate ML projects
- ML project on premise or in the cloud
- Pre-configured virtual machines (VMs)
Another major option for AI software development tools is the Microsoft Azure AI platform, which is trending in the development market. A robust cloud platform, many organizations depend on it. The platform has many cool features, such as object recognition, unsupervised machine learning, speech recognition, and more.
The Microsoft Azure AI platform has made it easy for organizations to develop AI and offers various customization options, such as pre-trained domain-specific AI models for text, face, and speech recognition . It also offers various machine learning features like Azure ML, a Python-based automated ML service; Azure Databricks, a big data service based on Apache Spark; and ONNX, an open source model format and runtime environment for ML.
Here are some of the key features of the Microsoft Azure AI platform:
- Python-based automated ML service
- Automatic translation
- Object, speech and text recognition capabilities
- AI models to create bots
3. IBM Watson
Another of the best-known AI tools for software development is IBM Watson, which is equipped with advanced AI capabilities including chat interfaces, mobile application APIs, chat interfaces and NLP services. .
IBM Watson’s robust software development tools have been deployed in many different industries like Oil & Gas, Media & Entertainment, Financial Services, Internet of Things (IoT) and more.
The platform also offers AI development services that help developers build apps with pre-trained AI capabilities. Some of its other features include Watson Assistant, which can be integrated to create AI-powered conversational interfaces in your application, and its NLP service in the form of Watson Natural Language Understanding (NLU).
Here are some of the main features of IBM Watson:
- Rapid development and deployment for AI applications
- Text-to-speech capabilities
- PNL and NLU Services
- Powerful mobile app APIs
H20 is an open-source machine learning platform that is growing in popularity. It is a powerful AI software development tool that offers a wide range of features such as smart machine learning algorithms, statistical and generalized linear models, deep learning models, etc. The tool also supports Big Data, Hadoop and Spark/Kubernetes clusters.
H20, which lets you use programming languages like R and Python to build models, is often used for data analysis, fraud detection, risk management, digital health, and customer intelligence.
Here are some of the main features of H20:
- Includes AutoML functionality
- Supports many algorithms such as boosted gradient machines, deep learning, generalized linear models, etc.
- Linearly scalable platform
- Develop mobile applications using R, Java and Python
5. Tensor Flow
No list of AI software development tools would be complete without TensorFlow, which is an open source numerical computation tool and machine learning library. TensorFlow is primarily used for development and research purposes, and it is flexible while offering comprehensive tools and libraries that help accelerate AI development.
Businesses can use TensorFlow to develop and train intelligent ML and AI applications that handle complex operations such as forecasting, contract management, legal operations, customer services, and more.
Here are some of the main features of TensorFlow:
- Seamlessly deploy AI-powered solutions to mobile, desktop, edge devices, and more.
- Extensive set of tools, libraries and community resources
- In-depth analysis, service automation, unsupervised training, etc.
- Wide range of features and functionality
MxNet is a popular and leading AI software development tool which is a deep learning framework often used in research and production. MxNet helps improve AI development with advanced natural language processing capabilities and offers distributed training models to scale AI applications.
The tool is often used in multi-GPU and multi-machine training, as well as writing custom layers in high-level languages.
Here are some of the main features of MxNet:
- Open source deep learning framework
- Improve AI-based applications with NLP
- Highly scalable framework
- Define, train and deploy neural networks
7. Infosys Nia
Closing our list of top 7 AI software development tools is Infosys Nia, which is another great tool that lets you build powerful AI-powered applications. One of the best features offered by the tool is Nia Advanced ML, which offers a wide range of machine learning algorithms that work at speed and scale, helping to build high-performance ML models.
The tool also lets you create AI-powered chatbots, with your app providing access to the company’s knowledge repository. The app can also automate actions with a conversational interface and integrate Nia data, which is a robust analytics solution.
Here are some of the main features of Infosys Nia:
- Efficiently build ML training models
- Process large data sets at scale
- Data management capabilities
- Nia chatbot