- January 23, 2023
- Posted by: Aelius Venture
- Categories: Artificial Intelligence, Development, Innovation, IOT
AI’s growth has made a real difference in how software is made. Artificial intelligence has made it easier to process large amounts of data, and it is an application of different technologies that work together to let a computer do things that humans usually do.
1. Google Cloud AI Platform
The Google Cloud AI Platform is at the top of our list of the 7 best AI software development tools. It lets you train your algorithms for machine learning at scale, host your trained models in the cloud, and use your trained models to make predictions about new data.
The integrated toolchain that the platform provides speeds up the development and rollout of machine learning projects. With Kubeflow, a Google open-source platform, you can create portable ML pipelines. You can deploy your machine learning project on-premise or in the cloud, and there are different ways to store data, such as data storage and BigQuery.
AI Platform also has pre-configured Virtual Machines (VMs) that help build deep learning applications. It includes natural language processing (NLP) features that help figure out what text means and how it is put together. You can also use the platform’s APIs to use speech-to-text and text-to-speech functions, as well as vision functions to get information from images.
2. Microsoft Azure AI Platform
The Microsoft Azure AI Platform, that has been on the rise in the development market, is another great choice for AI software development tools. Many businesses depend on it because it is a strong cloud platform. The platform can do a lot of great things, like recognise objects, learn without being watched, recognise speech, and more.
The Microsoft Azure AI Platform has made it simpler for organizations to develop AI, and it gives them a lot of ways to make it their own, like pre-trained AI models for message, face, and speech recognition that are specific to their domain. It also has a number of machine learning features, such as Azure ML, an automated ML service based on Python, Azure Databricks, a big data service based on Apache Spark, and ONNX, an open-source ML model format and runtime.
3. IBM Watson
IBM Watson is another well-known AI tool for software development. It has advanced AI features like discussion interfaces, mobile app APIs, conversation interfaces, but also natural language processing (NLP) services.
The platform also has services for AI development that help developers make apps with AI features that have already been trained. It also has Watson Assistant, which can be used to construct AI-powered conversational interfaces into your app, and Watson Natural Language Understanding, which is an NLP service (NLU).
H20 is an open-source platform for machine learning that has been getting more and more popular over time. It’s a powerful AI software development tool with a wide range of features, such as smart machine learning techniques, statistical and generalized linear models, deep learning models, and more. The tool also works with clusters of Hadoop, Spark, and Kubernetes.
H20 is frequently employed for data analysis, fraud detection, risk management, digital healthcare, customer intelligence, and building models using programming languages like R and Python.
TensorFlow is an open-source tool for computing numbers and a machine learning library. No list of tools for making AI software would’ve been complete without it. TensorFlow is mostly used for research and development, and it has a lot of tools and library resources that help speed up AI development. It is also very flexible.
Businesses can use TensorFlow to build and train smart applications that use machine learning (ML) and artificial intelligence (AI) to handle complex tasks like forecasting, contract management, legal operations, customer service, and more.
MxNet is a machine learning framework that is a popular and well-known AI software development tool. It is frequently employed in research and development. MxNet helps improve AI development with its advanced natural language processing and distributed training models, which allow AI applications to be used on a larger scale.The tool is often used for Multi-GPU as well as multi-machine training, as well as for writing custom layers in high-level languages.
7. Infosys Nia
It is another great tool that lets you make powerful apps that use AI. Nia Advanced ML, one of the best features of the tool, lets you use a wide range of machine learning algorithms that work quickly and on a large scale to help you build high-performing ML models.
You can also use the tool to build chatbots that are powered by AI. Your app can connect to an enterprise knowledge repository. The app also can automate actions with such a conversational interface as well as integrate Nia data, which is a powerful analytics solution.
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