10 Best AI Software Tools You Need to Know in 2023
Exploring the Best AI Software Tools in 2023
Artificial Intelligence (AI) software tools form the backbone of machinations that enable machines and systems to function and learn from data and experience. From natural language processing to machine learning, these tools find applications across a spectrum of industries and domains, which includes robotics, healthcare, gaming, business, and more. This article will throw light on the top 10 AI software tools you should know in 2023, gauged based on their features, performance, popularity, and user reviews.
Defining AI Software
AI software is a computerized system that allows for the implementation of artificial intelligence (AI) to process substantial volumes of data for problem-solving tasks that would typically require human intellect. Such software is capable of mimicking various aspects of human intelligence, including learning, problem-solving, reasoning, perception, and natural language processing.
The AI software can be applied to a range of applications like image recognition, text recognition, video analytics, and voice recognition. Varying techniques like machine learning, deep learning, and natural language processing are entailed while developing AI software. They are instrumental in saving time and effort, improving quality, and performance, providing access to pioneering techniques, and enabling growth and learning for AI professionals.
Honing your Choice: Top 10 AI Software Tools in 2023
While there is a plethora of AI software tools available in the market, choosing the right set of tools can be overwhelming. Therefore, helping you identify the best, here are the top 10 AI Software tools that are worthy of attention in 2023:
| AI Software | Description | Functions and Features |
|---|---|---|
| TensorFlow | TensorFlow, an open-source platform by Google launched in 2015, fuels machine learning and deep learning, offering flexible tools and resources to create, manage, and deploy AI solutions. | TensorFlow Core (Low-level API for direct access to computational graph and variables) and TensorFlow Hub (Repository of pre-trained models) are some of the striking features offered. |
| IBM Watson | IBM Watson, launched in 2011, offers a wide array of services that help to tackle challenges across different domains using AI. It includes computer vision and natural language processing features. | Watson Assistant (For designing chatbots and conversational agents) and Watson Discovery (For harnessing insights from unstructured data) are some of the key functionalities.<'/td> |
| Microsoft Azure AI | Developed by Microsoft in 2017, Microsoft Azure AI is a cloud-based platform that provides all-round AI services and solutions. | The features primarily include Azure Machine Learning for secure and scalable machine learning platform and Azure Cognitive Services for enhancing app cognitive abilities. |
| Google Cloud AI Platform | Launched by Google in 2018, Google Cloud AI is a cloud-based platform offering AI services and solutions across domains and industries. | Main features include AI Platform Unified for machine/deep learning platform and AI Platform Data Labeling Service for labeling data. |
| Amazon Web Services (AWS) AI | Amazon Web Services (AWS) AI is a cloud-based platform offering a wide array of AI services and solutions. | A key feature is Amazon SageMaker, which aids in labeling data for ML tasks, and Amazon comprehension for text analysis. |
Adopting appropriate AI software tools is crucial to effectively harness the potential of AI for your projects. They help in saving time, improving quality and performance, availing latest resources and techniques, besides fostering learning and growth in the AI field.
