Top 10 Popular AI Software Products to Know in 2023

Top 10 Popular AI Software Products to Know in 2023

Artificial intelligence software products include speech and voice recognition, machine learning, and a virtual assistants

AI assumes many of the responsibilities of performing tasks that humans do. The sophisticated tasks that require more intelligence are done by the computer or the controlling robot.

There are many AI products developed by many companies with different software.

Here are the top 10 popular AI software products you should know about in 2023:

1. Google cloud machine learning engine:

One of the best AI software  programmes is the Google Cloud Machine Learning Engine. This software will help the user in machine learning train, analyse, and tune the model. After analysing the data, the user can get the predictions and record them. Machine learning models and their versions can be managed.

2. Jupyter Notebook:

Jupyter Notebook is one of the software product for coders and one of the top 10 popular AI software products. The user can enter the code and get the output. Jupyter notebook is used for data exploration, vision pipelines, machine learning models, developing ML models, and getting predictions from the analysis. This AI product is the most useful software for data scientists.

3. Azure Machine Learning Studio:

The Azure machine learning studio software is designed for users who work with frameworks and languages. This platform supports TensorFlow, Python, PyTorch, and many other languages. Azure Machine Learning Studio is the open-source platform.

4. TensorFlow:

TensorFlow's open-source python-based platform for users All the numerical computation for building machine learning models is done end-to-end on TensorFlow. Building and deploying the model can be done by the user on this AI platform.

5. Chorus.AI:

Chorus. AI is a platform designed to help users increase sales in their businesses or organizations. The platform allows the user to record, transcript, and manage the call and its records. The user can analyse the data. The advantages of the platform are call recording, sales management, and sales coaching. The chorus.AI is not open source as user can get the platform by pay the require money.

6. H2O. AI:

H20. AI is also the end-to-end platform. This AI platform is designed to train the machine learning models in businesses. It doesn't matter if the user is a beginner or expert in building machine learning models; any user can access the platform and train the ML models.

7. Cortana:

Cortana, an AI product, uses voice recognition and offers a variety of features, such as placing an order for an item or food product or turning on the light. The application takes voice input and gives the required output. Chinese, English, French, German, Italian, Japanese, Portuguese, and Spanish are the languages supported by the Cortana.

8. IBM Watson:

The AI platform used by many businesses and organisations is IBM Watson. Many complex machine learning processes, predictions, and many more can be done using the IBM Watson platform. The platform gives limited access to the free source, and the professional source edition will have a subscription fee. Any model that can be pre-trained or customised can recognise patterns and predict outcomes.

9. Salesforce Einstein:

Salesforce Einstein is used for customer relationship management in businesses or organizations. Any AI-powered application can be built for customers to help the business grow. Salesforce Einstein is not an open-source project, so users need to pay a minimum subscription fee to use the platform.

10. Infosys Nia:

The AI product used for the AI implementation process is Infosys Nia. Various tasks like deep learning, data management, machine learning, and natural language processing can be done through this Infosys Nia platform.

Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.

Related Stories

No stories found.
Analytics Insight