Software that mimics human behavior by learning different data patterns is referred to as Artificial Intelligence (AI) Software. Machine Learning, virtual assistance, speech recognition, etc. are all AI software features.
The purpose of such software is to simplify and streamline business processes as well as to develop intelligent applications from scratch with the help of machine learning and deep learning capabilities.
There are four key types of AI software:
Chatbots – a program that simulates a human participating in a conversation.
AI Platforms – created to develop apps from scratch.
Deep learning software – including speech recognition, is a subfield of machine learning that uses algorithms based on the structure and functionality of the human brain.
Machine Learning Software – makes the computer learn using data.
Based on those types, here is an overview of some of the best Artificial Intelligence Software available on the market.
1. Google Cloud Machine Learning Engine
The Google Cloud Machine Learning Engine was designed to assist you in training, analyzing, and tuning your model. Cloud ML Engine components include Google Cloud Platform Console, gcloud, and REST API.
Google Cloud ML has 3 components:
Google Cloud Platform Console is a graphical user interface for deploying and managing models, versions, and jobs.
gcloud is a command line tool for managing models and versions.
REST API is for online predictions.
The platform offers good support and serves its purpose well; however, the learning curve is quite steep. The pricing varies depending on the region.
2. Azure Machine Learning Studio
This tool will assist you in deploying your model as a web service. This web service will be platform agnostic and will be able to access any data source. It can deploy models in the cloud, on-premises, and at the edge, offers a browser-based solution, and is simple to use due to its drag-and-drop functionality. The software’s main advantages are that it does not require any programming skills and can be integrated with open-source technologies. When choosing this software, pay close attention to pricing details and select only the paid features that you require.
3. TensorFlow
It is a free computational tool and open-source system that can be run on CPUs, GPUs, and TPUs, as well as desktops, clusters, mobiles, and edge devices. It is suitable for both beginners and experts, and it offers excellent community support as well as excellent functionality. However, progressing to an advanced level of proficiency takes time.
4. H2O.AI
H2O AI is open-source software designed primarily for the banking, insurance, healthcare, marketing, and telecommunications industries. To create models, this tool employs programming languages such as R and Python. AutoML functionality, a linearly scalable platform, many algorithms supported, deep learning, and a distributed in-memory structure are among the key features of the H2O.AI. The software is simple to use and offers good support, but its documentation still needs to be improved.
5. Cortana
Cortana is a virtual assistant that can perform a variety of tasks such as setting reminders, answering questions, placing meal orders, and turning off the light. It supports Windows, iOS, Android, and Xbox OS, uses the Bing search engine, and can accept voice commands, which saves time. However, some platform features and skills are only available to users in the United States.
6. IBM Watson
IBM Watson is a question-answering system that uses the Apache Hadoop framework. When you train your model with Watson, it will deeply understand the real concepts. The software supports distributed computing, can work with the existing tools, provides an API for application development, and can learn from small data. If you need a robust system that will make your business processes smarter, consider IBM Watson.
7. Salesforce Einstein
The world’s smartest Customer Relationship Management (CRM) system, according to its own positioning, can be particularly useful for Sales,
Marketing, Community, Analytics, and Commerce. For sales, it helps to capture data and save the effort of data entry by adding new contacts and helps in prioritizing the opportunities based on history. There are some marketing tasks you can delegate to the software, such as recommending the best products, recognizing images to provide deeper insights, using engagement scoring, and collecting analytics. It doesn’t require data preparation for managing models, but it is expensive and difficult to learn.
8. Infosys Nia
Infosys Nia consists of three components: Data platform, Knowledge platform, and Automation platform. It helps in simplifying business processes. Its key features include a conversational interface, automation for repetitive and programmatic tasks, and data captures from various sources. The automation platform combines RPA, predictive automation, and cognitive automation. The knowledge platform focuses on capturing, processing, and reusing knowledge. The data platform provides advanced data analytics and a machine learning platform. The biggest downside is a steep learning curve.
9. Amazon Alexa
Cortana’s competitor, virtual assistant Alexa, is a cloud-based service, that can be connected to various devices and entertainment systems and can be integrated with existing products using AVS (Alexa Voice Service).
It can be used on plenty of devices and supports creating more Alexa gadgets.
10. Google Assistant
Another virtual assistant has been created by Google for pairing with mobiles and smart home devices. It supports operating systems including Android, iOS, and KaiOS and various languages. Google Assistant can support two-way conversations, search for information on the internet, schedule events, set alarms, and do hardware settings. It also can recognize objects and read visual information.
Which AI platforms are you exploring? Let us know in the comments!
10 Best Artificial Intelligence Software
Software that mimics human behavior by learning different data patterns is referred to as Artificial Intelligence (AI) Software. Machine Learning, virtual assistance, speech recognition, etc. are all AI software features.
The purpose of such software is to simplify and streamline business processes as well as to develop intelligent applications from scratch with the help of machine learning and deep learning capabilities.
There are four key types of AI software:
Based on those types, here is an overview of some of the best Artificial Intelligence Software available on the market.
1. Google Cloud Machine Learning Engine
The Google Cloud Machine Learning Engine was designed to assist you in training, analyzing, and tuning your model. Cloud ML Engine components include Google Cloud Platform Console, gcloud, and REST API.
Google Cloud ML has 3 components:
The platform offers good support and serves its purpose well; however, the learning curve is quite steep. The pricing varies depending on the region.
2. Azure Machine Learning Studio
This tool will assist you in deploying your model as a web service. This web service will be platform agnostic and will be able to access any data source. It can deploy models in the cloud, on-premises, and at the edge, offers a browser-based solution, and is simple to use due to its drag-and-drop functionality. The software’s main advantages are that it does not require any programming skills and can be integrated with open-source technologies. When choosing this software, pay close attention to pricing details and select only the paid features that you require.
3. TensorFlow
It is a free computational tool and open-source system that can be run on CPUs, GPUs, and TPUs, as well as desktops, clusters, mobiles, and edge devices. It is suitable for both beginners and experts, and it offers excellent community support as well as excellent functionality. However, progressing to an advanced level of proficiency takes time.
4. H2O.AI
H2O AI is open-source software designed primarily for the banking, insurance, healthcare, marketing, and telecommunications industries. To create models, this tool employs programming languages such as R and Python. AutoML functionality, a linearly scalable platform, many algorithms supported, deep learning, and a distributed in-memory structure are among the key features of the H2O.AI. The software is simple to use and offers good support, but its documentation still needs to be improved.
5. Cortana
Cortana is a virtual assistant that can perform a variety of tasks such as setting reminders, answering questions, placing meal orders, and turning off the light. It supports Windows, iOS, Android, and Xbox OS, uses the Bing search engine, and can accept voice commands, which saves time. However, some platform features and skills are only available to users in the United States.
6. IBM Watson
IBM Watson is a question-answering system that uses the Apache Hadoop framework. When you train your model with Watson, it will deeply understand the real concepts. The software supports distributed computing, can work with the existing tools, provides an API for application development, and can learn from small data. If you need a robust system that will make your business processes smarter, consider IBM Watson.
7. Salesforce Einstein
The world’s smartest Customer Relationship Management (CRM) system, according to its own positioning, can be particularly useful for Sales,
Marketing, Community, Analytics, and Commerce. For sales, it helps to capture data and save the effort of data entry by adding new contacts and helps in prioritizing the opportunities based on history. There are some marketing tasks you can delegate to the software, such as recommending the best products, recognizing images to provide deeper insights, using engagement scoring, and collecting analytics. It doesn’t require data preparation for managing models, but it is expensive and difficult to learn.
8. Infosys Nia
Infosys Nia consists of three components: Data platform, Knowledge platform, and Automation platform. It helps in simplifying business processes. Its key features include a conversational interface, automation for repetitive and programmatic tasks, and data captures from various sources. The automation platform combines RPA, predictive automation, and cognitive automation. The knowledge platform focuses on capturing, processing, and reusing knowledge. The data platform provides advanced data analytics and a machine learning platform. The biggest downside is a steep learning curve.
9. Amazon Alexa
Cortana’s competitor, virtual assistant Alexa, is a cloud-based service, that can be connected to various devices and entertainment systems and can be integrated with existing products using AVS (Alexa Voice Service).
It can be used on plenty of devices and supports creating more Alexa gadgets.
10. Google Assistant
Another virtual assistant has been created by Google for pairing with mobiles and smart home devices. It supports operating systems including Android, iOS, and KaiOS and various languages. Google Assistant can support two-way conversations, search for information on the internet, schedule events, set alarms, and do hardware settings. It also can recognize objects and read visual information.
Which AI platforms are you exploring? Let us know in the comments!
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