Here are some examples of AI products, descriptions and when those debuted (or their business was formed. AI use may have begun later):

ABB Ability - (2017) - An industrial automation platform developed by ABB that uses AI and machine learning to optimize manufacturing and energy operations. ABB Ability includes tools for predictive maintenance, energy management, and asset optimization. (China)

Ada (2016): AI-powered customer service chatbot focused on healthcare and finance industries.

Adext - (2016) - An AI-powered platform that uses machine learning to optimize ad campaigns. Adext analyzes the performance of ad campaigns and uses data to optimize targeting and ad spend.

Adobe Sensei - (2016) - An AI and machine learning platform developed by Adobe that helps creative professionals and marketers enhance their work and make more informed decisions. Sensei includes tools for image and video analysis, content recommendation, and personalization.

Aiva - (2016) - An AI-powered platform that composes original music in a variety of genres and styles. Aiva uses machine learning to analyze musical patterns and create new compositions based on user preferences.

Albert (2017): AI-powered sales assistant for prospecting, scheduling meetings, and deal management.

Amazon Alexa - (2014) - A voice-controlled personal assistant developed by Amazon that uses natural language processing and machine learning to interact with users. Alexa can perform a variety of tasks, such as playing music, answering questions, and controlling smart home devices.

Amazon Rekognition - (2016) - An AI-powered image and video analysis service developed by Amazon that uses machine learning to identify objects, faces, and other content in images and videos. Rekognition can be used for applications such as surveillance, security, and content moderation.

Appen - (1996) - An AI-powered data annotation platform that uses human-in-the-loop machine learning to label and categorize data for machine learning models. Appen can be used for a variety of applications, such as image and speech recognition, and natural language processing.

Ayasdi - (2008) - An AI-powered platform for data analysis and visualization that uses machine learning algorithms to uncover patterns and insights in complex data sets. Ayasdi can be used for a variety of applications, such as medical research, financial analysis, and supply chain optimization.

Braina - (?) - A virtual assistant software that uses natural language processing and machine learning to perform tasks such as voice dictation, web searches, and setting reminders. Braina also includes text-to-speech and speech-to-text features.

Chorus.ai - (2015) - An AI-powered sales platform that uses natural language processing to analyze sales conversations and provide insights into customer behavior and preferences. Chorus.ai can help sales teams to improve their communication skills and close more deals.

Cognitivescale - (2016) - An AI-powered platform that uses natural language processing and machine learning to help enterprises automate business processes, build intelligent products and provide enhanced customer experiences.

Clearbit RevUnit (2019): AI-powered sales intelligence platform for identifying ideal customers and predicting sales outcomes.

Cortexica - (2008) - An AI-powered platform for visual search and product recommendation that uses machine learning to identify and categorize images. Cortexica can be used for applications such as fashion retail and e-commerce.

Cortica - (2015) - An AI-powered platform for autonomous vehicle navigation that uses machine learning to analyze and interpret complex traffic scenarios. Cortica can help autonomous vehicles to navigate safely and make decisions in real-time.

Covariant - (2017) - An AI-powered robotics platform that uses machine learning to teach robots to perform complex tasks in a variety of industries, such as logistics and manufacturing. Covariant can enable robots to learn from human demonstrations and adapt to changing environments.

DataRobot (2012): Machine learning platform for building and deploying predictive models.

Darktrace - (2017) - An AI-powered cybersecurity platform that uses machine learning to detect and respond to cyber threats in real-time. Darktrace can help organizations to identify and prevent cyber attacks before they can cause damage.

Drift (2016): Conversational marketing platform using chatbots to qualify leads and personalize customer interactions.

Einstein Analytics (2014) by Salesforce: AI-powered analytics platform for CRM data insights.

Farmwave - (2014) - An AI-powered platform for agriculture that uses computer vision and machine learning to analyze crops and soil conditions. Farmwave can help farmers to optimize crop yields and reduce waste.

Freenome - (2014) - An AI-powered platform for early cancer detection that uses machine learning to analyze blood samples and identify biomarkers that indicate the presence of cancer. Freenome can be used for screening and monitoring purposes.

Glint (2013): AI-powered employee engagement platform for collecting feedback and improving workplace culture.

Google Assistant - (2016) - A virtual assistant developed by Google that uses natural language processing and machine learning to understand and respond to voice commands. Google Assistant can perform a variety of tasks, such as sending messages, making phone calls, and providing directions.

Google Translate - (2006) - A translation app that uses machine learning to automatically translate text and speech into different languages. Google Translate can also translate written text from images and provide real-time translation during conversations.

Grammarly - (2009) - A writing assistant tool that uses natural language processing and machine learning to analyze and improve the grammar, spelling, and style of written content.
Grammarly can be used for a variety of writing applications, such as emails, documents, and social media posts.

Grammarly Business - (2009 - A version of Grammarly that is designed for businesses and organizations. Grammarly Business includes advanced writing analytics and tools for team collaboration, and can be customized to match a company's specific style and preferences.

Grammarly for Microsoft Office - (2009) - A version of Grammarly that integrates with Microsoft Word and Outlook to provide real-time writing feedback and suggestions. Grammarly for Microsoft Office can help users improve their grammar, spelling, and punctuation in professional documents and emails.

H20.ai - (2012) - An AI-powered platform for machine learning that offers a range of tools and algorithms for data analysis and modeling. H20.ai can be used for applications such as predictive maintenance, fraud detection, and customer segmentation.

HiBob (2015): AI-powered HR platform for automating tasks like payroll and benefits administration.

HubSpot Marketing Hub (2011): All-in-one marketing platform with AI-powered lead scoring, social media listening, and content creation tools.

Hugging Face - (2016) - A natural language processing platform that uses AI to enable developers to build conversational AI applications, chatbots, and language translation tools. The platform offers access to pre-trained models and can also help to train customized models.

IBM Watson - (2010) - An AI platform developed by IBM that uses natural language processing and machine learning to analyze and interpret large amounts of data. Watson can be used for a variety of applications, such as healthcare, finance, and education.

IBM Watson Discovery - (2005?) - An AI-powered search and analysis platform developed by IBM that uses natural language processing and machine learning to help businesses and organizations uncover insights from large amounts of unstructured data. Watson Discovery can be used for a variety of applications, such as customer service, legal research, and scientific discovery.

IBM Watson Health - (2015) - An AI-powered platform developed by IBM that uses machine learning to help healthcare providers and researchers improve patient outcomes and advance medical research. Watson Health includes tools for medical image analysis, drug discovery, and patient data analysis.

Iris.ai - (2015) - An AI-powered platform for scientific research that uses natural language processing and machine learning to help researchers discover and analyze scientific literature. Iris.ai can help researchers to identify relevant papers and find new connections between different research topics.

Lattice (2016): AI-powered performance management platform for continuous feedback and goal setting.

LivePerson (1999): Conversational AI platform for building chatbots and virtual assistants for customer service.

Melio (2019): AI-powered payment platform for automating accounts payable and receivables.

Meya - (1998) - A conversational AI platform that uses natural language processing and machine learning to help developers build and deploy chatbots and virtual assistants. Meya offers a drag-and-drop interface and integration with popular messaging apps and voice assistants.

Microsoft Power BI - (2015) - A data analytics and visualization tool that uses AI to provide insights into business data. Power BI can analyze large amounts of data from various sources and generate visualizations that help business decision-makers to better understand and interpret the data.

Nest Learning Thermostat - (2011) - A smart thermostat developed by Nest that uses machine learning to learn the temperature preferences of users and automatically adjust the temperature to save energy. The thermostat can be controlled remotely through a mobile app.

Netflix - (1998) - A video streaming platform that uses machine learning algorithms to recommend TV shows and movies to users based on their viewing history and preferences. Netflix also uses AI for content tagging and categorization, and to optimize video streaming quality.

NVIDIA DRIVE - (2015) - An AI platform for autonomous vehicles that uses machine learning to provide advanced perception, mapping, and planning capabilities. NVIDIA DRIVE can be used to develop fully autonomous vehicles and improve driver safety features.

OpenAI GPT-3 - (2020) - A language model developed by OpenAI that uses deep learning to generate human-like text responses. GPT-3 can be used for applications such as chatbots, language translation, and content creation.

Roomba - (2002) - A robotic vacuum cleaner developed by iRobot that uses machine learning to navigate and clean homes. Roomba can map out a home's layout and adapt to changing environments to optimize its cleaning path.

Salesforce Einstein - (2023) - An AI-powered platform developed by Salesforce that uses machine learning to help businesses improve customer service, sales, and marketing. Salesforce Einstein includes tools for predictive analytics, data visualization, and natural language processing.

SalesPredict (now part of eBay)- (2012) - A sales and marketing AI platform that uses machine learning to predict customer behavior and purchase likelihood. The platform uses data from multiple sources to generate accurate predictions about potential customers.

Siri - (2008) - A virtual assistant developed by Apple that uses natural language processing and machine learning to understand and respond to voice commands. Siri can perform a variety of tasks, such as setting reminders, sending messages, and making phone calls.

SmartNews - (2013) - A news app that uses AI to personalize news feeds for users. The app analyzes user behavior, preferences, and reading habits to provide relevant news stories and alerts.

SoundHound - (2005) - An AI-powered music recognition app that uses natural language processing and machine learning to identify songs and lyrics. SoundHound can also provide information about artists and albums.

Spotify - (2008) - A music streaming platform that uses machine learning algorithms to recommend music to users based on their listening history and preferences. Spotify can also analyze songs to create playlists with similar features or to identify what songs have been sampled in other songs.

Suki - (2016) - An AI-powered platform for medical documentation that uses natural language processing and machine learning to transcribe and analyze medical notes. Suki can help healthcare providers to save time and improve patient care.

Synthace - (2011) - An AI-powered platform for biotechnology that uses machine learning to optimize lab experiments and accelerate drug discovery. Synthace can be used for applications such as protein engineering, genetic engineering, and cell culture.

Tesla Autopilot - (2014) - A suite of advanced driver assistance features developed by Tesla that uses computer vision and machine learning to improve safety and convenience while driving. Autopilot can perform tasks such as lane keeping, adaptive cruise control, and self-parking.

UiPath - (2005) - An AI-powered platform for robotic process automation that uses machine learning to automate repetitive business processes. UiPath can be used for applications such as data entry, invoice processing, and customer service.

Unity - (2005) - An AI-powered platform for game development that uses machine learning to create more realistic and interactive games. Unity includes tools for game physics, animation, and rendering.

Visage Technologies - (2002) - An AI-powered platform for facial recognition and analysis that uses machine learning to identify facial expressions, emotions, and other attributes. Visage Technologies can be used for applications such as security, entertainment, and healthcare.

Viz.ai - (2016) - An AI-powered medical imaging platform that uses machine learning to improve the speed and accuracy of stroke diagnosis. The platform analyzes CT scans and MRI images to help doctors quickly identify and treat strokes.

Waze - (2009) - A navigation app that uses machine learning to improve traffic routing and provide real-time alerts about accidents, road closures, and other hazards. Waze also uses AI for voice recognition and to predict routes based on the time of day and user habits.

X.AI - (2014) - A virtual assistant developed by X.AI that uses natural language processing to schedule and organize meetings for users. X.AI can interact with other virtual assistants, such as Siri and Alexa, and integrates with popular calendar apps.

Xnor.ai - (2017) - An AI-powered platform for low-power computing that uses machine learning to enable AI processing on devices with limited computing power, such as IoT devices and smartphones. Xnor.ai can be used for applications such as object recognition, face detection, and voice recognition.

Zebra Medical Vision - (2014) - An AI-powered platform for medical imaging analysis that uses machine learning to improve diagnostic accuracy and efficiency. Zebra Medical Vision can analyze X-rays, CT scans, and other medical images to identify and prioritize potential health risks.

Zoom - (1972) - A video conferencing platform that uses AI-powered features such as noise cancellation, virtual backgrounds, and facial recognition to improve the user experience. Zoom can be used for a variety of purposes, such as remote work, education, and social gatherings.

ZoomInfo - (2007) - A sales and marketing intelligence platform that uses AI to provide insights and data about potential customers and companies. ZoomInfo can help businesses identify key decision-makers and personalize their sales and marketing strategies.

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Here are some milestones in the history of AI

1943: Warren McCulloch and Walter Pitts develop the first artificial neural network model, which is a computational model inspired by the structure and function of the human brain. Neural networks have since become a key tool for many AI applications, including image and speech recognition.

1950: Alan Turing proposes the Turing Test, a method for testing a machine's ability to exhibit intelligent behavior that is indistinguishable from that of a human.

1956: The Dartmouth Conference, organized by John McCarthy, Marvin Minsky, Claude Shannon, and Nathaniel Rochester, marks the birth of AI as a field of research.

1958: John McCarthy develops Lisp, the first high-level programming language for AI applications.

1965: Joseph Weizenbaum develops ELIZA, a natural language processing program that can simulate conversation with a human.

1969: The General Problem Solver (GPS), a problem-solving program developed by Allen Newell and Herbert Simon, demonstrates the power of heuristic search algorithms.

1971: Terry Winograd develops SHRDLU, a natural language understanding program that can manipulate objects in a simulated block world.

1980s: Expert systems, rule-based systems that can make decisions based on a knowledge base of if-then statements, become popular in business and industry.

1986: Geoffrey Hinton, David Rumelhart, and Ronald Williams develop backpropagation, a method for training neural networks that allows them to learn from data.

1997: IBM's Deep Blue defeats world chess champion Garry Kasparov in a six-game match.

2011: IBM's Watson defeats two human champions in the game show Jeopardy!

2012: Google develops a neural network that can recognize cats in YouTube videos without being explicitly programmed to do so.

2016: AlphaGo, a program developed by Google's DeepMind, defeats the world champion of the board game Go.

2020: OpenAI's GPT-3, a natural language processing model with 175 billion parameters, demonstrates impressive capabilities in text generation and language understanding.

Timeline of Artificial Intelligence - Wikipedia

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Logic programming - In the 1950s and 1960s, researchers developed early versions of logic programming languages, such as LISP and Prolog, which are used for developing expert systems and other forms of symbolic AI.

Expert systems - In the 1970s and 1980s, expert systems became a popular form of AI. These are computer programs that mimic the decision-making abilities of a human expert by using a knowledge base of rules and heuristics.

Backpropagation - In 1986, Geoffrey Hinton, David Rumelhart, and Ronald Williams developed the backpropagation algorithm for training neural networks, which made it possible to train deeper and more complex neural networks that can learn from large amounts of data.

Support vector machines - In the 1990s, support vector machines (SVMs) were developed as a powerful machine learning algorithm for classification and regression tasks. SVMs have since become a key tool for many AI applications, including image and speech recognition.

Reinforcement learning - In the 1990s, researchers developed the reinforcement learning paradigm, which involves training agents to learn from feedback in a dynamic environment. Reinforcement learning has been used to develop autonomous systems in a variety of fields, including robotics and game playing.

Deep learning - In the 2000s and 2010s, researchers made significant breakthroughs in deep learning, a type of machine learning that involves training deep neural networks with many layers of neurons. Deep learning has enabled significant advances in fields such as image and speech recognition, natural language processing, and game playing.

Generative models - In recent years, generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), have been developed as a way to generate new data that is similar to existing data. These models have been used for tasks such as image and text generation, and are also being explored for their potential in other areas, such as drug discovery and climate modeling.

One of the areas in which AI is making a significant impact is healthcare. AI-powered diagnostic tools, such as IBM Watson Health, are helping doctors and clinicians to make more accurate and timely diagnoses, while AI-powered drug discovery platforms are accelerating the development of new treatments and therapies. AI is also being used to analyze medical images, predict patient outcomes, and improve patient care.

In finance, AI-powered chatbots are being used to interact with customers, while AI algorithms are being used to detect fraud and manage risk. In transportation, autonomous vehicles are becoming more prevalent, with companies like Tesla, Waymo, and Uber investing heavily in the technology. AI is also being used in entertainment, with AI-powered music and video recommendation systems providing personalized content to viewers and listeners.

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