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KSL conducts research in the areas of knowledge representation and automated reasoning in the Artificial Intelligence Laboratory of the Department of Computer Science at Stanford University. Current work focuses on enabling technology for the Semantic Web, hybrid reasoning, explaining answers from heterogeneous applications, deductive question-answering, representing and reasoning with multiple contexts, knowledge aggregation, ontology engineering, and knowledge-based technology for intelligence analysts and other knowledge workers.

"MusicGraph.ai is the first web-based graph analytics and intelligence engine for the music industry. The platform gives MusicGraph API users access to a comprehensive library of powerful algorithms that can be leveraged to extract even more value from the world's most extensive repository of music data. It's also fully integrated with MusicGraph allowing users to view all the relevant metrics surrounding API usage."

"MusicGraph.ai is the first web-based graph analytics and intelligence engine for the music industry. The platform gives MusicGraph API users access to a comprehensive library of powerful algorithms that can be leveraged to extract even more value from the world's most extensive repository of music data. It's also fully integrated with MusicGraph allowing users to view all the relevant metrics surrounding API usage."

a visual learning robot, that identifies and extracts the important parts of any web page .. "Diffbot's computer vision and machine learning services structure Web data with better-than-human-level accuracy across any website or language."

The DARPA Agent Markup Language (DAML) Program officially began in August 2000. The goal of the DAML effort is to develop a language and tools to facilitate the concept of the Semantic Web. Michael Pagels is the DARPA Program Manager for DAML. The DAML program will end in early 2006.

ai-one™ - biologically inspired intelligence. We sell software development kits (SDKs) for machine learning applications. We give programmers a virtual brain so they can build artificial intelligence into any software application. Unlike other machine learning tools, our technology works in any language, works with any data and learns quickly without human intervention.

START, the world's first Web-based question answering system, has been on-line and continuously operating since December, 1993. It has been developed by Boris Katz and his associates of the InfoLab Group at the MIT Computer Science and Artificial Intelligence Laboratory. Unlike information retrieval systems (e.g., search engines), START aims to supply users with "just the right information," instead of merely providing a list of hits. Currently, the system can answer millions of English questions about places (e.g., cities, countries, lakes, coordinates, weather, maps, demographics, political and economic systems), movies (e.g., titles, actors, directors), people (e.g., birth dates, biographies), dictionary definitions, and much, much more. Below is a list of some of the things START knows about, with example questions. You can type your question above or select from the following examples.

The first Semantic Engine that learns Add a semantic flavor to your apps. With  Meaningtool you can create your own   Semantic Trees and let its intelligence    learn new concepts to filter and categorize     websites, text and users in any language!

"Integrate ChatGPT, Web Monitoring & Automation to your browser. Get ChatGPT responses alongside Google search results, automate tedious data extraction, content summarization and web monitoring."

"Hey there! I'm a robot brain. I learn concepts by searching the Internet. I can interpret natural language text, images, and videos. I watch humans with my sensors and learn things from interacting with them. Here are a few things I've learned recently..."

The objective of INSEMTIVES is to bridge the gap bet­ween human and computational intell­igence in the current semantic content authoring R&D land­scape. The project aims at pro­ducing metho­dologies, methods and tools that enable the massive creation and feasible manage­ment of semantic cont­ent in order to facilitate the world-­wide up­take of semantic tech­nologies.

"KBpedia is a comprehensive knowledge structure for promoting data interoperability and knowledge-based artificial intelligence, or KBAI. The KBpedia knowledge structure combines six (6) public knowledge bases - Wikipedia, Wikidata, OpenCyc, GeoNames, DBpedia and UMBEL - into an integrated whole. KBpedia's upper structure, or knowle"

"Extract Meaning from your Text. The TextRazor API helps you extract and understand the Who, What, Why and How from your legal documents with unprecedented accuracy and speed."

This page links to 820 pages around the web with information on Artificial Intelligence. Links in Bold* followed by a star are especially useful and interesting sites. Links with a + sign at the end have "tooltip" information that will pop up if you put your mouse over the link for a second or two.

"We are a small interdisciplinary team determined to bring novel technology and useful products to the world."

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importan

"Firedrop uses artificial intelligence and machine learning to automatically create uniquely designed websites around your content. No templates, just bespoke design created in minutes."

How can a computer accumulate a massive body of knowledge? What will Web search engines look like in ten years?