The modern definition of artificial intelligence (or AI) is "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success.[1] John McCarthy, who coined the term in 1956,[2] defines it as "the science and engineering of making intelligent machines."[3] Other names for the field have been proposed, such as computational intelligence,[4] synthetic intelligence[4][5] or computational rationality.[6] The term artificial intelligence is also used to describe a property of machines or programs: the intelligence that the system demonstrates.
Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents"[1] where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.[2] John McCarthy, who coined the term in 1956,[3] defines it as "the science and engineering of making intelligent machines."[4]
"Data Science Agent
An experiment to build an AI generated Colab notebook that handles data cleaning, data exploration, plotting, Q&A on data, and predictive modeling."
Neuro-Evolving Robotic Operatives, or NERO for short, is a unique computer game that lets you play with adapting intelligent agents hands-on. Evolve your own robot army by tuning their artificial brains for challenging tasks, then pit them against your friends' teams in online competitions! New feat
"The Artificial Intelligence (AI) program at the University of Michigan comprises a multidisciplinary group of researchers conducting
theoretical, experimental, and applied investigations of intelligent systems. Current projects include research in rational decision
making, computational game theory, distributed systems of multiple agents, reinforcement learning, machine learning, cognitive modeling,
natural language processing, information retrieval, and robotics."
The Artificial Intelligence (AI) program at the University of Michigan comprises a multidisciplinary group of researchers conducting
theoretical, experimental, and applied investigations of intelligent systems. Current projects include research in rational decision
making, computational game theory, distributed systems of multiple agents, reinforcement learning, machine learning, cognitive modeling,
natural language processing, information retrieval, and robotics.
The Oycib infrastructure is based in the ethnographic observation model based agents called e-Xploration. The infrastructure allows the analysis, interpretation and visualization of profiles and digital practices. Furthermore, we propose work in the context-awareness to enhance the collaboration and cooperation among people and groups.
"OpenAI Gym BETA
A toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Go."
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.
"Build voice AI into your apps
Deepgram's voice AI platform provides APIs for speech-to-text, text-to-speech, and language understanding. From medical transcription to autonomous agents, Deepgram is the go-to choice for developers of voice AI experiences."
"Build voice AI into your apps
Deepgram's voice AI platform provides APIs for speech-to-text, text-to-speech, and language understanding. From medical transcription to autonomous agents, Deepgram is the go-to choice for developers of voice AI experiences."
"Build voice AI into your apps
Deepgram's voice AI platform provides APIs for speech-to-text, text-to-speech, and language understanding. From medical transcription to autonomous agents, Deepgram is the go-to choice for developers of voice AI experiences."