Artificial Intelligence Glossary | Stanford HAI

Artificial Intelligence

Summary. The term artificial intelligence (AI) is typically used as if it refers to a coherent, extant or near-future set of technologies, but, in fact, it

Artificial intelligence

Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in engineering, mathematics and computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.[1]

Artificial intelligence glossary: 60+ terms to know

Use this comprehensive glossary of AI terms to understand the language of artificial intelligence.

The 2026 AI Index Report | Stanford HAI

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

LukeW | The Evolution of AI Products

At this point, the use of artificial intelligence and machine learning models in software has a long history. But the past three years really accelerated the ev...

Machine Learning Glossary  |  Google for Developers

This glossary defines a wide range of machine learning terms, including those specific to TensorFlow and large language models.

Glossary of Terms for Artificial Intelligence | Columbia Business School

Columbia University in the City of New York 665 West 130th Street, New York, NY 10027 Tel. 212-854-1100

AI Index | Stanford HAI

The mission of the AI Index is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI. To achieve this, we track, collate, distill, and visualize dat

LukeW | Common AI Product Issues

At this point, almost every software domain has launched or explored AI features. Despite the wide range of use cases, most of these implementations have been t...

II. From AGI to Superintelligence: the Intelligence Explosion - SITUATIONAL AWARENESS

AI progress won’t stop at human-level. Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into ≤1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power—and the peril—of superintelligence would be dramatic. Let an ultraintelligent machine be defined as a machine that

Glossary of Terms: Generative AI Basics - MIT Sloan Teaching & Learning Technologies

Learn key AI terms. This glossary defines and explains important concepts like generative AI, large language model, natural language processing, and more.

Stuff we figured out about AI in 2023

2023 was the breakthrough year for Large Language Models (LLMs). I think it’s OK to call these AI—they’re the latest and (currently) most interesting development in the academic field of …

From AGI to ASI

Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade target for many of the largest AI organisations. Achieving this goal would have profound and far-reaching impacts on human society, which raises many complex questions for the decade ahead. This report investigates how AI itself might continue to develop in a post-AGI world along the continuum of machine intelligence. The endpoint of this continuum, Universal AI, is theoretically well understood, which provides some formal grounding for the main focus of this report: the transition from human-level AGI to artificial general superintelligence, which can intuitively be understood as a system that is more intelligent and cognitively capable than large organisations of humans. After characterizing ASI, the report discusses four potential pathways from AGI to ASI: scaling AGI, AI paradigm shifts, recursive improvement, and ASI emerging from large-scale multi-agent collectives. The report then discusses possible frictions and bottlenecks along these pathways. Determining whether the impact of these frictions will be negligible or substantial raises a number of concrete open research questions. Due to large uncertainties for predicting ASI progress, it cannot be ruled out that AI progress might continue to accelerate over the next years. This could imply that the image of a single transformative step change, caused by the introduction of human-level AGI into our society, could be inaccurate. More apt might be the prospect of a series of transformative societal changes caused by AI-enabled progress and breakthroughs across many areas of science and technology. Preparing for this prospect requires a massively interdisciplinary endeavour of global scope and interest.

AI is An Ideology, Not A Technology

At its core, "artificial intelligence" is a perilous belief that fails to recognize the agency of humans.

Opaque recurrence, and other AI terms that you should probably know | TechCrunch

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most important words and phrases you might encounter.