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Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [85] Google Photos, [86] and the Adobe Suite (Adobe Firefly). [87] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model.
Artificial intelligence (AI) refers to the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, ...
A problem is informally called "AI-complete" or "AI-hard" if it is believed that in order to solve it, one would need to implement AGI, because the solution is beyond the capabilities of a purpose-specific algorithm. [47] There are many problems that have been conjectured to require general intelligence to solve as well as humans.
Explainable AI (XAI), or Interpretable AI, or Explainable Machine Learning (XML), is artificial intelligence (AI) in which humans can understand the decisions or predictions made by the AI. [129] It contrasts with the "black box" concept in machine learning where even its designers cannot explain why an AI arrived at a specific decision. [ 130 ]
Artificial intelligence research and development did not start until the late 1970s after Deng Xiaoping's economic reforms. [3] While there was a lack of AI-related research between the 1950s and 1960s, some scholars believe this is due to the influence of cybernetics from the Soviet Union despite the Sino-Soviet split during the late 1950s and early 1960s. [10]
The Chinese start-up DeepSeek developed an AI chatbot that reportedly rivaled models from industry leaders like OpenAI, Anthropic, and Alphabet at a fraction of the cost. The market reaction ...
Approaches for integration are diverse. [10] Henry Kautz's taxonomy of neuro-symbolic architectures [11] follows, along with some examples: . Symbolic Neural symbolic is the current approach of many neural models in natural language processing, where words or subword tokens are the ultimate input and output of large language models.
Knowledge collection from volunteer contributors – Subfield of AI; Knowledge extraction – Creation of knowledge from structured and unstructured sources; Information processing (psychology) – Approach to understanding human thinking