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The AI market in India is projected to reach $8 billion by 2025, growing at a compound annual growth rate (CAGR) of over 40% from 2020 to 2025. [1] This growth is part of the broader AI boom, a global period of rapid technological advancements starting in the late 2010s and gaining prominence in the early 2020s.
Its capacity was ten times greater than that of the T-NLG. It was introduced in May 2020, [132] and was in beta testing in June 2020. 2022 ChatGPT, an AI chatbot developed by OpenAI, debuts in November 2022. It is initially built on top of the GPT-3.5 large language model.
Timeline of Indian innovation encompasses key events in the history of technology in the subcontinent historically referred to as India and the modern Indian state.. The entries in this timeline fall into the following categories: architecture, astronomy, cartography, metallurgy, logic, mathematics, metrology, mineralogy, automobile engineering, information technology, communications, space ...
The removal of cataract by surgery was also introduced into China from India. [36] Sushruta's treatise provides the first written record of a cheek flap rhinoplasty, a technique still used today to reconstruct a nose. [37] Otoplasty (surgery of the ear) was developed in ancient India and is described in the same medical compendium, the Sushruta ...
Logic was introduced into AI research as early as 1958, by John McCarthy in his Advice Taker proposal. [173] [98] In 1963, J. Alan Robinson had discovered a simple method to implement deduction on computers, the resolution and unification algorithm. [98]
At the same time, since OpenAI released GPT-4 in March 2023 and competitors introduced similarly performing AI large language models, these models have stopped getting significantly “bigger and ...
2024 was a big year for artificial intelligence. 2025 could be even bigger. Business Insider spoke to over a dozen key figures in the industry about AI's future. Here's what they had to say. If ...
Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s 'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s: Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach.