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Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in 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]
The history of artificial intelligence (AI) began in antiquity, with myths, stories, and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen.
Perplexity was founded in 2022 by Aravind Srinivas, Andy Konwinski, Denis Yarats and Johnny Ho, engineers with backgrounds in back-end systems, artificial intelligence (AI) and machine learning: Srinivas, the CEO, worked at OpenAI as an AI researcher. Konwinski was among the founding team at Databricks.
Geoffrey Everest Hinton (born 6 December 1947) is a British-Canadian computer scientist, cognitive scientist, cognitive psychologist, known for his work on artificial neural networks which earned him the title as the "Godfather of AI".
Mustafa Suleyman CBE (born August 1984 [1]) is a British artificial intelligence (AI) entrepreneur. He is the CEO of Microsoft AI, and the co-founder and former head of applied AI at DeepMind, an AI company acquired by Google. [2] [3] After leaving DeepMind, he co-founded Inflection AI, a machine learning and generative AI company, in 2022. [4] [5]
The letter highlights both the positive and negative effects of artificial intelligence. [7] According to Bloomberg Business, Professor Max Tegmark of MIT circulated the letter in order to find common ground between signatories who consider super intelligent AI a significant existential risk, and signatories such as Professor Oren Etzioni, who believe the AI field was being "impugned" by a one ...
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Transformer architecture is now used in many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings, improving upon the line of research from bag of words and word2vec. It was followed by BERT (2018), an encoder-only Transformer model. [35]