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  2. Perplexity AI - Wikipedia

    en.wikipedia.org/wiki/Perplexity.ai

    Perplexity AI is an AI-powered research and conversational search engine that answers queries using natural language predictive text. It is based in San Francisco, California. Founded in 2022, Perplexity generates answers using sources from the web and cites links within the text response. [2] Perplexity works on a freemium model; the free ...

  3. Perplexity AI’s challenge to Google hinges on something ...

    www.aol.com/finance/perplexity-ai-challenge...

    Like a number of AI startups, Perplexity has managed to raise money in a tough environment. In 2023, $170.6 billion was invested across venture—that marks a decline of $71.6 billion from 2022 ...

  4. Perplexity AI to launch ads on search platform by fourth quarter

    www.aol.com/news/perplexity-ai-launch-ads-search...

    August 22, 2024 at 2:24 PM. (Reuters) - Nvidia and Jeff Bezos-backed Perplexity AI said on Thursday that it plans to introduce advertising on its artificial intelligence-powered search platform by ...

  5. SoftBank to invest in search startup Perplexity AI at $3 ...

    www.aol.com/news/softbank-invest-search-startup...

    San Francisco, California-based Perplexity AI in January raised $73.6 million from a group of investors including Nvidia and Amazon founder Jeff Bezos at a valuation of $520 million.

  6. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    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]

  7. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a computational model capable of language generation or other natural language processing tasks. As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process. [ 1 ]

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