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2. Perplexity.ai - Wikipedia

   en.wikipedia.org/wiki/Perplexity.ai

   Perplexity. Perplexity AI is an AI chatbot -powered research and conversational search engine that answers queries using natural language predictive text. [2] [3] Launched in 2022, Perplexity generates answers using sources from the web and cites links within the text response. [4] Perplexity works on a freemium model; the free product uses its ...

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

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

   The AI search startup last week announced that it had raised $73.6 million in a funding round led by IVP and including Jeff Bezos, NEA, NVIDIA, Databricks, and Bessemer Venture Partners at a $520 ...

4. Jeff Bezos–backed AI search startup’s CEO says ‘Google is ...

   www.aol.com/finance/jeff-bezos-backed-ai-search...

   On Thursday, San Francisco–based Perplexity announced that it has raised $73.6 million from a group of investors led by venture capital firm IVP and including Bezos, the $1.2 trillion AI chip ...

5. Jeff Bezos’s investment in Perplexity AI has nearly ... - AOL

   www.aol.com/finance/jeff-bezos-investment...

   Founded in August 2022, Perplexity aims to challenge Google by offering an AI-based search engine that is “part chatbot and part search engine, offering real-time information and footnotes ...

6. List of search engines - Wikipedia

   en.wikipedia.org/wiki/List_of_search_engines

   Desktop search product with Outlook plugin and limited support for other formats via IFilters, uses Lucene search engine. Proprietary (14-day trial) Nepomuk: Linux: Open-source semantic desktop search tool for Linux. Has been replaced by Baloo in KDE Applications from release 4.13 onward. License SA 3.0 and the GNU Free Documentation License 1. ...

7. Perplexity - Wikipedia

   en.wikipedia.org/wiki/Perplexity

   The perplexity is the exponentiation of the entropy, a more straightforward quantity. Entropy measures the expected or "average" number of bits required to encode the outcome of the random variable using an optimal variable-length code. It can also be regarded as the expected information gain from learning the outcome of the random variable ...