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The perplexity PP of a discrete probability distribution p is a concept widely used in information theory, machine learning, and statistical modeling.It is defined as ():= = = ()
Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries using sources from the web and cites links within the text response. [ 3 ] [ 4 ] Its developer, Perplexity AI, Inc., is based in San Francisco, California .
Perplexity measures how well a model predicts the contents of a dataset; the higher the likelihood the model assigns to the dataset, the lower the perplexity. In mathematical terms, perplexity is the exponential of the average negative log likelihood per token.
Perplexity AI reportedly secured $500 million in its latest funding round this month. That puts the startup's valuation at $9 billion, tripling its worth within six months.
Perplexity makes money by offering a Pro version for $20 per month that allows users to pick from various large language models, among them OpenAI’s GPT-4, Anthropic’s Claude 2.1, or the ...
Perplexity AI is valued at $520 million. Google’s market cap is nearing $2 trillion. Perplexity’s CEO thinks he can take them on by being better.
Perplexity is a measurement of how well a probability distribution or probability model predicts a sample. Perplexity may also refer to: Perplexity , a 1990 ...
The perplexity is a hand-chosen parameter of t-SNE, and as the authors state, "perplexity can be interpreted as a smooth measure of the effective number of neighbors. The performance of SNE is fairly robust to changes in the perplexity, and typical values are between 5 and 50.". [2]