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According to Forbes, Perplexity published a story largely copied from a proprietary Forbes article without mentioning or prominently citing Forbes. In response, Srinivas said that the feature had some "rough edges" and accepted feedback but maintained that Perplexity only "aggregates" rather than plagiarizes information.
Over time, you build the team out further with a similar approach, targeting people who can "bring in new skills," he added. The AI CEO also talked about his approach to running a company as it grew.
Of course, even Perplexity does hit a $1 billion valuation, it has a long way to go to truly challenge Google, which has enormous resources and AI talent at its disposal—and whose parent ...
The news company demanded details about how Perplexity had been accessing Times content and told the company to "immediately cease and desist all current and future unauthorized access."
For example, training of the GPT-2 (i.e. a 1.5-billion-parameters model) in 2019 cost $50,000, while training of the PaLM (i.e. a 540-billion-parameters model) in 2022 cost $8 million, and Megatron-Turing NLG 530B (in 2021) cost around $11 million. [56] For Transformer-based LLM, training cost is much higher than inference cost.
The base of the logarithm need not be 2: The perplexity is independent of the base, provided that the entropy and the exponentiation use the same base. In some contexts, this measure is also referred to as the (order-1 true) diversity. Perplexity of a random variable X may be defined as the perplexity of the distribution over its possible ...
Perplexity is raising new investment that would value the search startup at $9 billion, a source familiar with the matter said on Tuesday, a sign of heightened investor enthusiasm around ...
For Hex, 10x training-time compute trades for 15x test-time compute. [7] For Libratus for heads up no-limit Texas hold 'em , and Cicero for Diplomacy , and many other abstract games of partial information, inference-time searching improves performance at a similar tradeoff ratio, for up to 100,000x effective increase in training-time compute.