Perplexity
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Perplexity CEO tells CNBC one metric will determine who wins the AI race
The companies that can provide the most economic value from the power their AI uses will ultimately command the highest valuations, Perplexity CEO Aravind Srinivas told CNBC on Wednesday. Perplexity is stepping up its focus on agentic AI, a term that refers to AI systems capable of handling more complex tasks beyond simple queries. In February, the company announced Perplexity Computer, an agent it says can execute complex tasks over long periods of time.
CNN is the latest media company to sue Perplexity
CNN is the latest media company to sue Perplexity, a news summarizer that has been accused of copyright infringement. The lawsuit alleges that Perplexity has been using CNN's content without permission, and that the company has been profiting from the use of the content. The lawsuit seeks to stop Perplexity from using CNN's content and to recover damages for the alleged infringement.
Perplexity plans 2028 IPO regardless of Anthropic or OpenAI listings, CNBC reports
Perplexity plans 2028 IPO regardless of Anthropic or OpenAI listings, CNBC reports June 8 : AI firm Perplexity is planning to go public in 2028 regardless of how the market receives the listings of Anthropic and OpenAI, CNBC reported on Monday, citing an interview with CEO Aravind Srinivas. • "Agnostic of these two companies, we were planning for something in 2028, so that still remains the case," Srinivas told CNBC in an interview.
Large Language Models are Perplexed by some Political Parties
Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used, including in political applications, but their political fairness has been little studied. We assess it using perplexity, posing that a fair model should give equal probability to all political groups. However, we find, across ten LLMs and three datasets covering 37 languages, that LLMs are more perplexed by the texts of far right and nationalist parties than of social-democratic parties.
Perplexity Splits AI Work Between PCs and Servers to Ease Strain
The logo of Perplexity on a laptop arranged in Riga, Latvia, on Wednesday, Aug. 13, 2025. AI startup Perplexity made a formal offer to acquire Google’s Chrome browser for $34.5 billion, an audacious bid to get ahead of a potential requirement for the search giant to sell the web browser in US antitrust proceedings.
Perplexity planning IPO in 2028 regardless of what happens to Anthropic or OpenAI, CEO tells CNBC
Perplexity planning IPO in 2028 regardless of what happens to Anthropic or OpenAI, CEO tells CNBC June 8 : AI firm Perplexity is planning to go public in 2028 regardless of how the market receives the listings of Anthropic and OpenAI, CNBC reported on Monday, citing an interview with CEO Aravind Srinivas. "Agnostic of these two companies, we were planning for something in 2028, so that still remains the case," Srinivas told CNBC in an interview.
Perplexity Can Miss SAE Feature Damage Under Quantization
Announce Type: replace Abstract: Quantization is a standard path to deploying large language models, and quantized models are typically judged acceptable when perplexity or downstream accuracy remains close to the full-precision original. But behavioral parity need not imply feature fidelity: the sparse-autoencoder (SAE) features used to interpret a full-precision model may change after weight rounding.
Perplexity plans IPO in 2028 regardless of what happens to Anthropic or OpenAI, CEO tells CNBC
Perplexity is planning to go public in 2028 regardless of how the market receives the listings of Anthropic and OpenAI, CEO Aravind Srinivas told CNBC. "Agnostic of these two companies, we were planning for something in 2028 so that still remains the case," Srinivas said in an interview that aired on Tuesday. Srinivas has previously said the company has no plans to go public before 2028.
Hacking Generative Perplexity: Why Unconditional Text Evaluation Needs Distributional Metrics
arXiv:2606.08417v1 Announce Type: new Abstract: Diffusion and continuous flow-based language models have emerged as the leading non-autoregressive alternatives to language modeling. Progress in both paradigms is overwhelmingly tracked by generative perplexity (gen-PPL): the per-token negative log-likelihood of samples under a frozen autoregressive (AR) scorer such as gpt2-large, typically paired with an empirical-entropy guardrail to rule out low-entropy collapse. We argue that this metric...
Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching
arXiv:2411.00759v5 Announce Type: replace Abstract: Discrete flow matching, a recent framework for modeling categorical data, has shown competitive performance with autoregressive models. However, unlike continuous flow matching, the rectification strategy cannot be applied due to the stochasticity of discrete paths, necessitating alternative methods to minimize state transitions. We propose a dynamic-optimal-transport-like minimization objective and derive its Kantorovich formulation for...