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Perplexity announced on Tuesday the launch of its enterprise-level API service "Sonar", allowing businesses and developers to integrate its generative AI search capabilities into their own applications. The service is available in two versions: the basic Sonar and the advanced Sonar Pro, and it supports customers in customizing the information sources of the AI search engine. Unlike traditional AI models that rely solely on training data, Perplexity emphasizes that Sonar can connect to the internet in real-time and obtain information from reliable sources, thereby providing more factual and authoritative results.

In recent years, large language models (LLMs) have made significant progress in the field of natural language processing (NLP), widely applicable in scenarios such as text generation, summarization, and question answering. However, these models rely on a token-level processing method that predicts word by word, which struggles with contextual understanding and often leads to inconsistent outputs. Moreover, when scaling LLMs to multilingual and multimodal applications, the computational costs and data requirements tend to be relatively high. To address these issues, Meta AI has proposed a novel approach.