PulseAugur
EN
LIVE 20:11:02

Perplexity AI trains Qwen model for optimized search and tool use

By PulseAugur Editorial · [1 sources] ·

Perplexity AI has developed a new model by post-training on top of Qwen, achieving optimal accuracy-cost trade-offs. This model is specifically engineered for enhanced search capabilities and simultaneous tool usage, integrating the tool call router for unified functionality. This advancement aims to improve the efficiency and effectiveness of AI-driven search and task execution. AI

IMPACT Enhances search and tool-calling capabilities, potentially improving AI assistant efficiency.

RANK_REASON A research announcement detailing a new model post-trained on an existing foundation model.

Read on X — Aravind Srinivas (Perplexity) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Perplexity AI trains Qwen model for optimized search and tool use

COVERAGE [1]

  1. X — Aravind Srinivas (Perplexity) TIER_1 English(EN) · AravSrinivas ·

    We’ve post trained a model on top of Qwen that achieves Pareto optimality on accuracy-cost curves.

    We’ve post trained a model on top of Qwen that achieves Pareto optimality on accuracy-cost curves. Unlike our previous post trained models, this model has been trained to be good at search and tool calls simultaneously, allowing us to unify the tool call router and

RELATED ENTITIES

RELATED TOPICS