According to @DeepLearningAI, researchers introduced Self-Search Reinforcement Learning, a method that trains language models to simulate web searches to retrieve information from their own parameters, improving internal retrieval efficiency. Source: DeepLearning.AI tweet and The Batch summary at hubs.la/Q03VV2d-0. @DeepLearningAI reports that SSRL fine-tuning improved accuracy on multiple question-answering benchmarks and further enhanced performance when combined with real web search tools. Source: DeepLearning.AI tweet and The Batch summary at hubs.la/Q03VV2d-0. For trading context, the source highlights capability gains but does not cite specific market impacts, companies, tokens, or tickers; treat this as validated progress in model-side retrieval and QA accuracy to watch for in future product updates or research integrations. Source: DeepLearning.AI tweet and The Batch summary at hubs.la/Q03VV2d-0.