GuShiio.com ① It is reported that Grok3 is trained to synthesize data and can be reviewed for logical consistency.
② At present, synthetic data is showing huge value potential in the AIGC era and is widely used in all walks of life in the field of artificial intelligence, demonstrating the enabling role of “artificial intelligence +”.
Musk announced the release of Grok 3. Grok-3 and Grok-3 mini both surpassed or competed with rivals such as Gemini, DeepSeek and ChatGPT in multiple test scores. It is reported that Grok3 is trained to synthesize data and can be reviewed for logical consistency.
Currently, the artificial intelligence paradigm is undergoing a shift from “model-centric” to “data-centric”. As one of the “troika” of artificial intelligence infrastructure, data is the cornerstone of building and optimizing AIGC models, and is often referred to as the “fuel” in the field of artificial intelligence. Musk said that the data used to train AI models in the real world is almost exhausted, and synthetic data is the solution for the future. Market analysis points out that synthetic data, as a kind of “renewable energy” trained by large models, has the advantages of low acquisition cost, high quality and avoidance of privacy violations. At present, synthetic data is showing huge value potential in the AIGC era and is widely used in all walks of life in the field of artificial intelligence, demonstrating the enabling role of “artificial intelligence +”.
According to the Cailian theme library, among the relevant listed companies:
LiardIt said that large action models can help agents and others complete fusion calculations such as synthetic data and reasoning. Data enhancement needs to be based on stable features. The company is already trying synthesis methods of different actions, and the improvement of reasoning performance is also being optimized.
xinghuan technologyHe said that the company has researched and used synthetic data and is exploring related solutions. The company’s big data development tool TDS can be combined into data development, data governance, and data operation suites according to customers ‘actual needs to meet the needs of enterprise users.
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