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A recent joint study by Google, Carnegie Mellon University, and MultiOn explores the application of synthetic data in training large language models. According to Epoch AI, a research institution focused on AI development, currently available high-quality text training data totals around 300 trillion tokens. However, with the rapid advancement of large models like ChatGPT, the demand for training data is growing exponentially, projected to exhaust existing resources by 2026. Therefore, synthetic data is becoming increasingly crucial.

Meta recently announced the launch of the latest member of its Llama series - Llama3.370B. Meta's VP of Generative AI, Ahmad Al-Dahle, announced this on the X platform, noting that Llama3.370B has achieved significant improvements in performance compared to Meta's previous largest Llama model, Llama3.1405B, while significantly reducing costs. Al-Dahle stated that by leveraging the latest technology after training, Llama3.370B...

Google recently launched its latest AI model series, Gemini 1.5, which includes Gemini 1.5 Flash-8B, Gemini 1.5 Flash, and Gemini 1.5 Pro. These models are designed to handle long texts and large amounts of multimodal inputs such as documents, videos, and audio. Gemini 1.5 Flash is a lightweight version with 8 billion parameters, significantly enhancing performance and becoming the preferred choice for developers worldwide. Gemini 1.5 Pro excels in mathematics, coding, and handling complex prompts.