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Latent Space: The AI Engineer Podcast — Practitioners talking LLMs, CodeGen, Agents, Multimodality, AI UX, GPU Infra and all things Software 3.0 cover image

Llama 2, 3 & 4: Synthetic Data, RLHF, Agents on the path to Open Source AGI

Latent Space: The AI Engineer Podcast — Practitioners talking LLMs, CodeGen, Agents, Multimodality, AI UX, GPU Infra and all things Software 3.0

NOTE

Harnessing Synthetic Data for Effective Model Training

The shift back to pixel-level analysis in diffusion models may influence language models to adopt larger vocabularies, approaching natural language limits. The use of models like LAMA for data cleaning in LAMA 3 highlights the importance of selecting quality training data, especially within the noisy content available online. Research shows that applying classifiers to curate synthetic data can significantly enhance training efficiency. This method not only improves data quality but also allows for topic tagging to ensure a diverse and balanced dataset tailored to specific domains.

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