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    Alignment is Real - Fine-Tuning vs. Prompting in Domain-Specific Tasks

    MLOps.community0.0
    39 minutes
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    Alignment is Real - Fine-Tuning vs. Prompting in Domain-Specific Tasks

    YouTube·MLOps

    Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the intricacies of AI alignment and domain-specific model fine-tuning in this MLOps Podcast episode featuring Shiva Bhattacharjee, CTO of TrueLaw Inc. Delve into the necessity of fine-tuning versus prompting, and discover the innovative loop of sampling, feedback collection, and fine-tuning that yields superior performance in specialized tasks. Learn about DSPy implementation, RAG strategies, cost-effective embedding fine-tuning, and AI infrastructure decision-making. Gain insights into prompt data flow evolution, the buy vs. build dilemma, and essential tech stack considerations. With 20 years of experience in distributed and data-intensive systems, Bhattacharjee shares valuable perspectives on creating models that excel in domain-specific applications, offering a 7-10x improvement over base models.

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