April 9, 2024, 8:57 p.m. | MLOps.community

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// Abstract
Dive into the challenges of scaling AI models from Minimum Viable Product (MVP) to full production. The panel emphasizes the importance of continually updating knowledge and data, citing examples like teaching AI systems nuanced concepts and handling brand name translations. User feedback's role in model training, alongside evaluation steps like human annotation and heuristic-based assessment, was highlighted. The speakers stressed the necessity of …

abstract ai models ai systems annotation assessment brand challenges concepts data evaluation examples feedback human importance knowledge mvp panel product production role scaling scaling ai systems teaching training translations user feedback

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US