Ari Morcos, the CEO of DatologyAI and former researcher at DeepMind and FAIR, dives into the fascinating world of data and deep learning. He explores the nuances of data quality, emphasizing the distinction between hard and bad data points. The conversation touches on the evolution of image representation models and the critical role of data selection for model training. Ari also warns against the careless use of synthetic data and discusses how careful curation can boost model performance. Overall, it's a deep dive into optimizing data for smarter AI.

Explore the importance of data curation in AI models, challenges in data quality, removing types of data, relationship between data size and model size, choosing optimal data subset, future of data curation, impact on service providers. CEO of automated data curation platform shares insights. Estimating conceptual complexity algorithmically, automated data curation for ML training, exploring sector-specific approaches, optimizing model size and data size in ML.