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Secret to Production AI: Tools & Infrastructure | Data Brew | Episode 37

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Contenuto fornito da Databricks. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Databricks o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode, Julia Neagu, CEO & co-founder of Quotient AI, explores the challenges of deploying Generative AI and LLMs, focusing on model evaluation, human-in-the-loop systems, and iterative development.
Highlights include:
- Merging reinforcement learning and unsupervised learning for real-time AI optimization.
- Reducing bias in machine learning with fairness and ethical considerations.
- Lessons from large-scale AI deployments on scalability and feedback loops.
- Automating workflows with AI through successful business examples.
- Best practices for managing AI pipelines, from data collection to validation.

  continue reading

44 episodi

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What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 462513591 series 2814833
Contenuto fornito da Databricks. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Databricks o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode, Julia Neagu, CEO & co-founder of Quotient AI, explores the challenges of deploying Generative AI and LLMs, focusing on model evaluation, human-in-the-loop systems, and iterative development.
Highlights include:
- Merging reinforcement learning and unsupervised learning for real-time AI optimization.
- Reducing bias in machine learning with fairness and ethical considerations.
- Lessons from large-scale AI deployments on scalability and feedback loops.
- Automating workflows with AI through successful business examples.
- Best practices for managing AI pipelines, from data collection to validation.

  continue reading

44 episodi

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