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Databricks has introduced new AI innovations within its Lakehouse platform, enabling customers to develop generative AI applications, including large language models (LLMs), with ease. These innovations include Vector Search, a curated collection of open-source models, LLM-optimized Model Serving, MLflow 2.5 with LLM capabilities, and Lakehouse Monitoring. By unifying the data and AI platform, Databricks simplifies the process of developing and deploying generative AI solutions, allowing organizations to accelerate their AI journey. This integrated approach offers benefits such as improved data quality, faster development, and effective governance. JetBlue, for example, has leveraged Databricks' platform to build their own LLM, enhancing decision-making using real-time data streams and improving user onboarding times.

Speakers By


Maria Zervou

Senior Specialist Solutions Architect, Databricks

Maria is a Greek-expat experiencing the London life… and weather! With a Data Science degree and a lot of curiosity about how coding and data can unlock new ways of solving problems, her journey to the data world started. Maria has worked as a Data Scientist and an ML engineer for the past 5 years, where she experienced how data actually challenges and transforms the way we think and operate.

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