Catalog & Cocktails: The Honest, No-BS Data Podcast cover image

Catalog & Cocktails: The Honest, No-BS Data Podcast

Live from Data Council Austin: what’s your honest no-bs take of the data world?

Mar 28, 2024
The podcast covers insights on funding, product development, AI applications, and future implications of tech advancements. It discusses challenges in data consumability, biases in large language models, evolving data processing techniques, and challenges in utilizing data effectively. Also, it evaluates the efficacy of A.B. testing in business decisions and follows a day at a data conference with discussions on data engineering topics and metadata layers for AI.
44:51

Podcast summary created with Snipd AI

Quick takeaways

  • Evaluating large language models remains a challenge in the data world, requiring a multi-stage evaluation process for reliability.
  • Robust data infrastructures are essential for successful AI implementations, emphasizing the importance of solid metadata layers.

Deep dives

AI's Impact on Data Evaluation

One of the highlights from the conference was a discussion on the challenges of evaluating large language models, stressing that the evaluation is still unsolved. Most development happens locally, whereas the assistance for evaluation is often cloud-based. The speaker outlined a multi-stage evaluation process used by major companies, ranging from basic tests to more advanced assessments, shedding light on a crucial aspect in building reliable AI applications.

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