Large language models offer new opportunities for data analysis. With access to previously off-limits data such as knowledge bases and email threads, numerical information can now be put into context. Language models can be utilized as calculators on language, allowing for the combination of metadata from various sources and output from numerical models. This enables the merging of data in ways that were previously impossible, leading to the emergence of new intelligence. However, accuracy remains a challenge, and efforts are underway to ensure correctness. By combining stack traces with the program state, precise answers can be obtained from language models in most cases. The magic of these models lies in their combination with other data sources and traditional numerical models, bringing valuable insights to users.
Olivier Pomel, co-founder and CEO of Datadog, the leading observability company, discusses the company’s founding story, early product sequencing, platform strategy, and acquisitions. Olivier also shares his thoughts on their more recent expansion into security, and why he’s bullish on the potential for AI in DevOps.
** No Priors is taking a summer break! The podcast will be back with new episodes in three weeks. Join us on July 20th for a conversation with Devi Parikh, Research Director in Generative AI at Meta. **
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Show Notes:
[00:10] - DevOps and AI Potential
[06:54] - Datadog and Generative AI
[20:40] - Datadog's Acquisition and Expansion Strategy
[31:46] - LLMs in Automation and Precision
[42:35] - Datadog's Customer Value and Growth