SE Radio 610: Phillip Carter On Observability For Large Language Models Software Engineering Radio - The Podcast For Professional Software Developers podcast

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SE Radio 610: Phillip Carter on Observability for Large Language Models

3M ago 1:05:06

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Phillip Carter, Principal Product Manager at Honeycomb and open source software developer, talks with host Giovanni Asproni about observability for large language models (LLMs). The episode explores similarities and differences for observability with LLMs versus more conventional systems. Key topics include: how observability helps in testing parts of LLMs that aren't amenable to automated unit or integration testing; using observability to develop and refine the functionality provided by the LLM (observability-driven development); using observability to debug LLMs; and the importance of incremental development and delivery for LLMs and how observability facilitates both. Phillip also offers suggestions on how to get started with implementing observability for LLMs, as well as an overview of some of the technology's current limitations. This episode is sponsored by WorkOS.

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SE Radio 610: Phillip Carter on Observability for Large Language Models

Software Engineering Radio - the podcast for professional software developers

55,049 subscribers

published 3M ago

Delen

MP3•Thuis aflevering

Inhoud geleverd door SE-Radio Team. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door SE-Radio Team of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.

Phillip Carter, Principal Product Manager at Honeycomb and open source software developer, talks with host Giovanni Asproni about observability for large language models (LLMs). The episode explores similarities and differences for observability with LLMs versus more conventional systems. Key topics include: how observability helps in testing parts of LLMs that aren't amenable to automated unit or integration testing; using observability to develop and refine the functionality provided by the LLM (observability-driven development); using observability to debug LLMs; and the importance of incremental development and delivery for LLMs and how observability facilitates both. Phillip also offers suggestions on how to get started with implementing observability for LLMs, as well as an overview of some of the technology's current limitations. This episode is sponsored by WorkOS.

… continue reading

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