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The New Monitoring for Services That Feed from LLMs

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Manage episode 403590075 series 2574278
Contenuto fornito da The New Stack Podcast and The New Stack. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da The New Stack Podcast and The New Stack 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.

This New Stack Makers podcast co-hosted by Adrian Cockroft, analyst at OrionX.net and TNS founder and publisher, Alex Williams discusses the importance of monitoring services utilizing Large Language Models (LLMs) and the emergence of tools like LangChain and LangSmith to address this need. Adrian Cockcroft, formerly of Netflix and now working with The New Stack, highlights the significance of monitoring AI apps using LLMs and the challenges posed by slow and expensive API calls from LLMs. LangChain acts as middleware, connecting LLMs with services, akin to the Java Database Controller. LangChain's monitoring capabilities led to the development of LangSmith, a monitoring tool. Another tool, LangKit by WhyLabs, offers similar functionalities but is less integrated. This reflects the typical evolution of open-source projects into commercial products. LangChain recently secured funding, indicating growing interest in such monitoring solutions. Cockcroft emphasizes the importance of enterprise-level support and tooling for integrating these solutions into commercial environments. This discussion underscores the evolving landscape of monitoring services powered by LLMs and the emergence of specialized tools to address associated challenges.

Learn more from The New Stack about LangChain:

LangChain: The Trendiest Web Framework of 2023, Thanks to AI

How Retool AI Differs from LangChain (Hint: It's Automation)

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

  continue reading

301 episodi

Artwork
iconCondividi
 
Manage episode 403590075 series 2574278
Contenuto fornito da The New Stack Podcast and The New Stack. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da The New Stack Podcast and The New Stack 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.

This New Stack Makers podcast co-hosted by Adrian Cockroft, analyst at OrionX.net and TNS founder and publisher, Alex Williams discusses the importance of monitoring services utilizing Large Language Models (LLMs) and the emergence of tools like LangChain and LangSmith to address this need. Adrian Cockcroft, formerly of Netflix and now working with The New Stack, highlights the significance of monitoring AI apps using LLMs and the challenges posed by slow and expensive API calls from LLMs. LangChain acts as middleware, connecting LLMs with services, akin to the Java Database Controller. LangChain's monitoring capabilities led to the development of LangSmith, a monitoring tool. Another tool, LangKit by WhyLabs, offers similar functionalities but is less integrated. This reflects the typical evolution of open-source projects into commercial products. LangChain recently secured funding, indicating growing interest in such monitoring solutions. Cockcroft emphasizes the importance of enterprise-level support and tooling for integrating these solutions into commercial environments. This discussion underscores the evolving landscape of monitoring services powered by LLMs and the emergence of specialized tools to address associated challenges.

Learn more from The New Stack about LangChain:

LangChain: The Trendiest Web Framework of 2023, Thanks to AI

How Retool AI Differs from LangChain (Hint: It's Automation)

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

  continue reading

301 episodi

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