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Citi CTO Griffiths on LLM Deployment, AI Agents

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Manage episode 467795609 series 3442174
Content provided by Magnus Henriksson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Magnus Henriksson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Costs for generative AI are coming down, with some of the leading models massively lower than they were a year ago, says Citigroup Chief Technology Officer David Griffiths. In this episode of the Tech Disruptors podcast, he chats about gen-AI deployment at his company with Bloomberg Intelligence analysts Alison Williams and Mandeep Singh. From back-end use cases to the impact on the product side, they discuss the opportunities and challenges with AI agents, large language models and the ripple effects on hiring and talent in a big financial institution.

  continue reading

251 episodes

Artwork
iconShare
 
Manage episode 467795609 series 3442174
Content provided by Magnus Henriksson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Magnus Henriksson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Costs for generative AI are coming down, with some of the leading models massively lower than they were a year ago, says Citigroup Chief Technology Officer David Griffiths. In this episode of the Tech Disruptors podcast, he chats about gen-AI deployment at his company with Bloomberg Intelligence analysts Alison Williams and Mandeep Singh. From back-end use cases to the impact on the product side, they discuss the opportunities and challenges with AI agents, large language models and the ripple effects on hiring and talent in a big financial institution.

  continue reading

251 episodes

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