Episode Summary
How difficult will it be to train and build an AI Agent that has expertise in a given domain? Will it happen in the next year, or 3 years or 10 years? And who will benefit in the marketplace from his evolution? SHOW: 984SHOW TRANSCRIPT: The Cloudcast #984 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[Mailtrap] Try Mailtrap for free[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.SHOW NOTESOpenAI looks to train their models to replace junior bankersWHAT WOULD BE THE STAGES OF AN EXPERT AGENT?Train it on a set of standard knowledge (e.g. Masters of Accounting, Auditing, International Tax)Train it on a set of well-defined case studies, to provide industry contextTrain it on a set of adjacent case studies and other domains (business, law, specific industries)How to train corner cases?How to train gray areas like ethics, morality, or cost-benefit analysis? Who is motivated to train these experts? What would the cost of these experts be? Can it be similar to a human, or need to be a fraction, or a premium? Is there a way to build memory (e.g. experience) without disclosing client information? Is there a way to build shareable knowledge between agents for reinforcement training/learning?FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod
