Today, we are joined by Ram Venkatesh, the founder of Sema4.ai – an enterprise AI agent platform that enables businesses to build, operate, and scale AI agents. Ram shares the risks of training LLMs from agent data, and the contextual work training protocol for agents. We also unpack the requirements of a large language model when you’re not responsible for training it, the various modalities and how they can be improved, the threat that agents pose to SaaS, and Ram’s vision of the future of AI.
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Key Points From This Episode:
“I’ve spent the last 30 years in data. So, if there’s a database out there, whether it’s relational or object or XML or JSON, I’ve done something unspeakable to it at some point.” — @ramvzz [0:01:46]
“As people are getting more experienced with how they could apply GenAI to solve their problems, then they’re realizing that they do need to organize their data and that data is really important.” — @ramvzz [0:18:58]
“Following the technology and where it can go, there’s a lot of fun to be had with that.” — @ramvzz [0:23:29]
“Now that we can see how software development itself is evolving, I think that 12-year-old me would’ve built so many more cooler things than I did with all the tech that’s out here now.” — @ramvzz [0:29:14]
Links Mentioned in Today’s Episode:
Sama provides ML Professionals and AI team Leads with an indispensable solution for Computer Vision data labeling.
