At a Generative AI thought leadership dinner with other CTOs in NYC today and some interesting trends are emerging: * a consensus that LLMs are converging on a general set of features and basically comparable performance * a consensus that an org's data pipelines will matter more than the LLM chosen * and a group of people who read the TOS that are really scares about what these LLMs will do with access to all your data. Lastly, my prediction: the work of tech is moving from the keyboard to the whiteboard. Ai as microservice means structuring your data, thinking with ai, and chaining ai agents will supercharge your career and your cause -- but only if social change orgs platform their data. In my study of polymaths, Charles Babbage designed the basic idea for a unit of computing being something that takes an input, does something to it and gives an output -- the so called Babbage difference engine. In a real way, GenAI is approaching a world where chaining inputs ala a babbage difference engine is accessible to all. This can be an awesome opportunity if we get Non profits to work together!
Pete Grett
8mo
Converging on features, data's the new code. Exciting if structured right Steven Francisco
Director of Machine Learning and GenAI | Author of Graph Neural Networks in Action
8moThanks for sharing these insights. What I am seeing is that orgs test an idea using a proprietary LLM like OpenAI, then put it into production with an open source LLM using a development platform like Llamaindex. That way, private data remains private.