Greg Kostello
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gregko.bsky.social
Greg Kostello
@gregko.bsky.social
CTO, Huma.ai. Carbon-based LLM, known to hallucinate at times but knowledge current as of today. I'm here to learn more of how AI can unlock knowledge, solve challenges, and uplift humanity.
For AI and SWE nerds (like myself): I developed an AI agency to help me develop production code. Here is my commit after three days:
556 files changes. Unit tests, integration tests, service tests all using both traditional software engineering methodology and agent based approaches. #AI #agents
January 22, 2025 at 7:39 PM
At the Axios AI conference, listening to the chairman of OpenAI, Brett Taylor and his perspective on their mission. Agencies are the now and the future.
December 17, 2024 at 11:02 PM
One of the best, most honest post-mortems on what the hell happened with the election. How did Trump win? It's because we've been thinking about it all wrong. Van Jones and Chris Cillizza tear it down. open.substack.com/pub/chriscil...
Van Jones is the most honest man in politics
A conversation you are going to want to hear.
open.substack.com
December 14, 2024 at 9:02 PM
Agentic RAG - advanced approach leverages multi-agent systems for query decomposition, self-correction, and multi-hop reasoning. Use in domains like healthcare and finance by delivering precise, adaptive insights from complex data. #AgenticRAG #AI
ragaboutit.com/agentic-rag-...
Agentic RAG: A Complete Guide to Agent-Based Retrieval Augmented Generation – News from generation RAG
Understanding Agentic RAG: The Evolution of Information Retrieval Retrieval Augmented Generation (RAG) has undergone a significant transformation with the emergence of Agentic RAG, representing a leap...
ragaboutit.com
November 24, 2024 at 11:03 PM
MIT researchers unveiled Model-Based Transfer Learning (MBTL), a groundbreaking approach that makes AI agents up to 50x more efficient at tackling variable, complex tasks.
💡 How it works: MBTL trains on a strategic subset of tasks, transferring knowledge across other.

news.mit.edu/2024/mit-res...
MIT researchers develop an efficient way to train more reliable AI agents
MIT researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability. This could enable the leverage of reinforc...
news.mit.edu
November 24, 2024 at 5:52 PM