Multi-agent collaboration is the last of the four key AI agentic design patterns that I’ve described in recent letters...| Agentic Design Patterns Part 5, Multi-Agent Collaboration
I think Debate is probably the most exciting existing safety research direction. This is a pretty significant shift from my opinions when I first rea…| www.alignmentforum.org
AutoGen is an open-source framework that allows developers to build LLM applications via multiple agents that can converse with each other to accomplish tasks. AutoGen agents are customizable, conversable, and can operate in various modes that employ combinations of LLMs, human inputs, and tools. Using AutoGen, developers can also flexibly define agent interaction behaviors. Both natural language and computer code can be used to program flexible conversation patterns for different application...| arXiv.org
One obstacle to applying reinforcement learning algorithms to real-world problems is the lack of suitable reward functions. Designing such reward functions is difficult in part because the user only has an implicit understanding of the task objective. This gives rise to the agent alignment problem: how do we create agents that behave in accordance with the user's intentions? We outline a high-level research direction to solve the agent alignment problem centered around reward modeling: learni...| arXiv.org
We believe that LLMs will now be able to automate large swathes of knowledge work that AI previously couldn’t touch.| Foundation Capital
A Comprehensive Overview of Prompt Engineering| www.promptingguide.ai
I spent the last couple of months delving deeper into how I could integrate elements of modern machine learning with my love of building personal knowledge tools. This is a space brimming with untapped ideas and experiments to come. One open question for me is how exactly human users should interact with AI integrated into knowledge tools and creative tools.| thesephist.com