Grad @UMD | Bridging Finance and Machine Learning | Passionate about turning data into actionable insights
While studying a multi-agent AI paper, I came across the fact that the researchers used Microsoft AutoGen to implement collaborative agent workflows. This led me to study AutoGen in depth, and I wrote an article: “AutoGen — The Multi-Agent AI Framework That Thinks Like a Team." Key takeaways from the article: 1. GroupChat: Enables multiple agents to communicate, debate, and collaborate in a shared conversation. 2. Specialized Roles: Agents like Planner, Critic, and Summarizer work together to tackle complex tasks. 3. LLM Integration: Leverages OpenAI models and can also integrate other language models. 4. Human-in-the-loop & Tools: Agents can receive feedback, use multiple tools, and share context for smarter outcomes. Read the full article here: https://lnkd.in/gzZ3_V6e
