The Institute of Foundation Models at MBZUAI focuses on advancing research in Generative AI, developing foundation models for various data types, and driving innovation in healthcare, climate change, and sustainability.
Biomedical researchers face significant challenges due to the complexity of topics and the need for trans-disciplinary approaches. The AI Co-Scientist system, powered by Gemini 2.0, aims to accelerate scientific discovery by generating, debating, and evolving hypotheses. It integrates specialized agents to interact with scientists, manage tasks, and allocate resources effectively.
The AI Co-Scientist integrates four key components:
- Natural Language Interface: Allows scientists to interact with the system.
- Asynchronous Task Framework: Implements a multi-agent system for continuous execution.
- Supervisor Agent: Manages the task queue and assigns specialized agents.
- Persistent Context Memory: Stores and retrieves agent and system states.
The system includes various specialized agents:
- Generation Agent: Initiates research and creates hypotheses.
- Reflection Agent: Reviews hypothesis quality and correctness.
- Ranking Agent: Prioritizes hypotheses using an Elo-based tournament system.
- Proximity Agent: Computes similarity graphs for hypothesis clustering.
- Evolution Agent: Refines top-ranked hypotheses.
- Meta-review Agent: Synthesizes insights from reviews and debates.
- "Deep Research" is a new trend in AI-driven research using large language models for multi-step investigations.
- The article compares Deep Research systems, highlighting capabilities and limitations like generating tangential content and handling nonsensical queries.
- Includes systems such as Gemini Advanced 1.5 Pro, OpenAI’s Deep Research, Perplexity’s Deep Research Mode, and You.com’s Research Feature.
Sakana AI introduces The AI Scientist, a system enabling foundation models like LLMs to perform scientific research independently, automating the entire research lifecycle.
