Towards an AI co-scientist

Scientific discovery relies on scientists generating novel hypotheses that undergo rigorous experimental validation. To augment this process, we introduce an AI co-scientist, a multi-agent system built on Gemini 2.0. The AI co-scientist is intended to help uncover new, original knowledge and to formulate demonstrably novel research hypotheses and proposals, building upon prior evidence and aligned […]

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Agent Laboratory: Using LLM Agents as Research Assistants

Historically, scientific discovery has been a lengthy and costly process, demanding substantial time and resources from initial conception to final results. To accelerate scientific discovery, reduce research costs, and improve research quality, we introduce Agent Laboratory, an autonomous LLM-based framework capable of completing the entire research process. This framework accepts a human-provided research idea and […]

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Designing Reliable Experiments with Generative Agent-Based Modeling: A Comprehensive Guide

In social sciences, researchers often face challenges when conducting large-scale experiments, particularly due to the simulations’ complexity and the lack of technical expertise required to develop such frameworks. Agent-Based Modeling (ABM) is a computational approach that simulates agents’ actions and interactions to evaluate how their behaviors influence the outcomes. However, the traditional implementation of ABM […]

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The AI Scientist: Towards Fully AutomatedOpen-Ended Scientific Discovery

One of the grand challenges of artificial intelligence is developing agents capable of conducting scientific research and discovering new knowledge. While frontier models have already been used to aid human scientists, e.g. for brainstorming ideas or writing code, they still require extensive manual supervision or are heavily constrained to a specific task. We’re excited to […]

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European Guidelines for Use of LLMs in Research

The European Commission has put forward a set of guidelines to support the European research community in their responsible use of generative artificial intelligence (AI). As the adoption of generative AI technology continues to expand across various fields, including science, these recommendations address both the promising opportunities and potential challenges associated with its proliferation. Rooted […]

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