The video explores how AI agents, particularly through systems like Stanford University’s STORM, are revolutionizing the research process by significantly reducing the time required to conduct complex inquiries. It emphasizes the collaborative potential of humans and AI, where AI handles repetitive tasks, allowing researchers to focus on innovation and decision-making.
The video discusses the transformative impact of agentic systems, particularly in the realm of research. It highlights how AI agents can significantly streamline the research process, which is often time-consuming and repetitive for humans. By utilizing AI, researchers across various fields—such as data science, engineering, finance, medicine, and academia—can accomplish tasks in minutes that would typically take hours or days. A notable example mentioned is Stanford University’s STORM, a multi-agentic system that can conduct research and generate a Wikipedia page complete with annotations in a matter of minutes.
The video begins by exploring the fundamental nature of research, which is rooted in the quest for answers to questions. The term “research” originates from the Old French word “rechercher,” meaning to seek or search for. It emphasizes that research often starts with a question, ranging from simple factual inquiries to complex, multi-layered problems that require deep reasoning and analysis. For instance, a lawyer might need to understand the implications of a landmark case in a unique context, which necessitates a more intricate research approach.
To tackle complex research questions, the video outlines a typical human research process that involves several steps: defining the objective, creating a research plan, gathering data, refining insights, and generating an answer. This structured approach mirrors the capabilities of AI agents in agentic research. These systems can replicate human-like investigation and synthesis by employing reasoning and utilizing various tools, including online and offline search APIs.
The video further explains how a well-designed agentic research system operates similarly to human researchers. It begins by defining the research objective, breaking it down into actionable steps, and assigning tasks to different agents within the system. Each agent plays a specific role, from planning to data gathering and refining insights, ultimately leading to the generation of answers. This iterative and contextual process reflects the way humans conduct research, building on previous knowledge and insights.
Finally, the video emphasizes that the future of research lies in the collaboration between humans and AI, rather than one replacing the other. By leveraging AI to handle tedious research tasks, researchers can focus on higher-value activities such as innovation, experimentation, and decision-making. The potential of agentic research is in its ability to augment human capabilities, allowing for a more efficient and effective research process. The video encourages data scientists, developers, and researchers to explore existing multi-agent frameworks to harness the benefits of agentic research in their own work.