The presentation from Isa Fulford and Edward Sun offers an in-depth look into “Deep Research,” a capability within ChatGPT powered by a fine-tuned version of the o3 model. The model is built with agentic capabilities that enable it to autonomously conduct complex, long-horizon research tasks involving browsing, reasoning, data processing, and synthesis. Deep Research is positioned as a leap toward more capable AI agents that save users significant time and deliver high-quality, sourced outputs. The presentation also showcases how reinforcement learning, reasoning models, and safety measures contribute to creating a robust system meant to support real-world professional tasks—particularly in business, science, medicine, and academia.

The discussion featured Marion Carre and Valentin Schmite, co-founders of Ask Mona, alongside OpenAI's AI policy lead, Martin Signeux. The conversation explored the intersection of AI and culture, particularly how AI can enhance museum experiences, democratize knowledge, and expand accessibility to cultural heritage. Ask Mona has been using AI for nearly a decade, well before AI became mainstream, to create interactive, personalized experiences for museum visitors. The company’s work spans major cultural institutions like the Louvre and the Center Pompidou, as well as educational applications. The discussion also touched on broader themes, including AI’s role in creativity, how AI is evolving, and the ethical considerations in using AI for knowledge-sharing. Concrete examples, such as AI-powered interactive guides in museums, augmented school books, and "smart magnets" that enable conversations with historical figures, highlighted the impact of AI in making culture more engaging. Additionally, the conversation addressed AI’s ability to facilitate trust in cultural institutions and how AI could play a role in education beyond traditional settings.

During the virtual event on December 3rd, Prof. Terence Tao and OpenAI's Mark Chen and James Donovan engaged in a deep discussion on the intersection of AI and mathematics. They explored how AI models, particularly new reasoning models, could enhance traditional mathematical problem-solving and potentially transform mathematical research. The speakers discussed the integration of AI into various scientific fields, emphasizing AI's role in accelerating discovery and innovation. Key topics included the challenges of AI in understanding and contributing to complex mathematical proofs, the evolving nature of mathematical research with AI integration, and the future of collaboration between AI and human mathematicians. The conversation highlighted both the potential and the current limitations of AI in advancing mathematical sciences.