Welcome to our virtual event, "Building an AI-Powered University," hosted by the OpenAI Forum. The session, moderated by Natalie Cone, OpenAI Forum Community Architect, began with a reminder of OpenAI's mission to ensure that artificial general intelligence (AGI) benefits all of humanity. The event featured a keynote speech by Leah Belsky, VP of Education at OpenAI. Leah discussed the transformative potential of AI in education, emphasizing the goals of enabling global access to AI for students and teachers, powering AI-driven educational products, and fostering collaboration to enhance AI's educational impact. The panel included Jason Horn, a technology investment banker and the evening's facilitator, who has a rich background in the education technology sector; Alex Persaud, Assistant Vice President of Enterprise Engineering and Operations at the University of Maryland, who manages critical infrastructure and co-chaired the university’s AI commission; Dr. Jaci Lindberg, who combines roles at the University of Nebraska to push innovation in digital learning and IT strategy; and David Brubaker, who leads AI initiatives at the Wharton School, focusing on aligning AI with educational priorities. During the discussion, panelists shared their diverse experiences with AI implementation at their institutions. They highlighted the impact of AI tools like ChatGPT in enhancing both the student and faculty experience and improving operational efficiencies across university functions. The session transitioned into a virtual networking event, allowing participants to engage directly with thought leaders and peers interested in AI's future role in education. The event concluded with Natalie Cone encouraging participants to continue the dialogue on AI in education through upcoming OpenAI Forum events and platforms like LinkedIn and Substack, fostering ongoing collaboration and innovation in the field.

The third Technical Success Office Hours, where we tackle technical challenges and share expert insights to support the community. Perfect for those eager to deepen their knowledge and connect with industry experts, this session offers valuable opportunities for growth and collaboration. Kevin Alwell and James Hills, Solutions Architects at OpenAI, will lead this session as we celebrate the season with cutting-edge AI capabilities designed to enhance your workflows. Dive deep into our latest releases, including exciting year-end surprises that showcase how OpenAI continues to innovate.

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.

The OpenAI Forum hosted an engaging session titled "Harvard’s AI-Enhanced Classroom: Revolutionizing Learning with Custom GPTs", featuring Jake Cook from Harvard Business School and Siya Raj Purohit from OpenAI. Siya provided insights into AI-native universities, showcasing how ChatGPT transforms education at individual, team, and institutional levels. Jake presented real-world applications of AI in his classroom, emphasizing creative experimentation, personalized learning, and the power of play to unlock students' potential. The event highlighted innovative uses of AI, including custom GPTs for dynamic teaching and adaptive learning, fostering both efficiency and critical thinking. The discussion underscored AI's role in reshaping education and left participants with actionable insights and strategies for adoption.

The webinar, part of the ongoing ChatGPT Enterprise Learning Lab series, featured Ben Kinsella, a member of OpenAI’s Human Data Team, alongside Lois Newman, Customer Success Manager, and Aaron Wilkowitz, Solutions Engineer. They explored how ChatGPT Enterprise can empower organizations by streamlining data analysis, enhancing productivity, and fostering a data-driven culture. Key Takeaways: 1. Data Security & Privacy: Lois highlighted the robust data privacy and compliance measures of ChatGPT Enterprise, emphasizing that user data is not used to train models and is fully controlled by the organization. 2. Integration with Data Infrastructure: The session outlined how ChatGPT Enterprise can seamlessly integrate with existing tech stacks, providing employees with easy access to powerful AI tools. 3. Demos and Practical Applications: Aaron demonstrated how ChatGPT Enterprise helps teams prepare, analyze, and visualize data, showcasing examples from anomaly detection to complex forecasting. AI-Powered Data Analysis: 1. Enhanced Accessibility: ChatGPT Enterprise makes it easier for non-technical employees to run analyses, freeing data scientists to focus on more complex tasks. 2. End-to-End Demos: The session included live demos showing how users can prepare data, generate visual insights, and integrate results directly with tools like Jira and Outlook using GPT Actions. Q&A Highlights: Elan Weiner, Solutions Engineer, joined for a live Q&A, answering questions about integrating ChatGPT into organizational workflows and data security concerns.

The recent OpenAI Forum event titled "How Wharton is Becoming an AI Native Institution" was a fascinating discussion led by Natalie Cohn, OpenAI Forum’s Community Architect, and featured experts like Dr. Richard Paul Waterman, a professor from Wharton, as well as his collaborators, MBA students Nupur Jain and Ceren Okar, and IT project lead Brandon Lafving. The event highlighted how Wharton has integrated AI into its educational framework, focusing on Dr. Waterman’s AI-based tools such as the "StatBot". These innovations aim to enhance the learning experience by automating tasks like summarizing lectures and improving faculty collaboration through data sharing. The team shared insights into the process of AI adoption, emphasizing that the demand for AI-powered tools is growing, with students driving the initial engagement. Throughout the event, participants also discussed broader trends in AI adoption within higher education, including how faculty and administrators can overcome challenges by integrating AI more seamlessly into the curriculum. Sia Raj Purohit, OpenAI’s education leader, further outlined a three-stage framework for AI transformation in universities, beginning with individual faculty adoption, moving toward department-level collaboration, and culminating in full organizational integration. Dr. Waterman and his collaborators demonstrated how Wharton is leading the way in AI-native education, both with student-focused AI tools and faculty-driven innovations, providing a glimpse into the future of higher education powered by AI.

Lois Newman led another session in the exciting ChatGPT Enterprise Learning Lab series. During the session, participants gained valuable insights into deploying ChatGPT widely across their organizations, along with best practices for driving user adoption. Whether attendees were just beginning with ChatGPT or looking to scale existing initiatives, the session provided actionable strategies for ensuring success. Designed to guide users through the ins and outs of GPT technology, the series offered a comprehensive overview of essential topics. The agenda covered: 1. AI Strategy 2. Change Management 3. Understanding ChatGPT Users 4. Developing Use Cases 5. Adoption Initiatives

Natalie Cone introduced three key contributors to OpenAI's O1 model, Ahmed Elkishki, Hongyu Ren, and G.B. Parascandolo, who discussed the development and reasoning capabilities of the O1 model. The speakers shared insights on how the O1 model utilizes reinforcement learning to develop its reasoning skills, including breaking down complex problems into sub-steps, error correction, and employing a structured thought process, similar to how humans solve problems. The discussion emphasized the significance of reasoning in AI, highlighting O1's ability to handle complex tasks, including high-level math problems and code generation. Ahmed presented O1's advanced capabilities, showing its superior performance in benchmarks like AIME and Codeforces, demonstrating how reasoning allows the model to explore different approaches before reaching a solution. Hongyu introduced O1 Mini, a smaller, more cost-efficient version optimized for STEM tasks, while maintaining high performance in general inquiries. The event also included a Q&A session, where the speakers addressed questions on the nuances of reasoning, O1's applicability in creative domains, and its potential impact on AGI development. Overall, the discussion showcased O1 as a pioneering advancement in reasoning-focused AI, with significant implications for the future of large language models.