Category Archives: AI

AI Live Reflection

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Reflecting on the AI Live event hosted by the College of Natural Sciences at UT Austin last week, I am struck by the sense of community and collaboration that permeated the event. The gathering was a testament to our collective curiosity and commitment to exploring the vast potential of artificial intelligence within our unique context. I applaud Dean David Vanden Bout, Melissa Taylor, and the entire team that made this event a true celebration to cap off the Year of AI at UT.

One of the most memorable moments for me was witnessing the enthusiasm of the students. During Sal Kahn, founder of Kahn Academy, spoke the excitement was palpable as students waited in the hall to get in. It is a reminder of the thirst for knowledge and the drive to be part of discussions that will define our future. It was inspiring to see such a diverse group of individuals come together, united by a shared interest in AI and its implications. I loved his personal reflection on his journey to bring knowledge to everyone, everywhere. It was a reminder of the power of the Internet and its ability to create impact at scale.

Sal Kahn speaking.

The event itself was a tapestry of learning opportunities, spanning various tracks from research to health to ethics. It was a celebration of how AI intersects with different facets of our lives and how it can be harnessed to address complex challenges. The sessions were not just informative but also deeply engaging, sparking conversations that extended beyond the scheduled times.

What stood out to me was the collaborative spirit that defined the event. It wasn’t just about the presentations or the panels; it was about the interactions and the shared insights. The AI Live event was a microcosm of what we strive for in our roles – fostering an environment where innovation thrives through collaboration and where every voice can contribute to the dialogue.

Looking back, I am reminded of the importance of creating spaces where ideas can flourish and where the community can come together to explore new frontiers. It really reminded me of the early days of my career and the events we held at Penn State. Those small gatherings that turned into the TLT Symposium where we would routinely host over 500 faculty and staff to discuss innovations in the use of technology to support teaching and learning is what specifically comes to mind. The AI Live event, like the TLT events from PSU, was more than just a symposium; it was a celebration of our collective potential and a glimpse into the future we are building together. It reinforced my belief in the power of community and the incredible things we can achieve when we come together with a shared purpose.

AI Platforms, Products, and Features

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Bear with me, I am going to just do some outloud thinking. I want to make sure I get my thoughts down on leveling the vocabulary around the AI explosions happening around us. What are the differences between AI platforms, AI products, and AI features and why each has a critical role in our strategy.

I believe in an enterprise as large and diverse as ours, an AI platform will provide the foundation. In my mind, platforms are flexible, scalable, and built for creating custom solutions. They give us the ability to develop, integrate, and innovate on top of a common framework. I believe that investing in a campus-wide AI platform that serves as the bedrock for much of what we’re doing across research, teaching, and operations is the right thing to do. It’s the engine that drives AI innovation and allows the community to participate at scale to create solutions tailored to unique needs.

Visual representation of the UT.AI platform.

Then there are AI products like M365 Copilot. Copilot enhances collaboration, improves workflow, and helps us get more out of the underlying Microsoft 365 platform we’ve already embraced. An AI product is standalone, one that fits into a larger AI strategy. It exists above or adjacent to our platform, enhancing daily operations while complementing the custom AI solutions we’re building.

Finally, there are AI features like Apple Intelligence, which come baked into devices like your iPhone. These are the quiet, background AI capabilities that make your user experience more intuitive and personalized. But by themselves, they’re limited in scope—enhancing specific tasks rather than transforming entire workflows.

The strategy that I am envisioning begins with a platform approach. It gives us the power to drive true innovation and adoption by the community. Providing a common platform does not preclude us from also investing in AI products like M365 Copilot, bringing in vertical solutions that can serve parts of the university. The platform is our foundation for building and adapting AI to meet the diverse needs of our students, faculty, and staff. By leveraging one platform at this level, it allows us the greatest chance to innovate, grow our internal expertise, and control our long-term success.

More AI at UT Thoughts

AI, Thoughts

At UT Austin, we see the AI revolution as a pivotal opportunity – not just to advance research, but to apply AI in ways that directly support our core values: People, Place, Experience, and Education. We’re committed to making AI an integral part of how we achieve our strategic goals across the entire University.

To that end, we have been partnering with KUNGFU.AI – an alumni owned and operated AI management and engineering firm – to help develop an ecosystem where we put the right tools, data, and capabilities in the hands of the incredible people across the Longhorn Nation.

Our approach should be built on ensuring scalability, security, and affordability. By consolidating our AI practice into a unified platform, we’ll have the opportunity to make it accessible to all, from undergraduates to faculty, without burdening departments with commercial-level costs. This ensures we’re providing the right resources to help close the digital divide and foster equitable innovation across campus.

Diagram of the UT.AI platform and approach.

Thinking about all of this at scale, we must also be mindful of affordability. At a place like UT Austin, with over 50,000 undergraduates and nearly 15,000 graduate students, let alone the over 10,000 faculty and staff, paying $20-$30 a month per license for AI tools gets expensive. By providing a consolidated AI platform, my vision is to ensure that everyone has access to these tools.

As a university, we have a huge number of advantages including our multi disciplinarity and federated structure. Our approach to AI innovation cannot be directive, but one that enables and supports. We want to ensure people have the resources they need, know where and how to ask the right questions, and get to the right use cases for AI. A distributed governance body responsible for enabling AI tool development while offering guidance on boundaries and parameters to ensure AI is used safely and responsibly will complement our platform approach and empower AI at UT. All the while encouraging and seeding innovation across campus.

I am incredibly optimistic and excited about the work that lies ahead. I know we can build an AI ecosystem that will continue our strength and reputation as a world-class institution.

Advancing the AI Revolution: What’s Next?

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For the last several years, I have tried not to be in the business of chasing trends. My early days leading ed tech organizations, I was always looking to adopt the next digital promise — the use of the internet, the new world that Web 2.0 gave us, mobility, tablets, blah. I’ve done a lot of thinking about the impact of all that evangelism and much of it isn’t immediately measurable. Disruptive technology is often an investment in future returns, but it requires playing a longer game. With AI, I’m not sure if that holds true — the returns may be much more immediate.

To me, that nudges me toward thinking more about the diffusion of AI to as diverse of a population as possible across campus. In today’s world, I can’t think of another digital investment one could make to immediately advance human potential holistically. Can you?

Three principles emerge in my mind: shrinking the digital divide, scaling AI expertise, and building strategic partnerships that fuel innovation.

  1. Shrinking the Digital Divide: AI has the potential to change everything, but only if we make it accessible. Providing AI tools to all members of the community will foster creativity at scale, from every possible perspective.
  2. Scaling AI Expertise: We are a community that’s engaged, curious, and ready to make change. Our advantage is that community. We should be scaling the expertise that’s already here and providing thought leadership across campus.
  3. Building Strategic AI Partnerships: I know that what we plan to do will require partnerships and that is how I am approaching these opportunities. I believe as the ways that we operate will only improve by leveraging this moment to modernize operations and infrastructure.

Here we are back to the start of something new. We get to build it from the ground up. That’s pretty exciting.