In this edition of Generative AI in the Real World, Ben Lorica and Rajeshwari Ganesan talk about how to put generative AI in closer touch with human needs and requirements. AI isn’t all about building bigger models and benchmarks. To use it effectively, we need better interfaces; we need contexts that support groups rather than individuals; we need applications that allow people to explore the space they’re working in. Ever since ChatGPT, we’ve assumed that chat is the best interface for AI. We can do better.
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About the Generative AI in the Real World podcast: In 2023, ChatGPT put AI on everyone’s agenda. In 2025, the challenge will be turning those agendas into reality. In Generative AI in the Real World, Ben Lorica interviews leaders who are building with AI. Learn from their experience to help put AI to work in your enterprise.
Timestamps
- 0:00: Introduction to Rajeshwari Ganesan, distinguished technologist at Infosys.
- 0:17: We’re both builders and consumers of AI. How does this dual relationship affect how we design interfaces?
- 0:41: A lot of advances happen in the large language models. But when we step back, are these models consumable by users? We lack the kind of user interface we need. With ChatGPT, conversations can go round and round, turn by turn. If you don’t give the right context, you don’t get the right answer. This isn’t good enough.
- 1:47: Model providers go out of their way to coach users, telling them how to prompt new models. All the providers have coaching tips. What alternatives should we be exploring?
- 2:50: We’ve made certain initial starts. GitHub Copilot and mail applications with typeahead don’t require heavy-duty prompting. The AI coinhabits the same workspace as the user. The context is derived from the workspace. The second part is that generative interfaces are emerging. It’s not the content but the experience that’s generated by the machine.
- 5:22: Interfaces are experience. Generate the interface based on what the user needs at any given point. At Infosys, we do a lot of legacy modernization—that’s where you really need good interfaces. We have been able to create interfaces where the user is able to walk into a latent space—an area that gives them an understanding of what they want to explore.
- 7:11: A latent space is an area that is meaningful for the user’s interaction. A space that’s relatable and semantically understandable. The user might say, “Tell me all the modules dealing with fraud detection.” Exploring the space that the user wants is possible. Let’s say I describe various aspects of a project I’m launching. The machine looks at my thought process. It looks at my answers, breaks [them] up part by part, judges the quality of response, and gets into the pieces that need to be better.
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