Speaker A discusses common uses of AI agents, emphasizing connecting LLMs to personal data for question-answering and deeper research. They note growing complexity, including telecom applications where agents predict network outages and recommend remedial changes to human operators. The speaker also briefly asks whether such capabilities are being used at GTC.
Some of the most basic things that we see from agents are really about being able to talk to data. Probably the first thing that we see most people try to do is they have their own personal data. They connect an LLM to that data and then they're able to ask questions. And I think, you know, more recently, they're able to ask more and deeper questions. Right. Deep research has been a big topic. It's a big topic here at qtc. And the more information you can get out of that data and the more quickly you can query that. That's a pretty standard, standard agent that we would see out there now, then they start to get a lot more complex. I think there's some really cool stuff going on in the telecom space where they're actually using agents to improve the network. So they can actually predict when there might be network outages coming and they can make recommendations to the human employees who, you know, maybe you want to make these changes. Here are the recommended changes so that you can actually, you know, still provide the service. Is that kind of thing happening at GTC right now? Are they using that kind of stuff? I wish they would.
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