原始对话

Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph

Training Data · · 52:28

Ben Rudolph says early AI use may look like improved search. As users become familiar with the product, they begin doing deeper analysis that had previously been impossible. He describes how agents identified a three-day weather pattern linked to sand channels and rip currents — a finding that gave the agency something actionable to consider. Rudolph argues that accurate data remains essential for charts, agents, and future technologies. Peregrine’s core strategy, he says, continues regardless of changes in its tools.

Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph
Training Data

一目了然

关键时刻3

简短、标注来源的段落,并附有可验证上下文。完整对话保留在其发布者处。

企业级AI

Users can move from search to deeper analysis

原始摘录

As users get more used to the product and understand how it works, you start to see the floor get raised for everybody across the department, and you start seeing these really interesting, deep types of analysis that previously were just impossible.
上下文

When you initially deploy this type of AI to these organizations, you often just get what I'd call nice search. Maybe you were looking for an address, and now you don't have to look at a bunch of rows — you see everything that happened at that address, in a nicely formatted way.

企业级AI

Agents helped uncover a reported rip-current pattern

原始摘录

And those rip currents cause a lot of issues for people who are in the water at that time.
上下文

So they started asking Peregrine, interrogating this question. And what they started to uncover — these weather patterns had happened before, but after a couple of iterations, and the agent doing some deep research, out came the pattern: these weather patterns had never occurred for three consecutive days. And those types of weather patterns create these sand channels, and those sand channels are the perfect conditions for rip currents. That is actionable for the agency — they can think deeply about that.

企业级AI

Accurate data remains essential as tools change

原始摘录

The same is true with agents, and the same will be true with the next technology.
上下文

So much of what Peregrine does and is, on the technology side, is emergent. Peregrine has been providing domain expertise — we deeply understand and empathize with law enforcement, fire departments, EMTs — and then we provide technology to enable them to achieve their most important missions. That technology can change over time, and that's the great thing about it. Most of it is downstream of really high-quality data: you can build charts, and that chart is completely useless if it's not accessing the right, accurate information. So I believe the core strategy of Peregrine has remained very unchanged in this new age of AI. We're just applying a new technology to see how it impacts our customers.

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