While humans have assembled a lot of weather data, flash floods are too short-lived and localized to be measured comprehensively, the way the temperature or even river flows are monitored over time. That data gap means that deep learning models, which are increasingly capable of forecasting the weather, aren't able to predict flash floods.
Weather impacts sales. Every retailer knows it. But for most, the likelihood that it might rain, snow, or sleet on the third of March somewhere in the Midwest is rarely used. Vendors such as Weather Trends have offered accurate, long-range forecasts for more than 20 years. But the opportunity is not predicting the weather; it's knowing what to do with the data. AI might change that.
We're investing a lot in AI - we're doing a lot, but we're stopping at individual productivity. We're not taking the next step. You can't just screw AI on everything - it only makes you faster. It means you need to think about, 'how are our teams collaborating? How are people collaborating?' You probably need to change the way you work.
Imagine you're selecting an influencer to work with on your new campaign. You've narrowed it down to two, both in the right area, both creating the right sort of content. One has 24.6 million subscribers, the other 1.4 million. Which do you choose? Now imagine you could find out the first had 8.7 million unique viewers last month, while the second had 9.9 million. Do you want to change your mind?
What happens under the hood? How is the search engine able to take that simple query, look for images in the billions, trillions of images that are available online? How is it able to find this one or similar photos from all that? Usually, there is an embedding model that is doing this work behind the hood.
When discussing their results, they tell us that Facebook's reporting or Google Analytics show the ad campaigns as barely breaking even. Yet they keep investing in this channel. They reason that Facebook can only see a fraction of the sales, so if Facebook is reporting a 1x return on ad spend (ROAS) then it's probably at least 2x in reality.
