In 2018, companies spent an estimated $19 billion on third-party data in the United States alone. Unfortunately, using third-party data isn’t always your best bet. In fact, it can pose a serious risk to you and your customers.
The creep factor is when companies get a little too personal with their customers. So personal, in fact, that it feels like a breach of privacy. Chances are, you’ve experienced this at one point or another, so you can understand just how unsettling it is. To avoid it, businesses can be more transparent about how they’re using customer data. Better yet, they can deliver experiences that don’t rely on using any personally identifiable information.
In the spirit of simplicity, our machine-learning scientists put together a list of some of the most enigmatic-sounding algorithms, problems, and theorems. Then, we created graphics to represent each of them. By putting a face to concepts that are typically considered abstract, we hope to make them easier to understand. We also hope to humanize them.
Businesses that are navigating AI for the first time often ask us the same thing: Should we build it, or buy it? It’s a pretty common question, actually. And a good one. That’s why we’re going to break down the pros and cons of both approaches. Then, we’ll give you our totally unbiased answer.