There's a lot of discussion about how accurate artificial intelligence actually is. What's most important is really two pieces of that. One is the data and two is the algorithm. It really comes down to those two pieces. Now, there's a lot that happens between the data and the algorithm and then obviously the output. But it's hard to say how accurate artificial intelligence is. What's most important is to understand how efficient the data is being moved through the model. How it's being trained, what those data sets look like, how we're managing things like data drift and bias, missing data, minimum and maximum values, all sorts of different areas that need to be tracked with a model and then ultimately looking at the output. It's why the use of artificial intelligence isn't a start and stop type of project. Where most people are focused on is just bringing their models into production so they can be leveraged in the most effective way. But that's actually where you're just starting the process of that second phase of being able to manage these models when they're in production. We want to all make sure that the games we're playing on our phones are challenging enough that we want to keep playing, but not so hard that we never want to return to them. That's all artificial intelligence. We want to be able to know that when we go on to any commerce site that we're being served up the products that would be most interesting to us, or that we're getting the best rates on potential travel opportunities. All of that is driven through artificial intelligence. Understanding its accuracy is an area that is more defined by how it's having an impact in the real world. And how are we able to manage that? Most importantly, how are we also able to observe that and monitor it so that we can make adjustments backwards? Let's go back and look at the data. Let's retrain the models. Let's adjust the algorithm and then let's see what the output is. But overall, artificial intelligence is having an incredible impact across almost every industry that you can think of. If it's manufacturing, if it's health care, if it's insurance or finance, if it's in gaming or in autonomous driving, everything is being driven in many, many ways by artificial intelligence. And what makes the boss platform so unique is our ability to apply the same approach for artificial intelligence across all of these different vertical industries, but allow them to have an impact across different use cases that are at the core of what each individual company needs to do. Remember, there's a technology level that drives artificial intelligence. Then there's the use case level. And while the technology level, the algorithm itself may be similar, or the model itself may be similar, how it's applied from a use case perspective is what really drives the value to individual businesses and individuals.