00:00What's going on, everybody?
00:01Welcome back to another video.
00:02Today, we're gonna be talking about SaaS.
00:10A couple of weeks ago, I was invited out to SaaS Explore,
00:13which is their big SaaS conference out in Las Vegas.
00:16Now on my channel, I have recommended in the past
00:18for people to learn SaaS for statistics.
00:21That's really all I've ever personally used it for,
00:23but I had a feeling it did more than that.
00:25So when they mentioned that this conference
00:27was gonna have a big focus on AI and analytics,
00:29I really wanted to attend
00:31because I wanted to see how these large companies
00:33were gonna be integrating AI into their software.
00:35Now, although AI and generative AI
00:37was the main focus of this conference,
00:39they still had all these booths in this giant room
00:41with everything that SaaS actually did.
00:43I honestly didn't know that SaaS did all of those things.
00:45I really just thought it was for statistics,
00:48and that is in the name of SaaS,
00:50but they do a lot of other things like data engineering,
00:54computer vision, augmented analytics,
00:55data governance, and a ton of other things as well.
00:58And so I was just kind of nerding out at every booth.
01:00I was asking a ton of questions and really digging into
01:02how each of their systems work,
01:04and they honestly looked really cool.
01:06And so now looking back, I feel kind of bad
01:08because I've only ever talked about it
01:09for statistical analysis, and I didn't really know
01:12or understand that it did all of these other things.
01:15But one of the things that interested me the most
01:16and something that I specifically came out there
01:18to learn more about was AI and generative AI within SaaS.
01:22There's really only two different things that I wanted to talk about
01:24in terms of AI and generative AI within SaaS,
01:26that I just thought was really, really cool.
01:28The first was how they can create this synthetic data
01:31that you can use to test for specific use cases.
01:34It's basically fake data that you can create
01:35for all these what-if scenarios.
01:37What if this happens and you can test the data on it
01:39to see what would happen in that scenario?
01:42That alone is a really great use of AI.
01:44And they gave an example with kidney disease
01:46and kidney transplants in healthcare.
01:48And I'm extremely familiar with that area.
01:51And so I thought the use case that they gave was really unique
01:54and something that I thought would be really useful
01:56because I've actually worked with that data before.
01:59I could absolutely see myself using something like that,
02:02using this fake synthetic data in order to test
02:05all these hypotheses or all these scenarios.
02:07The second thing that I thought was really cool
02:08is that they're implementing LLMs throughout their entire product.
02:11So at every single level of their product,
02:14you're going to be able to just chat with your data and ask questions
02:16and kind of get some of the low level tasks done quickly.
02:20That's something that a ton of other really big tech companies
02:23are trying to do and SaaS is actually doing it.
02:25So it's just really neat to see how they're executing it
02:28and how it actually works.
02:29All that to say, I feel like I need to dig into SaaS
02:31just a little bit more to really understand it
02:33and see everything that it can do.
02:35Huge shout to SaaS for bringing me out to the conference.
02:37I had a wonderful time and I got to spend time
02:39with some really awesome creators in the data space.
02:42If you liked this video, be sure to like and subscribe
02:44and I will see you in the next video.
02:50Bye.
02:52Bye.
02:55Bye.
02:56Bye.
02:57Bye.
