Over the past few years, we’ve seen an evolution of services available on the web and in mobile. Initially we had software as a service that was primarily made up of email platforms and then turned into pretty much everything. This included project management, finance, social, content, and everything in between. From there we got platform as a service or architecture as a service. This included APIs, servers, databases, and more. Most of the startups that launched over the past year could be found in this space. Lately however, there appears to be another evolution on the horizon. I’m calling it Data Science or AI as a Service.
We’re currently at a moment in time where we’ve reached a tipping point of data collection. What I mean by that is that most tasks we perform in a given day produce data that is collected in some way. When you think of all of the services on the web, mobile, and now the rise of wearable tech, it’s really amazing at the depth and overall expanse of collected data.
With all of this data, there seems to be an increased need to properly analyze and learn from it. With limited resources in the data scientist talent pool in most ecosystems, a rather large gap has been identified.
Data Science or AI as a Service is starting to enter the minds of founders looking for their next great startup. This includes traditional data science, machine learning, and even algorithms put into a subscription model where people can easily access the tools necessary to properly analyze and utilize their data. It will be really interesting to see what comes down the road in this space.
If you have any questions on any of these points, including companies in each evolution, please let me know.