What does the Future of the SaaS Industry look like in 2019?
SaaS products analyze and solve real world cases for businesses using deep learning technology. In 2019 as well, deep learning algorithms will drive SaaS industry to greater heights.
First of all, unlike Machine Learning, which mainly centralizes the core of its efforts on solving real - world problems, which of course is beneficial, Deep Learning is a bit more, implementing what has been learned through Machine Learning and taking things a step further, still. Machine Learning incorporates neural networks and AI (or Artificial Intelligence), respectively, hoping to properly mimic the every actions of the human decision - maker, so as to more effectively enact a future response, prediction or predictability rate, and much more. Two very narrow subsets, are what ML’s (Machine Learning’s) tools focus on, mainly.
Deep Learning, as such, falls
underneath Machine Learning, as one of its major subsets, relatively speaking.
It’s one of the newest terms in its field, as well as one of the best ways to
incorporate it. So without Machine Learning, Deep Learning would not exist ----
without Deep Learning, on the other hand, Machine Learning would not be as
beneficial. The two do go hand - in - hand.
Certain Dependencies in Terms of Data
Machine Learning’s and Deep
Learning’s algorithms both base themselves off of potentially performance as the main separating
factor. Yet when the amount of data is very small, or limited in quantity, one
may find that Deep Learning algorithms may not work as well, since as has been
mentioned, they are initially designed for further, more complex and higher
amounts of data, respectively. But when there is plenty of data to be broken
down and processed, variated, and more (usually by means of larger
organizations or firms who hold growing numbers of clients and databases), Deep
Learning is the more preferable solution of the two. It is designed for engaging mass sums of information in short periods.
Certain Dependencies in Terms of Hardware
Deep Learning will, more often than not, rely upon high - end machines. Traditional, Machine Learning does the very opposite and holds its reputation for doing so, working to rely mostly on low - end machines. GPU’s, as such, become a more central requirement - component for Deep Learning initiatives. Countless, ongoing, Matrix multiplication operations, as well, can be more effectively done on a larger scale --- through Deep Learning. Similar things may be said in terms of software, as well, which is better to integrate Deep Learning to….when the need is more quantity- and quality- based.
Incorporation of Artificial Intelligence (AI) much deeper into SaaS
Without AI, SaaS solutions cannot utilizing the user’s data, predict better and help businesses get more traction in engaging users and winning new customers
AI will drive much better Automation
As seen with Salesforce and many such top solutions, AI is a driving force behind automation in SaaS. Chatbots are no longer a new trend but a necessary technology for many enterprises. Automation enables businesses to communicate better with less reliance on human resources.
With data security considered as the most important virtue for any business in the digital world, 2019 will mark prioritization of data security and data loss prevention for every SaaS business. Once again, AI will step in to automatically detect and eliminate threats.
These are a few ways AI will make SaaS more accessible and user-friendly in 2019. The fastest growth businesses have already embraced AI, and now it is your turn to do the same. Talk to us for free Consultation!