Technology that automates repetitive tasks and cost-cutting go hand in hand, so with a looming recession, it’s logical to expect RPA tools to do well. Overall, they are doing well, but in recent conversations with buyers, systems integrators, and resellers, things are not going as well as they should be.
Intelligent Process Automation
It’s hard to believe that I founded Deep Analysis five years ago (almost to the day). It’s hard to believe we made it this far and that we are looking forward to the next five. But maybe what is hardest to grasp is just how much our industry has changed over these past few years. …
This was a bullish briefing from Blue Prism. SS&C paid $1.65 billion, so we expected nothing less than a moon shot effort. Of course, the proof will be in the pudding, as a lot of product integration promises were made and there is still much work to do here. It’s also hard to imagine that this is the last acquisition SS&C will make. Will the portfolio grow even further with a process intelligence/mining addition on the horizon?
TWAIN Direct’s ultimate goal is connecting devices directly to the software app, completely removing the PC from the middle. That’s really important to the new wave of cloud developers; it abstracts the proprietary hardware layer and replaces all the other confusing scanner connectors. Plus it’s free to any developer.
Does the Zillow algorithm fail have larger meaning for AI? Some tech pundits have used this story to rail against the blind adoption of AI by businesses or to preach against the sins of replacing human wisdom with AI bots. After reading a few posts, you’d be forgiven for thinking this could be the beginning of the end for evil AI. At Deep Analysis, we thoroughly disagree with the fearmongers and naysayers.
Move over, machine learning, here come the deep learning algorithms. We predict that deep learning models will disrupt the status quo of document classification over the next 12 – 24 months, as customers discover that they can train an AI classifier with as few as five samples and deploy it in a matter of hours. Without the need for Amazon, Google, Microsoft, or IBM, and without the traditional massive compute costs and data sets associated with Deep Learning to date. Time will tell if we are right or not, but change is on the horizon.