Article | August 11, 2020
The life sciences industry is at a turning point. According to Deloitte, “to prepare for the future and remain relevant in the ever-evolving business landscape, biopharma and medtech organizations will be looking for new ways to create value and new metrics to make sense of today’s wealth of data.” For life sciences companies using outdated legacy on-premises and cloud database systems, however, the exploding volume and variety of data pose significant management and security challenges.
Article | December 21, 2020
Machine learning — a branch of artificial intelligence that gives computer systems the ability to automatically improve and learn from experience — has been making serious waves for the last few years. More recently, though, the applications for smartphones and other small screen experiences have started to take shape, driving the way millions interact with their mobile devices.
Yes, Your Mobile Devices are Becoming Smarter
So what do these innovations means for your business? Machine learning can, essentially, make your smartphone “smarter” by improving a host of functions and processes instantly. In fact, most smartphones are already using some type of machine learning or intelligent automation application that aids mobile devices in becoming more efficient and effective. Predictive text messaging, for example, is one such application that’s already become part of the mobile vernacular — chances are, you use it daily without thinking twice.
As a whole, businesses are ramping up their machine learning investment, meaning we’ll be seeing more of this technology — and more accessible versions of this technology — in the coming months and years. For each generation, there’s an added level of intuitiveness when it comes to mobile technology — your current smartphone is smarter than the computers that helped bring man to the moon, in many ways. From that end, how advanced will our mobile devices be in another 10 or 20 years? Smartphones could be paving the way for Robotic Process Automation (RPA) and evolving the very way many industries work.
What’s Next for Mobile Machine Learning
Historically, machine learning requires a tremendous amount of power — power mobile devices simply didn’t have. However, businesses can now install special chips in drones, automobiles and smartphones enabling them to consume 90 percent less power. As a result, mobile devices — even without an internet connection — can perform a variety of once-complex tasks, including:
Virtual / Augmented Reality
Smarter Camera Functionalities
Improved Device Security
Going forward, envelope-pushers are driving towards even bigger, better, more sophisticated applications — think motion control and navigation, diagnosing and analyzing sensory data and more. Interactivity or perceptual interfaces are also capabilities that the new applications are expected to be equipped with, giving mobile devices seemingly endless capabilities.
Due to these unique benefits, machine learning on small devices is clearly becoming a priority for businesses.
Article | March 29, 2020
As our world has become filled with screens in our work as well as personal lives, it has also become filled with more and more visual imagery – and it can all start to feel a bit garish, a bit fake or simply too much. For some time now, whenever I’m in the office, instead of sitting in front of my laptop over lunch, I force myself away from my desk for 15 minutes, find a quiet space or just sit in my car, put in my earphones, turn on some music, and close my eyes. I've found that I can actually relax better by tuning out the visual world and concentrating on my music. I sleep better, I dream better, I live better. Even the brief lunch break clearly does some good, as I often work and engage better in the afternoon too. According to a recent study, I’m not alone. Feeling increasingly distressed by fakery and overloaded with superficial images, millennials and Gen Z in particular are seeking deeper connection, greater meaning and more mindfulness – and they’re finding it when they close their eyes and start to listen.
Article | April 1, 2020
Most of the time, collaborating on a software project means working with tools like Git—taking turns making modifications, then reconciling the final product into a single codebase. But live collaboration on code—two or more people working on the same file in real time—has become far more viable in recent years. You’ll still want to have one person sign off on the final code, but being able to see other people’s edits as they happen is a great boon for distance learning, crunch-time work, and peer review.