Understanding the newest breakthroughs in artificial intelligence (AI) might be challenging. Still, if you’re interested in studying the fundamentals, many AI innovations can be boiled down to two concepts: machine learning and deep learning.

There are several examples of machine learning and deep learning. It’s what allows self-driving vehicles to become a reality, how Netflix decides which program you’ll want to watch next, and how Facebook identifies whose face is in a photo.

Machine learning and deep learning might appear to be synonymous buzzwords, but they are not. So, what precisely are these two ideas that dominate AI discussions, and how do they differ? Continue reading to find out.

Data is critical to how a company works and performs. Businesses need to make sense of data and discover meaning in the noise generated by the many systems and technologies. Data plays a central role in this regard.

With today’s advancement of technology that allows for mass data collection, data-driven decision-making has become the norm. From machine learning, data science, and advanced analytics …

Over the past decade, with the unprecedented growth speed of technology, advanced analytics have totally transformed the way businesses operate globally. Today, advanced analytics is …

In a previous report about the state of AI adoption and its impact on high-performing firms globally, we see that high AI performers who see …

As a fact, big corporations often have better and deeper AI adoption than SMEs – but does that equals more profits and more value? In …

Today, RPA, or Automation technologies, are widely recognized by global enterprises as a cost-effective and non-invasive way to utilize business. With RPA’s core benefits lies in valuable insights generated throughout the whole business process, Robotic process automation is applied in analytic tasks of several industries, namely assembling data, analyzing business processes, and improving them. Based on what they discover, businesses can find new domains or utilize time-consuming tasks to focus on their core competencies.

Due to the catalyst of COVID-19, in 2020, the world witnessed a global transformation in every aspect, especially in the manufacturing industry. With massive quantities …