What Is Artificial Intelligence?

Thadeus Suzenski

The term artificial intelligence (AI) is thrown around in many contexts, especially in the tech industry. However, many people (including those in IT) don’t actually understand what AI is, let alone the challenges and opportunities it presents. This is the first in a series of “AI for Dummies” blogs where I’ll share the basics of all things AI.

Why does AI matter?

As computer systems become ever more capable of performing the tasks that traditionally are staffed by humans, this evolution will affect nearly every industry. In the short term, there will be positions that are replaced by machines that lead to job loss. However, over the longer term, higher skilled workers will be increasingly needed to manage and maintain these machines and systems.

What is machine learning?

At its most basic, machine learning (or AI) involves “teaching” a computer to learn and change when given a vast amount of data. The computer is not necessarily explicitly programed for these changes, but instead learns to spot patterns and make connections. Therefore, the machine learns (get it?) to complete the task on its own. (Source: SAP.com)

What is deep learning?

Deep learning, or as it is alternatively known, cognitive computing, is a more advanced version of machine learning that uses neural networks to emulate human thought processes. The synapses of the human brain are mimicked by utilizing networks of small computing nodes. This allows the computer to solve complex, non-linear problems (Source: SAP.com)

What’s the difference between strong AI and weak AI

There are two popular classifications of artificial intelligence: Strong AI and Weak AI. Strong AI is aimed at replicating human thought, while Weak AI is generally about just getting the systems to do a specific task. Strong AI is further from realization at this point, but is very likely to become a reality (though the timeline for this is subject to much debate). Weak AI might be able to copy a human thought pattern to some extent, but it does not go deep into how the human decision process works.

Weak AI technology is already in broad use, with explosive growth expected as systems are vetted and standardized. Industry needs vary, and while there are many companies utilizing Weak AI, there are many more that would benefit from a robotic transition leading to reliability, cost savings, and functionality improvements.

Why the future of machine learning depends on interconnectivity

Interconnectivity will be the core of success for the AI and machine learning revolution. SAP is utilizing the Internet of Things (IoT) to connect systems as never before. Our market leading SAP HANA S/4 platform will continue to drive Big Data, pushing machine learning to analyze and process in ways never before imaginable.

As SAP moves forward into this new market, we will be working towards navigating the complex and evolving commercial framework. New challenges will be faced from a business, legal, and social standpoint, but these will also open market-making opportunities and a chance to lead with empathy. These will be addressed in the next installment of this “AI for Dummies” series.

Learn more about machine learning and artificial intelligence by reading our other blogs on predictive intelligence.


Thadeus Suzenski

About Thadeus Suzenski

Thadeus Suzenski is Senior Legal Counsel for SAP SE and is a member of both the Pennsylvania and New Jersey Bar. While his current position predominately involves both drafting and negotiating software services transactions, he also manages field-marketing legal issues and assists with pre-litigation for regulated industries. In addition to his legal functions, Thadeus is charged with writing about Artificial Intelligence & Machine Learning for the company’s Digitalist Magazine. Previous positions at SAP include roles in both Business Operations and Project Management.