Are You Joining The Machine Learning Revolution?

Jim Gold

Have you noticed that the better you know someone, the easier it is to communicate with them? When we are particularly close, this can border on the telepathic as we start to anticipate what the other person is going to say and finish their sentences. Unconsciously, our brains are collecting, processing, storing, and recalling a huge range of verbal and nonverbal signals, then translating this learning and familiarity into actions. Of course, we’re a long way from understanding – let alone replicating – the infinite complexities of the human brain. But in the simplest of terms, this is how machines can learn to interact with people.

Machine learning is one of the hottest technology trends at the moment, but the concept of giving computers the ability to learn without being explicitly programmed has been around since the 1950s. You may not even realize it, but machine learning is the technology behind the recommendation engines we use for shopping online, the personalization of our Facebook feeds, and the eerily predictive capabilities of our favorite search engines. In effect, the machines are getting to know you and communicating more effectively as a result. The really exciting bit is the potential for more sophisticated machine learning in business applications. As Markus Noga, head of Machine Learning Incubation at SAP, puts it: “Machine learning has revolutionized consumer applications, and the time is now to revolutionize enterprise applications.”

The strength of machine learning is its ability to identify patterns that humans may overlook or are unable to find quickly in vast amounts of data. Deep learning (also known as cognitive computing) takes this a stage further by using multi-layered neural networks that simulate human thought processes and enable machines to use input data sets and sophisticated algorithms to solve complex, nonlinear problems. Deep learning is the technology behind breakthroughs such as facial recognition software, self-driving cars, and smart home automation devices. These innovations are already revolutionizing the way we live, from strengthening cybersecurity and increasing public safety to improving medical outcomes.

Just think of the possibilities if you could embed this intelligence into enterprise applications. Repetitive, labor-intensive tasks such as manually matching payments to invoices or checking travel expenses would be done automatically – taking time and cost out of the process and improving accuracy. Or instead of sifting through thousands of job applications by hand, a machine can automatically match the best candidates to a job description in seconds.

These are just the tip of the iceberg. Advances in artificial intelligence (AI) technology mean that self-learning algorithms may soon come to their own conclusions within certain parameters and develop context-sensitive behavior. Devices will soon be able to schedule meetings, translate documents, and take on other routine business tasks.

If this all sounds like science fiction, it’s not. Machine learning in all its forms is here to stay, and the good news is that it’s available to everyone. The growing popularity of cloud computing means that processing power and storage are now more affordable than ever, so what are you waiting for?

In March 2017, SAP and Google Cloud announced a strategic partnership focused on developing and integrating Google’s best cloud and machine learning solutions with SAP enterprise applications. At the recent SAPPHIRE NOW, SAP and Google Cloud discussed machine learning in a keynote session.


Jim Gold

About Jim Gold

Jim Gold is Senior Director of Global Technology Partner Marketing for SAP. He is responsible for co-marketing, business development and co-innovation of key SAP strategic alliances. Jim previously held product marketing positions in support of SAP development and virtualization technologies. Prior to SAP, he worked in senior marketing and business development roles at large, midsize and startup technology companies and began his software career at IBM. Jim graduated cum laude from the University of Vermont and has done graduate work in business and political science