AI and Machinelearning in 2017 – What to Expect

by Thomas Wieberneit | Dec 21, 2016 | Blog |

2016 has been the year of Artificial Intelligence and machinelearning. With the year being almost at an end, let me chime in to the gang of pundits who venture into prediction land and pronounce what we get out of our glass balls. So here are my 5 plus 2 bonus ones. AI gets mainstream in Consumer Environments Alexa paved the way, the Google Assistant is on its heels, Microsoft Cortana wants to get there, too – and Apple, amazingly, is a late starter in this environment. Amazon started with a pretty smart strategy by not overselling the capabilities of its underlying AI, as Apple did with Siri, which caused some grief for Apple and some laughs for many people around. More and more helpful Alexa skills are developed and implemented that improve its usefulness. Similarly Google; they started late but are in the game now, too – following a different strategy of adding new functionality by just making it available in contrast to Amazon, who opt to have users individually enable ‘skills’. Identification of what these systems can do will be an interesting question. Facebook’s Mark Zuckerberg created a butler for his house, who he calls Jarvis, like the one of Tony Stark in the Ironman movies. Google recently based its translation engine on machinelearning and AI, seeing vastly improved translations. Facebook’s translations base on an AI, too – although this one still seems to have a lot to learn. Not to mention all the countless other consumer services Google has, that utilize machinelearning and AIs in the background. Two of the main developments to look at here are...

Why the Phone is Dead – And How to Accommodate for It

by Thomas Wieberneit | Dec 20, 2016 | Blog |

As our (digital) lives circle more and more around mobility, and consequently the mobile phone, the questions around communication-, and in particular around service- and support channels become more interesting by the day. Facebook triggered what can be dubbed a little revolution when opening its messaging platform for chatbots in 2016; meanwhile even Skype offers chatbot support. It is safe to say that chatbots have been one of the main technology trends in 2016. Slack, originally released only mid of 2013, has become one of the main collaboration- and communications platforms. Artificial Intelligence and machine learning in various flavors and strengths have become part of many business applications throughout business’s value chains. And the combination of conversational user interfaces and AI/machine learning has the potential of changing the way people interact with businesses (and data, for what it is worth in this context). Facebook, Google, Amazon, Apple, Microsoft, to name only the big players, offer voice driven digital assistants, which already now provide a hint of new engagement models between customers and companies. Intelligent, conversational systems are what we are about to see, first predominantly using chat-like user interfaces, then also merging voice into the mix, first to cover isolated situations, then increasingly for more complicated ones. Some Data Points Business Insider reported in September that the usage of chat apps has surpassed the usage of social media, measured in monthly active users. Additionally, Google found already in 2014 that 59 per cent of smartphone owners globally install games within a week of getting the phones, which is a higher percentage than any other type of app. On the...

SAP and MachineLearning – A Strong Approach, but none too early

by Thomas Wieberneit | Nov 10, 2016 | Analysis, Blog |

In my yesterday’s analysis of SAP’s HANA announcement, I wondered why SAP stays silent on the AI and MachineLearning frontiers. Well, today I know. They saved this announcement for today. And the announcement is a bang. SAP will deliver what they call ‘intelligent business applications’ that are based upon SAP’s new machine learning platform. The platform itself shall be made available with SAPPHIRE NOW 2017. The first significant intelligent application by SAP that is mentioned, is a brand intelligence application that leverages deep learning to analyze brand exposure in video and images to provide ‘accurate, real-time insights into sponsoring and advertising ROI”. You may remember that SAP earlier showcased an application to reduce recruiting bias, which is based on the machine learning platform, too. According to Juergen Mueller, Chief Innovation Officer at SAP, the new machine learning platform is intended to serve SAP’s and their ecosystem’s applications with the goal of creating more business value. Consequently, there are two more aspects to the announcement. SAP launched a partner program dedicated to SAP Application Intelligence. SAP invests into education offerings, starting with a ‘massive open online course’ on Enterprise Machine Learning on their OpenSAP platform. MyPoV This announcement clearly shows that SAP is as serious about machine learning as the company is about leveraging the power of its ecosystem. As I, and many other people, have often said, SAP is a formidable organization if and when it chooses to drive a topic. This is shown here again. And SAP is absolutely on the right track by pursuing this three-pronged approach of delivering a platform with first solutions, encouraging partners, and...

SAP HANA 2 – Revolution or Evolution?

by Thomas Wieberneit | Nov 9, 2016 | Analysis, Blog |

Yesterday SAP announced SAP HANA 2, an updated and improved version of its flagship product SAP HANA, and new SAP HANA microservices through SAP Hybris as a Service. SAP HANA 2 will be available for first customers on November 30 and an express edition shortly after its general availability. Note: if SAP talks about RTC this usually differs from General Availability, which is only after a successful ramp-up period of about 3 months to validate a product with early adopter customers. So the Express Edition will probably be released around end of Q1/2017. In usual bold marketing words SAP HANA 2 is poised to be a “new foundation for digital transformation” and is according to Bernd Leukert, member of the executive board, Products and Innovation at SAP SE, the continuation of “breakthrough innovation on a highly stable core data platform for our customers”. SAP HANA 2 shall deliver enhancements in the areas of database management, data management, analytical intelligence and application management as well as well as two more services for cloud customers: Text Analysis and Earth Observation Analysis. The latter in a beta status only. These latter two new HANA functionalities are likely to be the reason of tying the two announcements. The update cycle of HANA 2 shall be 6 months. Some Observations It is interesting that SAP refers to the new HANA services as microservices. This suggests that these services are built on top of the HANA 2 core – or else HANA itself has been rearchitected to be built on a microservice architecture. I rather think the former, also as the delivery is via YaaS....

Omnichannel – Myth, Reality or Utopia?

by Thomas Wieberneit | Nov 1, 2016 | Blog |

Omnichannel – is it a Myth, Reality or Utopia? Over the past 20 or so years the way products and services get sold and customer service as well as marketing get delivered changed dramatically. Gone are the times where a potential customer was addressed via a radio- or TV-spot or an ad printed in a newspaper, advertising mail in the mailbox … – well, it still happens, but the focus shifted dramatically. We started off from one single ‘channel’ – customer goes to the store and interacts with a person – and added an ever increasing number of additional ones, like the ones mentioned, plus many more. For retail businesses the store will not go away. Generally spoken, human interaction will stay important, probably increase in importance; human customer service will not vanish – but is likely to change … please hold this thought. In today’s omnichannel world we also have telephone, e-mail, web-delivered ads, mobile apps, branded and white-label communities, social media like Facebook, Instagram, Twitter, etc., knowledge bases in combination with self-service, chat, messenger applications like WhatsApp, FB Messenger, Snapchat, iMessage; chat supported by ‘machine intelligence’, exposed via so called chatbots, and what not. The list could virtually go on and on. This is all supported by and implemented on a platform that leverages integrated applications, which work on a joint, or at least consistent data model – with clean data – utilizing strong real-time analytics capabilities that powers both, customer segmentation and knowledge categorization for efficient search. And it delivers a great customer experience. In Real Life Uhhm, I am just awaking from my dream …...