Abstracto

Machine Learning 2018: Machine learning: An enabler of business strategy and innovation- Sylvester Juwe -British Gas

Sylvester Juwe

Computerized change is an excursion which originates from solid convictions in advanced economy by senior administration bolstered by a computerized change system. Methodology is considerably harder to send than create and it might possibly be accomplished when the change is driven by CEOs fortified by develop capacities. Sadly, most advanced change activities have flopped previously and a lot more will bomb later on. These disappointments have been fundamentally because of associations undertaking computerized change rather than advanced change notwithstanding the absence of capacities and non-preparation of the organization to deal with this change. New computerized developing innovations remain the spine and the empowering influence of any advanced change exercises. The digitization of tasks, workforce, advertising and new advanced plans of action will be acknowledged by the union of all new rising computerized innovations through new items/administrations, value, client experience and stage esteems. In this discussion, information science, AI, investigation, enormous information, IOT and their interrelationships will be illustrated. Instances of how computerized activities could help the business by improving productivity, keeping away from trips, lessening impromptu personal time and changing from time sensitive to condition-based upkeep will likewise be delineated. AI is independent intelligence comprehended by computers. That simple definition of AI is a significant break from the traditional notion of computing where humans develop application code and then input information for the code to deterministically process and provide output in accordance with the rules of the code. AI, however, is able to self-adapt the code and the associated rules and algorithms to achieve a goal. Many articles on AI frequency refer to mechanical mechanisms such as robotics. However, AI lives in software – code, associated rules and especially algorithms. Mechanical mechanisms are just one form of the application of AI. And, perhaps, it’s conceptually easier to speak to the concept of AI by utilizing tangible examples that manifest the everyday use of AI. For example, the concept of self-driving “autonomous” vehicles (cars, trucks, container ships and airplanes) is a wonderful example of the current state of AI and the direction in which AI is moving. Later in this post I will provide business process / business-to-business examples of AI. Why is “digital transformation” such a hot topic today? Cleary, mobile computing, cloud computing, enterprise application software, software as a service and web service integration are key enablers of digital transformation. These enablers, however, are mainstream at this point - well understood and are already incorporated into the vast majority of organizational and I.T. modernization strategies and solution initiatives. There are, in my opinion, three digital transformation enablers that are not yet as mainstream but are rapidly emerging and being incorporated into the organization and I.T. modernization strategies of the technological innovators, early adopters and some of the early majority. These enablers include, Artificial Intelligence & Machine Learning, Big Data & Predictive Analytics and Business Process Automation.In this post I define how Artificial Intelligence (AI) and machine learning disrupts traditional industry models and business practices to deliver exceptional customer and business value to create sustainable (existential) competitive advantage for your organization.

Biography:

Sylvester Juwe is a highly experienced and qualified Artificial Intelligence Lead, currently a Senior Data Science Manager at British Gas, United Kingdom. Operating at strategic levels, he leads on the leveraging sophisticated machine learning and big data analytics and capabilities in enabling and driving business strategy thereby creating business value. He has experience in the exploitation of a range of data mining, advanced analytical and artificial intelligence techniques to understand customer behavior, derive critical insights, optimize operations and solve complex business problems.