Kunstig intelligens bliver stadig mere udbredt, og dermed følger også nye udfordringer ved brug og anvendelse af maskinlæring og datadrevne modeller. En af de udfordringer, der har meget fokus lige nu er "black-box"-problematikken, altså ugennemsigtighed af datadrevne modeller og udfordringerne med at forklare deres resultater og logik.

Her er "Explainable AI" (XAI) det nye buzzword i klassen. Men hvordan skaber man værdi og dermed forretning og vækst med XAI i praksis? Hvornår er kunstig intelligens forklaret tilstrækkeligt?

Med udgangspunkt i den seneste forskning og eksempler på hvad danske virksomheder arbejder med, vil Senior Machine Learning Specialist Niklas Kasenburg tale om potentiale af forklarlig kunstig intelligens og hvordan man kan komme i gang med det for at tilføre ekstra værdi og forretning.

Predictive Machine Learning can help with business critical decisions related to e.g. inventory management, pricing and logistics. Unfortunately, producing high quality forecasts at scale is not an easy task to take on.

Companies that want to stay ahead of the curve need to create data-driven, automated and scalable forecasting tools that are specifically tailored to their business environment. How can your business take advantage of data from several sources and empower experts and non-experts alike. In this talk Computas will give real-life examples on how companies can utilize Cloud as a business catalyst.

When implementing Predictive Machine Learning into current business you often find that data is not readily or easily available. Many businesses find themself in a state where not all data is readily available in formats needed for implementing AI. This does not mean that you cannot start your AI journey - waiting for the perfect data warehouse is rarely an option.

In this talk Computas will share stories about how we start setting up workflows that gradually weans off manual processes and puts business on a path to running global scale analytics and Predictive Machine Learning.