Remote Workshops – How To Get The Most Out Of Them Amid the COVID-19 pandemic, travel bans have been issued and meetings of all kinds cancelled... If you’re in a business where client-facing workshops are an integral part of your work (like us) then this hits home particularly hard. Questions might come to mind like: how do I keep my colleagues’ attention? How can I run this meeting as effectively as possible?
Explainable AI in the UK – the Regulatory Landscape Currently, all sorts of data are becoming more and more available. Likewise, as computing power develops, Artificial Intelligence (AI) grows into an increasingly vital part of our daily lives. However, as we trust AI with more personal and professional tasks, the question of accountability must be asked.
The Future of Artificial Intelligence (AI) in the Finance Industry is Now The stereotypical idea of a bank — elegant people sitting behind desks and stamping documents — is becoming history. Forecasts show that, by 2021, the majority of all financial operations in the UK will be done via an app. From the client’s perspective, banking has never been easier. But simply…
AI Explainability: What If the Computer Says No? Artificial Intelligence is transforming the world we know on a daily basis. But, as we trust it to make more and more choices, what if we don’t like the decisions that are made? What happens when AI denies us something and we ask for an explanation? After all, businesses have to explain their reasoning or logic and using AI doesn’t circumvent them from…
Top 5 Reasons To Use Mesh Twin Learning in Your Smart Factory All the world’s talking about Digital Twin – but let’s think a little further ahead than that. Digital Twin is just the first step, not the end destination. Mesh Twin Learning is the next phase – so let’s explore that and provide a number of key benefits that MTL is…
More Effective Machine Learning Production with MLOps Machine Learning is slowly starting to mature as a field, but many businesses are still facing tough upfront challenges. While there are a huge (and increasing) amount of new algorithms, neural network architectures and libraries, practical deployments are still in the toddler phase. However, there’s plenty of new hope for…
MLflow: Tracking ML Model Changes & Deployment in Azure In this post, we’ll cover tracking changes, as well as comparing and tracking the deployment of Machine Learning models using MLflow library. We’ll later set up resources in the Azure Cloud so we can provision our model, as well as create the Azure DevOps pipeline to deploy a new model…
