AI, Machine Learning, Reinforcement Learning, and MLOps Articles

MLOps in Finance

Published

Jun 15, 2023

Author

Dr. Phil Winder

CEO

Our client is a UK-based financial services company specialising in offering loans for car finance. They leverage AI in their processes and are looking to expand its use. They realised that they would benefit from a comprehensive review of their machine learning operations from the perspective of MLOps experts, Winder.AI. As a finance industry specialist, we understand the unique challenges and regulatory requirements in this sector.

Reinforcement Learning for Power Generation

Published

Apr 20, 2023

Author

Dr. Phil Winder

CEO

Genesis Energy is a power generation company in New Zealand that sells electricity generated by hydroelectric and hydrothermal generators to the domestic energy market. Currently, people control the decisions surrounding power generation and pricing. Genesis asked Winder.AI to help them develop a reinforcement learning-powered solution to automate generation and pricing.

Reinforcement Learning Problem

New Zealand has the enviable situation of possessing high-altitude lakes refilled with ice melt. Discharging the lake presents an ample kinetic energy store that can be utilised for power generation via a turbine. Hydroelectric power generation is therefore sustainable and low carbon.

Presentation: MLOps and the Online Safety Bill

Published

Mar 21, 2023

Author

Dr. Phil Winder

CEO

This is a video of a presentation about the UK’s online safety bill. This places new burdens on social media companies to moderate content to keep the public safe. This video discusses how platforms are using MLOps to help operate AI solutions that allow them to scale and prevent hundreds of violating posts from being published every second.

How Social Media Platforms use MLOps and AI Governance to Help to Moderate Content

Published

Jan 30, 2023

Author

Dr. Phil Winder

CEO

The UK’s communications regulator, Ofcom, commissioned Winder.AI to produce a report to improve their understanding of the end-to-end processes that support the creation and deployment of automated content classifiers used in moderating online content.

Do you like DAGs? Implementing a Graph Executor for Bacalhau

Published

Jan 24, 2023

Author

Enrico Rotundo

Associate Data Scientist

Winder.AI helped Protocol Labs, a technology company in the crypto space, to help develop Bacalhau, a novel decentralised computational platform that focuses on the AI lifecycle. This case study describes some of our work to develop this project but for more information view the Bacalhau website.

RL Presentation: How to Overcome Reinforcement Learning Challenges

Published

Dec 14, 2022

Author

Dr. Phil Winder

CEO

This presentation discusses some of the greatest challenges for a reinforcement learning project. I will share some of the challenges we have faced and how we have overcome them. You’ll learn what to look out for and how that affects the planning process.

RL Presentation: Finding and Executing Reinforcement Learning Projects

Published

Nov 22, 2022

Author

Dr. Phil Winder

CEO

Learn about the framework that we use to help organizations find and develop problems that are best suited to reinforcement learning. This includes information about how to find business problems that are suited to RL, how to derisk the development process, and what technical tasks are involved.

An Introduction to Reinforcement Learning: All You Need to Know

Published

Oct 13, 2022

Author

Dr. Phil Winder

CEO

When a child wants to ride a bike, they learn by doing. This process of trial and error is also known as learning through reinforcement, because positive and negative experiences promote or discourage certain behaviours, respectively. Children learn to ride by avoiding actions that cause them to crash; for the thrill of feeling wind in their hair.

Pachyderm ❤️ Spark ❤️ MLFlow - Scalable Machine Learning Provenance and Tracking

Published

Aug 23, 2022

Author

Enrico Rotundo

Associate Data Scientist

This article shows how you can employ three frameworks to orchestrate a machine learning pipeline composed of an Extract, Transform, and Load step (ETL), and an ML training stage with comprehensive tracking of parameters, results and artifacts such as trained models. Furthermore, it shows how Pachyderm’s lineage integrates with an MLflow’s tracking server to provide artifact provenance.

Optimising Industrial Processes with Reinforcement Learning

Published

Aug 9, 2022

Author

Dr. Phil Winder

CEO

Winder.AI helped CMPC, a large paper milling company, to optimise their production process by using reinforcement learning. CMPC are now able to automate industrial processes that were previously manual. This case study describes our approach and the results.