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.
Read moreThe 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.
Read more
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.
Read moreThis 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.
Read moreLearn 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.
Read moreWhen 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.
Read moreThis 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.
Read moreWinder.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.
Read moreWinder.AI worked with Grid.AI (now Lightning AI) to investigate how Buildpacks can minimize the number of base containers required to run a modern platform. A summary of this work includes: Researching Buildpack best practices and adapting to modern machine learning workloads Reduce user burden and reduce maintenance costs by developing Buildpacks ready for production use Reporting and training on how Buildpacks can be leveraged in the future The video below presents this work.
Read moreWinder.AI worked with Protocol.AI to evaluate general-purpose computation frameworks. A summary of this work includes:
