Winder.AI Blog

Industrial AI insight about machine learning, reinforcement learning, MLOps, and more...

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Save 80% of Your Machine Learning Training Bill on Kubernetes

Save 80% of Your Machine Learning Training Bill on Kubernetes

Mon Jun 6, 2022, by Phil Winder, in Cloud Native, MLOps, Case Study

Winder.AI worked with Grid.AI to stress test managed Kubernetes services with the aim of reducing training time and cost. A summary of this work includes: Stress testing the scaling performance of the big three managed Kubernetes services Reducing the cost of training a 1000-node model by 80% The finding that some cloud vendors are better (cheaper) than others The Problem: How to Minimize the Time and Cost of Training Machine Learning Models Artificial intelligence (AI) workloads are resource hogs.

MLOps Presentation: When do You Need an MLOps Platform Team?

MLOps Presentation: When do You Need an MLOps Platform Team?

Wed May 11, 2022, by Phil Winder, in MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s MLOps consulting experience at a variety of large and small organizations. Abstract In this talk he presents industry observations of MLOps team size and structure for a range of business sizes and domains. Learn more about how others structure their MLOps teams. Discover which problems you need to solve first. About This Series Welcome to Winder.AI talks. A series of free interactive webinars hosted by Dr Phil Winder, CEO of Winder.

MLOps Presentation: Databricks vs. Pachyderm

MLOps Presentation: Databricks vs. Pachyderm

Wed Apr 6, 2022, by Phil Winder, in MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s MLOps consulting experience at a variety of large and small organizations. Abstract In this talk he presents a white paper that discusses the differences between two leaders in the data engineering space – Databricks and Pachyderm. Learn how these two products differ, when to use each, and the pros and cons. At the end of the talk Phil distils this information and presets best practices.

Machine Learning Presentation: Packaging Your Models

Machine Learning Presentation: Packaging Your Models

Wed Mar 16, 2022, by Phil Winder, in Machine Learning, MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s machine learning consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on packaging ML models for production serving. Learn about how the cloud vendors compare, what orchestration abstractions prefer, and how packaging tools seek to find the right abstractions. At the end of the talk Phil distils this information and presets best practices. There’s also some discussion of future trends and some ideas for aspiring open-source engineers.

GitOps for Machine Learning Projects

GitOps for Machine Learning Projects

Fri Mar 11, 2022, by Phil Winder, in MLOps, Software Engineering

Not so long ago, developers used clunky consoles to provision infrastructure and applications. It wasn’t long before someone realized it was better to automate such a process via scripts and APIs. But it wasn’t until Hashicorp showed that APIs were not enough. Their insight was to declare a canonical representation of the infrastructure. You can then reconcile this declaration against the live view of the infrastructure. In 2015-16 we helped WeaveWorks develop their cloud monitoring platform.

Machine Learning Presentation: Provenance and Lineage for Data, Pipelines, and Deployments

Machine Learning Presentation: Provenance and Lineage for Data, Pipelines, and Deployments

Wed Feb 16, 2022, by Phil Winder, in Machine Learning, Talk

Dr. Phil Winder shares experiences of Winder.AI’s machine learning consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on how provenance and lineage, typically thought of as a model deployment problem, can help make the development of machine learning models more repeatable, understandable, and robust. Discover the difference between lineage and provenance. Learn how to determine the “strength” of your lineage and how robust it is to failure.

Databricks vs Pachyderm - A Data Engineering Comparison

Databricks vs Pachyderm - A Data Engineering Comparison

Mon Feb 7, 2022, by Enrico Rotundo, Hajar Khizou, Phil Winder, in MLOps, White Paper

Winder.AI has conducted a study comparing the differences between Pachyderm and Databricks. Both vendors are prominent in the data and machine learning (ML) industries. But they offer different products targeting different use cases. Modern, production-ready requirements present major challenges where data is evolving, unstructured, and big. This white paper investigates the strengths and weaknesses in their respective propositions and how they deal with these challenges.

Reinforcement Learning Presentation: Cyber Security

Reinforcement Learning Presentation: Cyber Security

Wed Jan 19, 2022, by Phil Winder, in Reinforcement Learning, Talk

Dr. Phil Winder shares experiences of Winder.AI’s reinforcement learning consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on RL applications, looking at the use of RL in cyber security and discusses one interesting case study about how Winder.AI helped an internal security team develop a tool to hack web application firewalls. About This Series Welcome to Winder.AI talks. A series of free interactive webinars hosted by Dr Phil Winder, CEO of Winder.

MLOps Presentation: How to Build Resilient AI With GitOps

MLOps Presentation: How to Build Resilient AI With GitOps

Wed Jan 12, 2022, by Phil Winder, in MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s MLOps consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on how GitOps is a key ingredient in any ML platform to enhance resiliency and observability. Learn why it is important, what it involves, and how to implement it in this short 30 minute video. About This Series Welcome to Winder.AI talks. A series of free interactive webinars hosted by Dr Phil Winder, CEO of Winder.