AI, Machine Learning, Reinforcement Learning, and MLOps Articles

MLOps Presentation: How to Build Resilient AI With GitOps

Published

Jan 12, 2022

Author

Dr. Phil Winder

CEO

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.AI, Author of O’Reilly’s Reinforcement Learning and one of the founders of the MLOps Community, covering a range of topics about the use of machine learning operations (MLOps), reinforcement learning (RL), and machine learning (ML) in industry today.

The Value of a Machine Learning Pipeline: Past, Present, and the Future of MLOps With Kubeflow

Published

Nov 1, 2021

Author

Dr. Phil Winder

CEO

Industrial machine learning consulting and MLOps platform projects come in a variety of forms.

Sometimes clients ask for exploratory data analysis, to evaluate whether their data can be used to help solve a problem using artificial intelligence. Other times we use machine learning (ML) algorithms to automate decisions and improve efficiencies within a business or product. More recently we’ve refocused on reinforcement learning and customers ask us to help control some complex multi-step process.

Using Reinforcement Learning to Attack Web Application Firewalls

Published

Sep 3, 2021

Author

Dr. Phil Winder

CEO

Introduction

Ideally, the best way to improve the security of any system is to detect all vulnerabilities and patch them. Unfortunately this is rarely possible due to the extreme complexity of modern systems. One primary threat are payloads arriving from the public internet, with the attacker using them to discover and exploit vulnerabilities. For this reason, web application firewalls (WAF) are introduced to detect suspicious behaviour. These are often rules based and when they detect nefarious activities they significantly reduce the overall damage.

Helping Modzy Build an ML Platform

Published

Aug 25, 2021

Author

Dr. Phil Winder

CEO

Winder.AI collaborated with the Modzy development team and MLOps Consulting to deliver a variety of solutions that make up the Modzy product, a ModelOps and MLOps platform. A summary of this work includes:

• Developing the Open Model Interface
• Open-sourcing chassis, the missing link that allows data scientists to build robust ML containers
• Model monitoring and observability product features
• MLOps and model management product features

How To Build a Robust ML Workflow With Pachyderm and Seldon

Published

Jul 27, 2021

Author

Enrico Rotundo

Associate Data Scientist

This article outlines the technical design behind the Pachyderm-Seldon Deploy integration available on GitHub and is intended to highlight the salient features of the demo. For an in depth overview watch the accompanying video on YouTube.

Introduction

Pachyderm and Seldon run on top of Kubernetes, a scalable orchestration system; here I explain their installation process, then I use an example use case to illustrate how to operate a release, rollback, fix, re-release cycle in a live ML deployment. Throughout the demo, I showcase how Pachyderm comes in handy with data lineage and automation in a critical scenario.

How We Built an MLOps Platform Into Grafana

Published

Jun 11, 2021

Author

Dr. Phil Winder

CEO

Winder.AI collaborated with Grafana Labs to help them build a Machine Learning (ML) capability into Grafana Cloud. A summary of this work includes:

• Product consultancy and positioning - delivering the best product and experience
• Design and architecture of MLOps backend - highly scalable - capable of running training jobs for thousands of customers
• Tight integration with Grafana - low integration costs - easy product enablement

Grafana’s Need - Machine Learning Consultancy and Development

Grafana Cloud is a successful cloud-native monitoring solution developed by Grafana Labs.

Automating Cyber-Security with Reinforcement Learning

Published

May 5, 2021

Author

Dr. Phil Winder

CEO

The best way to improve the security of any system is to detect all vulnerabilities and patch them. Unfortunately this is rarely possible due to the extreme complexity of modern systems.

The common suggestion is to test for security, often leveraging the expertise of security-focussed engineers or automated scripts. But there are two fundamental issues with this approach: 1) security engineers do not scale, and 2) scripts are unlikely to cover all security concerns to begin with, let alone deal with new threats or increased attack surfaces.

CloudNativeX Interview: Reinforcement Learning

Published

Apr 5, 2021

Author

Join Lee Razo and Phil Winder for this comprehensive introduction to Reinforcement Learning, an area of machine learning in which problems are tackled with intelligent agents which take actions to maximize a specified reward.

Phil (quite literally) wrote the book on this topic and he takes us through the fundamentals of RL, some common use cases as well as tips on how even a small or mid-sized company can get started with and benefit from RL.

The Future of Transportation Infrastructure: Reinforcement Learning

Published

Mar 17, 2021

Author

Dr. Phil Winder

CEO

The lock-downs endured during the coronavirus pandemic have given many the opportunity to work from home, potentially for the first time. Along with the guilt of failing at home-schooling, trying to work with noisy babies or animals, the lock-down has entirely changed the way in which we travel.

When I speak to people about the pandemic, the lack of commute is one of the few positives they can take away from this experience and has led some to even question why they are paying for accommodation in some of the most expensive areas in the UK.

InfoQ Podcast: Phil Winder on the History, Practical Application, and Ethics of Reinforcement Learning

Published

Mar 1, 2021

Author

Charles Humble, friend and editor of InfoQ, was kind enough to ask me for an interview to talk more about my new book, in podcast format. From the blurb: