Discover how reinforcement learning is changing the way organizations do AI – with one of the world leaders, Winder.AI.
I could always count on Winder.AI to drive their responsibilities forward with only limited oversight—they knew what our goals were and how to achieve them. They also had a very high bar for quality. Everything they touched delivered an impressive result.
Our next-generation RL services bring automated strategies to your business.
RL Development We’re authors of the book on applying industrial reinforcement learning. Our RL engineers stand ready to develop your projects, e.g. a global aviation company.
RL Consulting Make the right decisions at the right time. Winder.AI’s reinforcement learning guidance can help you plan and design solutions to a variety of problems, e.g. a finance company.
RL POCs De-risk production RL projects with rapid proof of concept projects, e.g. Nestlé.
Simulation Development Simulators enable us to rapidly develop and evaluate RL agents irrespective of the methodology.
Deep RL Development Deep reinforcement learning generates the most advanced RL algorithms.
We've worked with hundreds of amazing people, all over the world.
Enterprise-ready Reinforcement Learning solutions.
Unlike larger, more general purpose IT agencies, we specialize in developing AI solutions. We’re more flexible, more pragmatic and better suited to integrate AI into your product.
We combine our bespoke AI solutions with cloud-agnostic or on-premise software engineering to produce production-ready large language models.
We exist to help companies like yours build better products. We collaborate closely with your internal engineering teams to both upskill and deliver pragmatic results.
Winder.AI is a flexible, decentralized, independent AI company that can deliver full-stack solutions. Reinforcement learning creates intelligent agents for automated strategies.
Reinforcement learning provides techniques and algorithms for reactive agents. Optimize for the long term.
With RL, you’re able to optimize for the thing you really care about, not a proxy metric, like accuracy.
RL excels at automating multi-step processes, far better than any machine learning solution.
RL provides better strategies for coping with adverse or anomalous conditions.
A free chapter from the book, Reinforcement Learning, by Winder.AI.
We are delighted to offer you a complimentary chapter written by our company CEO, Dr. Phil Winder.
The free chapter will enable you to learn about:
You can find out more on the dedicated RL book website.
Fill in the form and we will send a free chapter on Practical Reinforcement Learning directly to your inbox, free of charge. Please remember to check spam and junk folders if nothing arrives.
What if you would like to learn more about RL, or AI as a whole?
As a leader, you wear many ‘hats’ and, like every organization, no matter its size, it has constant challenges around sorting, cleaning and enhancing data. We listen to leaders’ needs and aspirations for their organizations.
We can offer insights and support, no matter the age or size of your organization. We uniquely work with all sectors.
Dr. Phil Winder will personally aim to reach back over the coming days to answer any follow-up questions you may have.
Case study
Our financial client is based in the UK. They specialise in providing services to the finance industry. Their data science team embarked on a project to leverage reinforcement learning within their product offering. Winder.AI, world-leading authors and experts on reinforcement learning, helped them deliver their POC into production. Read on to find out more.
Case study
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.
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.
Case study
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.
Reinforcement Learning
This is a video of a workshop about deep reinforcement learning (DRL). First presented at ODSC London in 2023, it is nearly three hours long and covers a wide variety of topics. Split into three sections, the video introduces DRL and RL applications, explains how to develop an RL project, and walks you through two RL example notebooks.
Reinforcement Learning
Dr. Phil Winder shares experiences of Winder.AI’s reinforcement learning consulting experience at a variety of large and small organizations.
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.
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.
Reinforcement Learning
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.
This page provides answers to our most common questions. If you have a query that isn't covered, please get in touch.
As we describe in our book, reinforcement learning (RL) is a sub-discipline of machine learning (ML) that specializes in teaching machines to execute multi-step, strategic decisions. Traditional ML automates single decisions, but they don’t leverage any context, nor do they operate over sequences. For example, a traditional recommendations algorithm will suggest a specific set of products and the algorithms are optimized to improve that recommendation. But this is the wrong objective. You don’t want to optimize for single placements. You should be optimizing for increased engagement or higher profitability per customer, or whatever your business prioritizes. RL allows you to train your models to do exactly that – optimize decisions towards your organization’s unique goals.
Strategic decisions tend to be the most lucrative choices a business can make and they are typically the most expensive. Reinforcement learning is a technique that we pair with AI consulting to automate strategic decisions.
The key premise in reinforcement learning is the concept of an environment and a policy. The environment represents the space that the agent will operate within, with all the signals and data it can observe. The policy represents the internal decision model of the agent, which is responsible for choosing what to do within the environment. Over time, the agent learns to update it’s internal model of the world to make better decisions.
The team at Winder.AI are ready to collaborate with you on your rl development project. We tailor our AI solutions to meet your unique needs, allowing you to focus on achieving your strategic objectives. Fill out the form below to get started.
