ML, RL, and MLOps Use-Cases and Examples

ML, RL, and MLOps use-cases and examples. Discover AI in your domain.

Automating Cyber-Security with Reinforcement Learning

May 2021

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.

The Future of Transportation Infrastructure: Reinforcement Learning

Mar 2021

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.

Solving Three Common Manufacturing Problems with Reinforcement Learning

Feb 2021

Like many industries, manufacturing is experiencing an explosion in both the growth of and access to data. The data is complex and multi-faceted, for example the data may originate from the production line, the environment, through usage, or even from users. When viewed in this light, the explosion is often called “big data” and the effect called smart manufacturing (USA) or industrie 4.0 (Germany). The data must be acted upon to be useful.

Inventory Control and Supply Chain Optimization with Reinforcement Learning

Feb 2021

Inventory control is the problem of attempting to optimize product or stock levels given the unique constraints and requirements of a business. It is an important problem because every goods-based business has to spend resources on maintaining stock levels so that they can deliver products that customers want. Every improvement to inventory control has a direct improvement the delivery of the business. Beginners study tactics, experts study logistics, so they say.