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  Curiosity, Courage and a Life at Sea: Exploring the World while building an Engineering career

  When I spoke with Leroy Osbourne FIET, CEng, MSc , for our 'My Engineering Career' blog series, I expected to hear about warships, sonar systems and a successful engineering career spanning the Royal Navy and industry. What I didn't expect was a story full of curiosity, adventure, resilience and lifelong learning. From a young boy fascinated by electricity and aeroplanes to a Chartered Engineer, IET Fellow and engineering leader, Leroy's journey demonstrates that there is no single route into engineering. In fact, some of the most rewarding careers begin with simply asking questions and refusing to stop learning. "I just wanted to know how things worked" For Leroy, engineering wasn't a carefully planned career choice. It was the natural outcome of a childhood spent being curious. Growing…

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  Engineering the Adaptive Workspace: From Asset Maintenance to System Strategy

  Managing change in modern engineering requires a radical shift in how we look at infrastructure . For generations, the focus has been on maintaining physical buildings. Today, the true challenge lies at the intersection of workplace strategy, data-driven insights, and human centric design. As the former Head of Research and Insight at the Institute of Workplace and Facilities Management (IWFM) and now working at the Institution of Engineering and Technology (IET) within our Local Networks, I have spent my career tracking how disruption shapes industry. The biggest disruption we face today is not a specific technology, but a fundamental change in the purpose of our workspaces. The Evolution of the Workplace The traditional office environment is no longer just a physical structure where…

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  Exploration vs Exploitation

  Reinforcement Learning (RL) is the branch of machine learning where an 'agent' (the actor, in an environment) learns by trying an action, observing the result, and adjusting its behaviour accordingly to achieve its goal. It is not unlike teaching a dog a new trick: the dog hears a command, tries something, and a treat either arrives or it does not, and over enough repetitions the dog works out which action gets the reward. This creates a hard engineering problem, because the agent has to decide how much to stick with actions that are already working versus how much to keep testing other options. This is a concept known as the 'exploration-exploitation trade-off'. Understandably, when you don't know what you don't know, it's tricky knowing how well you're doing and if you should change tactics…

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