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When people talk about artificial intelligence (AI) today, the conversation often drifts into mystique. We hear phrases like 'thinking machines' or 'AI replacing humans,' as if a spark of magic has suddenly entered our world. But history shows a different story: every wave of automation, whether industrial, digital, or now intelligent, has been shaped not by magic, but by clear thinking, human analysis and precise understanding of what needed to be achieved.

To see this, it helps to trace automation through three phases: achieve what I achieve, do what I do, and think what I think.

In the ever-evolving landscape of automation, the integration of bots across multiple systems has become a necessity for efficiency and productivity. However, as this technology progresses, a critical challenge has emerged as well. It's become increasingly difficult to balance the benefits of formatted and structured information for human use while also working towards the reduction of semantic resolution.

Ah, the age-old debate of working from home versus working in the office. It's like choosing between sweatpants and business casual, between Zoom meetings and water cooler banter. Now that the dust has settled on the post-COVID working landscape, let's take a lighthearted look at the differences between these two worlds. Yes, it’s another ‘post covid reflection’. You’ve heard loads, I know.

Welcome, dear reader, to the fascinating world of Robotic Process Automation (RPA), where bots and humans join forces to streamline business processes. While the term "automation" might conjure images of futuristic robots taking over the world, the reality is a bit more down-to-earth – and requires a stellar team of tech-savvy individuals.

I've recently had the opportunity to reflect upon our annual staff appraisal process, specifically around the quality of feedback. One frequent observation is that reviews and comments often lack details, making appraisals challenging. It is especially true for managers who don't work closely with the appraisee and rely entirely on their colleagues' feedback to assess their progress. To address this issue, my colleague and I were asked to revisit the process and suggest what could be improved.

A few weeks back, I decided to get involved in Java Challenge UK, by sitting on the competition’s jury panel. A bit of context: the Java Challenge is a gamified competition, with one league for professionals and one for students, that consists of multiple-choice questions. As part of the “jury duty”, I had the task of writing one of these questions. I decided to write my question around lambdas; read on to find out a little bit about why...