Blog Articles

At home, I live in a digital jungle. There are 8 Amazon Echo devices spread across the house, 12 smart bulbs that illuminate on command, 12 smart sockets that silently manage everything from the fish tank lights to festive decorations, a smart thermostat and 4 wireless temperature sensors monitoring room comfort, 3 Wi-Fi mesh nodes keeping everything connected, a smart fridge, a smart oven, 5 smart TVs, 2 smart car chargers and everyone in the house has a phone and laptop.

What the energy cost of Generative AI really means — and whether sustainability-minded institutions should use it anyway. As conversations around climate responsibility intensify, a growing concern has emerged in Higher Education (HE): should institutions committed to sustainability be using energy-hungry tools like Generative AI?

This week I crossed the finish line of the Manchester Marathon for the tenth time. Ten medals. Ten years. One slowly deteriorating finish time. I’d love to say I’m getting better with age, but the Strava data says otherwise.

I recently went through a fun thought experiment – ‘What if a serial killer approached their grim work like a computer scientist debugging a complex piece of code?’

Many of us, myself included, have at some point used AI writing tools to transform bullet points into polished text. It’s a practical way to express ideas clearly and professionally. However, this process reveals something deeper: written text is no longer just a medium for communication. Instead, it has become an intermediary layer - a way to translate ideas from sender to recipient.

As a kid growing up in the heyday of video games, I spent countless hours immersed in the digital worlds that were, at the time, the height of technology. The first game I ever completed from start to finish was Doom, the legendary first-person shooter from id Software. For me, Doom was a fun way to lose myself in a challenging game where the enemies where not human and it was set in a location far from reality – almost a 3D evolution of the classic space invaders. It was about getting deeply immersed in the gaming world and enjoying the thrill of conquering each level and defeating all the enemies that came my way.

Recently, I wrote a few words about Demis Hassabis, a computer scientist who won the Nobel Prize in Chemistry. With the upcoming release of a ZX Spectrum reproduction from Retro Games Ltd, I couldn’t help but reminisce about my early days in computing with a ZX Spectrum. As I sifted through the history of the ZX, I came across a photo of Demis with a ZX Spectrum—it turns out he started out on the same machine! Maybe there’s hope for me yet.

Ever wish you had more time in the day? Maybe to finish a project, catch up on a TV series, or even just sneak in a few extra minutes of sleep? If you’re like me, you’ve probably heard friends say, ‘If only I could slow down time, I’d get everything done!’ My go-to response? ‘Of course, it’s possible! All you need are really big magnets.’

Artificial Intelligence (AI) has quickly moved from science fiction to a part of our everyday lives. Tools like ChatGPT are at the forefront of this transformation, generating text, holding conversations, and answering questions with a fluency that seemed unimaginable not long ago. But how does it actually work? What’s happening under the hood when you type in a question?

I’ve stolen this idea from a friend, Apostolos. His perspective inspired me to explore how recent Nobel Prize wins by computer scientists demonstrate the profound impact of computer science on other fields, and as a computer scientist I am deeply proud of this news!