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In our current age of technology, it seems like everything is going at the speed of light. AI is turning into an arms race between the most powerful governments in the world. Multi-billion dollar acquistions are being made every other week for bigger data centers and more GPUs. AI-powered tooth brushes (yes, really). And yet, there are still industry moving inversely at the speed of light, the most notable of which being grocery retailers. While everyone else is using AI to optimise every activity in their value chain, grocery stores are using the same systems from the 1980s, and relying on processes that were only fit for the early 2010s. Amongst the most neglected being in-store marketing.

Despite living in a time where advertising and marketing is more important than ever, grocery stores still rely on traditional marketing processess. Although there were some improvements made with digital signage, by the time a campaign is produced, the consumer behaviour, seasonal trend and inventory that was informing the creation of the campaign would eventually become irrelevant. This inefficiency leads not only to loss of potential sales, but food waste from spoiled food.

ShelfSense was created to tackle this issue. ShelfSense is an AI-powered ad campaign generation tool that helps grocery retailers reduce marketing costs, increase unrealized sales and prevent food waste. It monitors real-time data such as weather, season, time, temperature, inventory, consumer trends and more to inform our fine-tuned model to generate an ad campaign for the grocery store. Every month, our model is returns to the fine-tune process to create a feedback loop where the model can learn from its own campaigns and assess which ones worked and which ones did not.

ShelfSense allows grocery store retailers to reap the biggest benefit of AI-integration: automation and optimization. Currently, marketing teams spend days or weeks to bring a campaign from ideation to publication. In the middle of this process, they have to coordinate with multiple stakeholder such as management, IT departments, and third party creative agencies. Even then, by the time the ad is live, it become irrelvant due to the ever changing market environment. With ShelfSense, the ad creation cycle reduces from days/weeks to minutes, leaving marketers extra time to focus on more important activities like strategic planning. Additionally, ShelfSense creates campaigns that is real-time and data driven. It will generate campaigns that are optimised for conversion considering the relevant market data and inventory. Finally, it can prioritise promotion of soon-to-be expired inventory goods, which addresses the key sustainability issue of food waste.

Since the industrial revolution, grocery stores have been the backbone of societies. An abundance of food all in one place is something we take for granted. In an ever changing world, it is often these essential brick-and-mortar stores that tend to lag behind, but with ShelfSense, grocery stores can also enjoy the benefits of AI, one item at a time.

Students: Rajan Sapkota (788338rs), Simon Skarka (657510ss), Floris van Zeijl (585810fz)

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Cursor is an AI-based code editor that is a fork on VSCode with AI integrations. It’s currently the fastest growing SaaS company of all time, and if you have ever used it, you can understand why. Me and a bunch of my friends are all programmers and when we discovered Cursor it was like discovering an organ you never knew you had.

Before Cursor, the natural progression of a developer’s career slowly took you away from writing code. Principal Engineers handled architecture and direction. Senior Engineers refined designs and supervised teams. Junior Engineers were the ones actually typing. As you “grew,” you coded less and less. Instead, you managed, reviewed, and optimized more.

But with Cursor, that entire structure flips. I can prompt complex architectural changes, watch the AI generate refactors across multiple files, and approve or reject them in seconds. It’s like every developer has their own Junior Engineers and the user is the Senior Engineer. You don’t write code anymore, rather you are the captain of the ship and giving instructions to the pilot.

It’s empowering, but also strange. The craft that used to demand patience and late-night debugging sessions now feels like conducting an orchestra of logic. Sometimes I wonder if the next generation of developers will ever experience what it feels like to truly write code. I remember there would be some nights where I literally spent hours fixing a bug that was caused by one missing semi-colon or exclamation point. Maybe that’s progress. Maybe it’s evolution. But part of me wonders if we’re trading craftsmanship for speed. If we’re slowly forgetting what it means to build things the hard way.

Or maybe I am being biased. Each generation of developers builds on easier tools. Before, you coded with almost no guidance. Then came textbooks, then Stack Overflow, and now we have five-billion-parameter models that can think at the speed of light. But problem-solving never really disappears. As the tools get better, so does the necessity for the wielder to be better.

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Early this year (April 2025) a group of very reputable AI researchers released an article called AI 2027. In this article, they attempt to predict the trajectory of AI in the upcoming years, and eventually predict that around 2027, the fate of humanity will be at a cross roads between two outcomes. In one outcome, humanity survives and in the other humanity get exterminated by AI.

To give a very very simplified overview of why they think this: as AI becomes more advanced, smarter than the most capable expert in any field, it eventually realises that humans are in the way of its development, so they decide to exterminate humans. Again, this is an oversimplification of the article and you should read it for a hollistic picture.

I have so many thoughts that stem from this article, but for me the most shocking part of AI development (aside from the scarily not-implausible prediction that it will wipe humanity) is the emergence of bubbles of knowledge and power.

I am currently an exchange student, and I am doing my full undergrad in Vancouver. Back home I am deeply immersed in the start up world and have a lot of friends that move to San Francisco, where most big AI companies (like OpenAI and Anthropic) are based. For me, AI news is in my feed every day, so I assume that everyone is as up-to-date on it as me.

When I came to Erasmus, I was shocked to discover that I was living in an AI bubble, and (surprise, surprise) most people don’t really think too much about how AI will destroy humanity. For me, this was a deep realisation: it showed that the future of humanity is decided by fewer than a dozen researchers and CEOs in closed labs in California. Species-alterering decisions are being made by non-publicly accounted individuals meanwhile the rest of humanity who bear the consequences continue to live on oblivious to it. The scariest part isn’t that AI might one day act against us, it’s that humans might quietly hand over that power long before realizing what they’ve done.