Chat as my one-window kitchen assistant

6

October

2025

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First, when I started using Generative AI, I mainly used it to search for recipes or explain cooking techniques. But over time, I discovered another use that changed my weeknights. I opened a dedicated cooking-only chat and treated it like a kitchen assistant. This single-purpose setup made a big difference in how I plan meals and reduce waste.

The part I struggled with most was not knowing what to cook after work. I often felt overwhelmed by choices and half-used ingredients. Here, the chat helped the most. I would paste what I had at home, including rough amounts and expiry dates, and ask for options. It broke things down into clear recipes, gave prep time estimates, and prioritized items that were about to expire. The suggestions were practical and matched my skill level.

I could personalize it as much as I wanted. I shared time limits for weekdays, basic dietary preferences, and pantry staples I always have. The tool then proposed dishes that fit those constraints and adjusted portions for the number of people. It also tracked a simple inventory. If I marked spinach as expiring on the 7th, it nudged me to use it first. That alone cut my food waste.

Of course, not everything was perfect. Sometimes the plan was too optimistic, asking for more prep or specialty spices than I had. When that happened, I trimmed the steps or swapped ingredients with its help. If I forgot to update the inventory, suggestions drifted. That is on me.

In addition, the chat was useful while cooking. It summarized steps into short instructions, highlighted times and temperatures, and offered quick fixes when I messed up a sauce or overcooked rice.

Overall, the cooking-only chat gave me a clear starting point every evening. It turned a messy fridge into a plan, made shopping lists realistic, and kept dinner stress low. This clarity made cooking feel manageable and even enjoyable.

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Chips Meet Code: Why ASML’s Stake in Mistral AI Signals a Strategic Shift for Europe

15

September

2025

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Earlier this month, ASML, the Dutch titan of advanced chipmaking equipment, announced a bold €1.3 billion investment in Mistral AI, a French startup making waves with its open-weight large language models. With this move, ASML didn’t just cut a cheque. It secured an 11 percent stake and a seat at Mistral’s strategic table. CFO Roger Dassen will represent ASML, which shows that this is more than a financial play. It is a strategic bet on Europe’s AI future.

From a technical point of view, this partnership feels like a no-brainer. ASML’s lithography machines are some of the most advanced pieces of technology on the planet, and they operate at levels of precision that are almost hard to imagine. Training AI models on the massive amounts of data these machines generate could make them even better by improving calibration, speeding up production steps, and predicting when parts need maintenance before they fail (ASML, 2025).

In the chip industry, where a few milliseconds of downtime can cost millions and a single nanometer of progress can mean a huge competitive edge, these kinds of gains are not just nice to have. They are essential. This partnership is ASML’s way of making sure it stays at the very top in an industry that is getting more competitive by the day.

But this is about more than just engineering and R&D. There is a clear geopolitical angle too. Europe has been playing catch-up with the United States and China when it comes to AI. By backing Mistral, ASML is helping to grow a European AI player and is taking an active role in strengthening the region’s tech ecosystem. This move fits with the EU’s push for digital sovereignty, where both governments and companies are trying to keep control over critical technologies instead of relying on foreign providers.

That said, the road ahead is not guaranteed. Mistral is still a young company, and bringing its software into ASML’s very hardware-focused world will be a real challenge. There is also the culture gap to consider. Startups move fast and break things, while semiconductor companies are built around stability and risk control. Whether those two mindsets can actually work together is something we will only find out over time.

As a student of Information Strategy, I find this a fascinating real-world case of digital disruption and of how deep tech is merging with data-driven intelligence. It also makes me wonder about Europe’s AI ambitions. Should companies like ASML, who lead in hardware, be the ones shaping Europe’s AI future? Or should that role be left to software-first innovators who can move faster?

In my view, this move is a step in the right direction. Rather than waiting to adopt AI solutions from abroad, ASML is helping to build them at home. The company is not just a buyer of innovation. It is becoming a co-creator. This approach gives Europe a stronger position in shaping its digital future.

Whether this partnership results in groundbreaking innovation or ends up as a case study in misalignment will depend entirely on execution.

References
ASML. (2025, September 9). ASML and Mistral AI enter strategic partnership. https://www.asml.com/en/news/press-releases/2025/asml-mistral-ai-enter-strategic-partnership
Reuters. (2025, September 9). ASML takes 11% stake in Mistral AI. https://www.reuters.com/technology/asml-becomes-biggest-mistral-investor-boost-europes-ai-ambitions-2025-09-09/

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