Chatgpt

– Source: Julian Zwengel on Unsplash. One of the (few) reasons to switch to macOS 26 Tahoe is the opportunity to use the language model that powers Apple Intelligence. Apple Intelligence is the final product, natively integrated into the Apple ecosystem, with which we can process text (but also images) directly on our device. For example, by selecting a section of text and right-clicking with the mouse to choose Show Writing Tools, we have at our fingertips a useful tool for summarising those mile-long documents or for rewriting hastily jotted-down sentences.

The conclusions of the post on Phi-4 left me stunned. How was it possible that a model like Phi-4 Reasoning Plus, which boasts an impressive 14.7 billion 4-bit parameters and was trained on scientific problems, particularly in mathematics, could have failed so badly? Comparing LLMs The question I asked Phi-4 Reasoning Plus was basic logic, a fourth-grade student could (and should) have answered it in 10 seconds. ChatGPT had no trouble at all and reasoned exactly as one would expect from the poor student.1

As some of you may already know, I use LLMs (Large Language Models) for what they’re really good at, but I’m pretty skeptical about whether they’re truly intelligent or can solve any problem, as the folks at OpenAI, Microsoft, Google, and Meta keep telling us every day. They’ve invested a ton of money in LLMs, and they obviously have a big stake in getting everyone to use them all the time.

– Image generated by the Microsoft Designer AI. Eleven years ago, when I started writing in this personal space, I never imagined I would stick with WordPress.com for so long. WordPress.com is a convenient and reliable blogging platform, but it has always been ill-suited to my way of working. Over time, I learned to live with these limitations, but the idea of changing platforms never left my mind.