Machine learning models possess a fundamental limitation that often frustrates newcomers to natural language processing (NLP): they cannot read.

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Large language models (LLMs) like ChatGPT can write an essay or plan a menu almost instantly. But until recently, it was also easy to stump them. The models, which rely on language patterns to respond to users’ queries, often failed at math problems and were not good at complex reasoning. Suddenly, however, they’ve gotten a lot better at these things. A new generation of LLMs known as reasoning models are being trained to solve complex problems. Like humans, […]

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Ernest Opoku knew he wanted to become a scientist when he was a little boy. But his school in Dadease, a small town in Ghana, offered no elective science courses — so Opoku created one for himself. Even though they had neither a dedicated science classroom nor a lab, Opoku convinced his principal to bring in someone to teach him and five other friends he had convinced to join him. With just a chalkboard and some imagination, they […]

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This is ChatGPT’s first year as the No. 1 app on the U.S. App Store by downloads.

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Ridge and Lasso regression are often perceived as more complex versions of linear regression. In reality, the prediction model remains exactly the same. What changes is the training objective. By adding a penalty on the coefficients, regularization forces the model to choose more stable solutions, especially when features are correlated. Implementing Ridge and Lasso step by step in Excel makes this idea explicit: regularization does not add complexity, it adds preference. The post The Machine Learning “Advent Calendar” […]

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