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In options trading, the Greeks are a set of risk measures—represented by Greek letters—that tell you exactly how an option’s price will react to changes in the market. Think of them as the dashboard of a car. They tell you your speed, your acceleration, how much fuel you have left, and what the weather is doing outside. Delta ($\Delta$): The Speedometer What it measures: Price sensitivity. The Question it Answers: “If the stock price moves $1, how much does my option price move?” ...

For the last five years, the recipe for AI progress has been remarkably simple: take a neural network, add more data, add more compute, and watch the intelligence line go up. This was the Age of Scaling. It was an era of industrial certainty, where companies could pour billions into hardware with the confidence of a guaranteed return. But according to Ilya Sutskever, that era is drawing to a close. ...

The entertainment world froze on Friday. In a move that redefines the concept of a “blockbuster,” Netflix has announced a definitive agreement to acquire Warner Bros. Discovery (WBD). This isn’t just a merger; it is the end of the Streaming Wars as we knew them and the beginning of a new, monopolistic era in Hollywood. If you are trying to make sense of the headlines, here is the deep dive into what is actually happening, why it matters, and why this deal is far from a done deal. ...

A reviewer, tasked with evaluating a technical submission for NeurIPS 2025—the most prestigious AI conference in the world—left a comment that will go down in infamy: “Who is Adam?” For the uninitiated, asking “Who is Adam?” in a Deep Learning paper is akin to a mechanic asking “What is a wheel?” or a chef asking “What is salt?” Adam (Adaptive Moment Estimation) is arguably the most popular optimization algorithm in modern deep learning. It has been the default optimizer for nearly a decade. It is not a person the authors forgot to cite. It is not an obscure character in the paper’s narrative. It is the math that makes the models learn. ...

In the high-stakes world of top-tier AI conferences like ICLR (International Conference on Learning Representations), getting a paper accepted is a career-defining moment. Authors spend months optimizing algorithms, ablation studies, and prose. They expect rigor. They expect tough questions. They do not expect 40 weaknesses and 40 questions from a single reviewer. A recent incident involving an ICLR 2026 submission has set the Machine Learning community on fire, highlighting a growing crisis in academic peer review: the suspicion that AI is now reviewing AI, and doing a terrible job of it. ...