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A new study reveals leading AI models, including Gemini 3.0 Pro and GPT-5, have crushed the rigorous CFA exams. Gemini 3.0 Pro hit a record 97.6% on Level I, a massive leap from just two years ago when models failed. This breakthrough signals a major shift for finance professionals and educators: technical knowledge is no longer a moat. The future belongs to human skills like judgment and ethics. Dive into the data and take the quiz to see how you stack up against the machine

When AI reads the word "it," it essentially asks the rest of the sentence: "Who am I?" 🧠 In this visual breakdown of the Attention Mechanism, we reveal the hidden math behind context. Watch as the Query searches for Keys, glowing pink lines map Attention Weights, and meaning flows to update the Value. See how a generic pronoun transforms into a specific concept: "It (Tired Animal)."

How educators can move beyond policing AI to designing assessments that promote authentic learning On September, 2025, Jobs and Skills Australia (JSA) released a interesting report on generative AI transition . It found that AI is already automating key entry-level tasks in fields like law, health, and creative industries—the very tasks we've traditionally used to build foundational skills in our graduates. This creates a critical gap. How do we assess competence when we can

If you've been paying attention to technology over the past two years, you've witnessed an explosion of AI tools that has fundamentally changed how we work, create, and learn. From ChatGPT to Midjourney, Grammarly to GitHub Copilot—the options are endless. But here's the problem: with 100+ specialized tools available, how do you know which ones to use? This comprehensive guide breaks down the entire AI tool landscape with an interactive hub, curated learning paths, and practi

Generative AI has entered education with remarkable speed. Yet alongside enthusiasm, educators face a critical challenge: understanding what these tools can actually do—and what they cannot. The six capabilities framework cuts through hype and grounds exploration in concrete input-output relationships. This taxonomy matters because it shifts conversation from "Is AI good or bad?" to "What specific problems can this capability solve in my teaching context?" When we understand

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