Basics Theory
Ten Uncomfortable Ideas That Challenge Common AI Assumptions
Explore 10 uncomfortable ideas that challenge common AI assumptions in health apps: data myths, fluent chatbots, feedback loops, bias, alignment and accountability.
Tessa Rodriguez
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User Needs Should Guide Which AI Features Companies Build
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Technology Hype Can Make Generative AI Progress Harder to Evaluate Clearly
Learn how generative AI hype distorts progress claims—and how to evaluate models using reliability, benchmarks vs. real work, edge cases, and true costs.
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The AI Industry Bubble Shapes How Technology Is Discussed
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High User Expectations Can Expose the Limits of Generative AI Products
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Start With Practical AI Skills for Learning, Work, and Building
Learn practical AI skills: prompt with context, verify outputs, and build simple workflows to study faster, write better, run meetings, and avoid privacy traps.
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Competition Between AI Platforms Can Accelerate New Model Development
How AI platform rivalry accelerates new model development through tooling, telemetry, infrastructure, and ecosystem pull—while increasing lock-in, safety, and fragmentation risks.
Basics Theory
Ten Uncomfortable Ideas That Challenge Common AI Assumptions
Explore 10 uncomfortable ideas that challenge common AI assumptions in health apps: data myths, fluent chatbots, feedback loops, bias, alignment and accountability.
Impact
AI Literacy Matters More Than Knowing Every New AI Tool
AI literacy beats chasing every new AI tool: learn prompts, evaluation, and judgment, plus privacy/IP limits, to use AI reliably at work.
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AI Assistants and Robotics Are Bringing Language Models Into Physical Tasks
Learn how language models power robotics: turning intent into plans, using tools/APIs safely, improving reliability, evaluation, and real-world deployment.
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Leading AI Models Can Reach Similar Performance in Different Ways
Learn why top AI models can score similarly on benchmarks yet differ in data, architecture, alignment, latency, cost, and reliability—and how to choose the right one.
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AI Copyright Questions Extend From Training Data to Generated Content
Explore AI copyright questions from training data to AI-generated content: what counts as copying, output similarity, ownership, and practical risk checks.
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Sensitive Questions Require More Than a Simple Chatbot Answer
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