Learn to Think in Color

Why Does AI Video Get Boring So Fast? The spectacle wins the glance. Story earns the stay. Generative AI can now produce images that would have seemed extraordinary only a short time ago. A medieval astronaut can wander through a glowing forest, a modern sitcom can become a gothic horror film, and entire imaginary cities can appear in seconds. The strange part is how quickly the fascination can disappear. A video can look spectacular and still feel boring after ten or fifteen seconds. That does not necessarily mean our attention spans are failing. It may mean the brain has already understood the most interesting thing the video had to offer. At First, We Are Watching the AI When we watch ordinary film, we usually pay attention to the people, the situation, or the story. AI video often creates an additional layer. We inspect the output. Does the face stay consistent? Are the hands correct? Does the movement look natural? Is the lighting convincing? Could AI really create this? ...

How Are Network Effects Impacted by Generative AI? When your flywheel meets a stochastic parrot with superpowers Big-picture framing Generative AI is reshaping  network effects and generative AI dynamics  at every layer: data, users, and products. In classic platforms, more users mean more value for each user; now, more users also mean more data, faster learning, and better models. The core question shifts from “How big is our network?” to “How quickly can we compound learning from our network?” Instead of replacing network effects, AI  bends and intensifies  them. It can turn weak flywheels into strong ones, transform single-sided products into ecosystems, and in some cases even erode old moats by lowering switching costs. If you build, invest in, or compete with AI products, understanding these new loops is now part of the job. Network effects 101 (in one minute) Classic  network effects : The product gets more valuable as more people use it. Each new user add...