The AI Edutainment Website opens up for guests—researchers, practitioners, educators, and AI enthusiasts—to contribute through interactive storytelling, guest blog posts, podcasts, and expert Q&A sessions.
In September, we feature an article by Silvio Gerlach, a Berlin-based economist. He will discuss the never-ending lottery of implementing AI projects in incumbent businesses. To accompany this post, we will share the MIT paper Silvio is referring to, along with his own comprehensive analysis on how to measure the traction of AI projects in businesses.
Additionally, we will discuss in one of our future blogs one of the most iconic papers showcasing a beautiful partnership between AI and neuroscience: “A Neural Substrate of Prediction and Reward,” written in 1997 by Schultz, Dayan, and Montague. Mentioning this work enables us to explain how reinforcement learning operates in brains versus machines.
Our September and October are entirely dedicated to the evolution of brains – alongside the history of AI and robotics. You will understand that the most studied worm on the planet and the Roomba vacuum cleaner share an algorithm. Furthermore, reinforcing the behaviour of chickens is much easier than implementing the exact mechanism in artificial neural networks, and some AI challenges have taken decades to solve. Ultimately, you will encounter something that remains true and valid in AIs. All today’s AIs are frozen in state after their models were trained and released.
When you follow our newsletter and regularly read our posts, you will be able to explain the ‘why’ behind such a vulnerability and limitation – and thereby cut through the fluffy nonsense of some consultants and vendors, trying to seduce you and your company with their tales of overwhelmingly powerful and unfailing technologies.