Thoughts from My Head
When you work for a long time with artificial neural networks, you begin to see patterns emerge. One of these touches on fundamental aspects of intelligence. As I haven't seen it described very often, I'll set it out here.
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This post continues my explorations of simple intelligence. In this post, we'll consider some elementary sensing cells. We'll then look at whether we can apply local function approximators. Sensors Consider a set of sensing cells, which we'll call "sensors". We have N sensors, where each sensor measures a value over time. This value could be … Continue reading Swift Taylor Approximations
This post looks at composition. It starts with Lego. It then looks at a theory of why deep neural networks work and how they could be trained. It ends on how brains may embody these theories.
Ever since "On Intelligence", I've been a Jeff Hawkins fanboy. It takes a lot of guts to invest all your wealth into understanding the brain. But what are his recent theories?
The rise of machine learning and developments in neuroscience hint that prediction is key to how brains navigate the world. But how could this work in practice?
Robotic Ape 