Deep learning researchers have been predicting for a while that the technology will make various professions obsolete and that self-driving cars are imminent. We’re still waiting. Some have even claimed that they are nearing artificial general intelligence, or AI capable of equalling or exceeding human performance at all tasks.Hype is nothing new to machine learning, but this wave seems different. Billions of dollars in funding have been allocated based on this hype, and it has led to a massive amount of public confusion (which motivated our book).Thanks for reading AI Snake Oil! Subscribe to get new posts and help us develop our ideas.Obviously, there are self-serving reasons for any field to hype itself. But that doesn’t explain all of it, and many deep learning people genuinely believe their overconfident predictions. We think there are a few cultural and historical reasons for this. We hope that understanding those reasons will help you resist the hype and push back the next time you meet a true believer of deep learning — while still acknowledging that it works well in a limited set of domains and tasks.The dogma that all problems are the sameEvery scientific field has a central dogma: a core belief that binds the group together and gives it its identity. The central dogma of deep learning is that the only thing you need in order to solve a new type of learning problem is to collect training examples (such as images and their corresponding descriptions). The thinking is that you…Why are deep learning technologists so overconfident?