I never felt comfortable with the term AI. I used to call it Augmented Intelligence (for my students) and preferred the term ML to AI. That was before I heard this talk. Now there is no going back.
Prof Jordan was amazing. It is the kind of interview you can listen to sitting glued to your seat for 2 hours!
I was jotting things down mostly paraphrasing from Prof Jordan’s replies.
- What is happening today is not AI. It is an intellectual aspiration.
- Thinking that you can have AI at the level of human intelligence is like ancient Greeks thinking about traveling to the moon some day. It is a similar challenge because we (humans) don’t even understand intelligence.
- We have no clue how the brain does computation. We don’t even know what the signals in the brain are – it can be chemical, it can be electrical it can be ions or whatever. It is a problem (a fantastic one) for the next century.
- We are completely dim about how thought emerges from the brain.
- It will take us a couple of hundreds of years to get to human level intelligence.
- What we have is Machine Learning – systems that learn from data and help us make decisions.
- Right now we are good at imitating some aspects of human intelligence.
- True conversational AI is not going to happen in our life time.
- What goes for AI now is mostly Machine Learning
- What we have now is pattern recognition and some level of prediction.
- True prediction is not possible with just data sets. You need a lot of context and more.
- What we have now is a little bit of reasoning and it is not AI.
- Prediction is difficult because the world is highly stochastic and we have massive uncertainty.
- Gradients (as in Gradient Descent) are amazing Mathematical objects.
- Statistics goes back to 250 years. It started as “Inverse Probability”.
- The name statistics comes from “study of data for state”.
- There are two types of statistics (decision theory) – Bayesian and Frequentist.
There were many interesting threads in this conversation:
- Gradient Descent,
- Recommendation systems,
- Privacy, and more.
It is a podcast/video worth watching/listening to. You can find an outline here.