Summary of Building Brains to Understand the World's Data

These are my notes on the following excellent video, by Jeff Hawkins. For reference, I buy it. This works for me. However, it’s rather old and I just wish we were further along, so I could use it to do stuff.

Does anyone know of an updated summary of comparable clarity?

Building Brains to Understand the World’s Data - YouTube

How to do machine intelligence
1. Discover operating principles of neocortex
2. Build systems based on these principles

The neocortex is a memory system, which receives a high velocity data stream and learns a model that allows it to:
• make predictions
• detect anomalies
• perform actions

The top 6 principles of neocortical function are:
1. On-line memory system: no batch processing
2. Hierarchy of memory regions
○ highly connected
○ all regions broadly perform the same functions
3. Sequence memory: 90% of memory is patterns over time
○ inference
○ motor
4. Sparse Distributed Representations
5. All regions are sensory and motor
6. Attention

Claim: these 6 principles are both necessary and sufficient for biological and machine intelligence.

SDRs have:
• many bits (thousands)
• few 1’s, mostly 0’s (eg 2000 bits,2% active)
• each bit has semantic meaning
• meaning of bit learned not assigned

• two SDRs with shared bits have semantic similarity
• only need to store the active bits (and a subset is OK)
• can union SDRs prior to compare

Claim: SDRs are the future of intelligent machines, there is no other way.
• language
• self-driving cars