Something I've been thinking about that I don't quite know how to formalize is the role of _understanding_ in the cycle of progress. The other component would be discovery - generating proofs, creating new algorithms, etc. Discovery pushes the boundaries of a field, but understanding disseminates that knowledge, allowing the field to stand on the shoulders of the new discovery and perhaps make yet another.
Understanding is really the measure of utility. I suspect that an average human's intelligence is similar to one 100 years or even a century ago, and thus our ability to discover new theorems and proofs. The difference is the understanding. We not only have the last thousand years of discovery, but also the compaction, categorization, education, tutorials, etc, that allowed us to learn it effectively in a few years or decades of academia.
AI is accelerating the discovery part, but the _understanding_ part is just as vital for true progress.
Isn't the ability for models to discover new things depend on the model understanding what exists already and figuring out how to apply it? It sounds like we already have everything in place to understand things, prove new things, understand those new things, prove new things with that new understanding, etc.
joeldw · · focus · HN ↗
Understanding is really the measure of utility. I suspect that an average human's intelligence is similar to one 100 years or even a century ago, and thus our ability to discover new theorems and proofs. The difference is the understanding. We not only have the last thousand years of discovery, but also the compaction, categorization, education, tutorials, etc, that allowed us to learn it effectively in a few years or decades of academia.
AI is accelerating the discovery part, but the _understanding_ part is just as vital for true progress.
philipwhiuk · · focus · HN ↗
charcircuit · · focus · HN ↗