I was just reading Michael Nielson's free ebook: Neural Networks and Deep Learning: A Principle-Oriented Approach[1] yesterday. When Dr. Nielsen tries to reason why it may or may not have a simple algorithm that represent the intelligence, this excerpt strike me the most:<p><pre><code> In the 1970s and 1980s Marvin Minsky developed his "Society of Mind" theory,
based on the idea that human intelligence is the result of a large
society of individually simple (but very different) computational processes
which Minsky calls agents. In his book describing the theory, Minsky sums up
what he sees as the power of this point of view:
</code></pre>
What magical trick makes us intelligent? The trick is that there is no trick.
The power of intelligence stems from our vast diversity, not from any single,
perfect principle.<p>Thought it's relevant to mention about it.<p>[1]: <a href="https://news.ycombinator.com/item?id=12305455" rel="nofollow">https://news.ycombinator.com/item?id=12305455</a>
I have often thought this, and I'm glad someone wrote the paper. I'd like to see more research in this area. It could end up being applicable to the design of more intelligent processes for group decision making at government scale.
Asset markets are a poor choice for studying "accurate shared beliefs". They're an excellent choice for studying groupthink, though.<p>The whole premise that people arrive at accurate shared beliefs is rather extraordinary to begin with. In my experience, widely shared beliefs are much more likely to be inaccurate.
For long I have been thinking that online communities such as YC and reddit benefit from an accelerated process of group evolution. Where other contexts necessitate 10 years to converge on a common idea/ideology, some communities do it orders of magnitude faster. Maybe this paper could explain why it works faster in some groups than others, given the topology and size.