I looked at a summary of his work.  I&#x27;ve never heard of him or of the BACON program so my knowledge is essentially zero in this.   Looking at summary of his work it doesn&#x27;t seem to me to qualify either.<p>I&#x27;m not sure how to convey the idea in my head to English in such a way to make it clear why I think BACON doesn&#x27;t qualify as discovering new ideas.  I&#x27;ll try though.<p>From the write up, by Langely, of the program he wrote the program to detect regularity in data and if it found such regularity it would &quot;leap out&quot; to the program so that &quot;it could take appropriate&quot; action.  As I understand the program it picks up on any sort of regularity.  The program doesn&#x27;t understand which forms of regularity are important and which are not.  The programming system and data it looks at are geared to finding regularity that are meaningful.  If the data inputs are vastly widened then it seems to me it would find regularity that wouldn&#x27;t be considered meaningful.  I can imagine the program fixating on a regularity pattern that is meaningless.  I hope what I&#x27;m writing makes sense.<p>The work he did is interesting and I wonder what advances have been made since then.<p>Let me ask this question.  Would a program that looks for regularity discover that in finite probability spaces probability zero events never occur?  I think this is something a computer could discover.  Could it end up concluding that probability zero events can occur if one looks at uncountable probability measure spaces?  It seems to mean that programs will never be able to think or discover things at a meta level.  Would a program be able to discover Godel&#x27;s incompleteness theorem?  Of course I don&#x27;t know the answer.  I just suspect that the answer is no.  However, humans took thousands of years to discover these things.  So perhaps an AI that ran for that long could as well.<p>Thank you for pointing me to the BACON program.  I&#x27;d never heard of it before.