This is Ben Goertzel, chief founder of the AGI conference series.

You are correct that the AGI conferences have a higher ratio of "speculative ideas"/"technical results" to ICML. This is intentional and I belief appropriate -- because AGI is at an earlier stage of development than machine learning, and because it's qualitatively different in character than machine learning.

Machine learning (in the sense that the term is now typically used, i.e. supervised classification, clustering, data minign, etc.) can be approached mainly via a narrowly disciplinary approach. Some cross-disciplinary ideas have proved valuable, e.g. GAs and neural nets, but the cross-disciplinary ideas there have quickly been "computer science ized"...

OTOH, I think AGI is inherently more complex and multifarious than ML as currently conceived, and hence requires more "out of the box" and freely multi-disciplinary thinking.

I think that in 10-15 years, when the AGI field is much more mature, the conferences will seem a bit more like ML conferences in terms of the percentage of papers reporting strong technical results. BUT, they will never seem as narrowly disciplinary as ML conferences, because AGI is a different sort of pursuit...

Thanks for the kind reply. I said ICML, but NIPS would have been a better point of reference -- since it was originally conceived as a cross-disciplinary enterprise. The NIPS TOC looks like this:

http://nips.djvuzone.org/nipsxx-toc.html

which indicates it's possible to have a selection of papers both technically sharp and interdisciplinary. We should all be so lucky to attract such a set of papers.

I'm reminded of the 1958 editorial by Peter Elias in the IEEE Information Theory Transactions ("Two Famous Papers"): http://oikosjournal.files.wordpress.com/2011/09/elias1958ire...

I sincerely wish you, your conference, and your research enterprise the best.