Archive for artificial intelligence

the Ramanujan machine

Posted in Books, Kids, pictures, University life with tags , , , , , , , , , , , on February 18, 2021 by xi'an

Nature of 4 Feb. 2021 offers a rather long (Nature-like) paper on creating Ramanujan-like expressions using an automated process. Associated with a cover in the first pages. The purpose of the AI is to generate conjectures of Ramanujan-like formulas linking famous constants like π or e and algebraic formulas like the novel polynomial continued fraction of 8/π²:

\frac{8}{{{\rm{\pi }}}^{2}}=1-\frac{2\times {1}^{4}-{1}^{3}}{7-\frac{2\times {2}^{4}-{2}^{3}}{19-\frac{2\times {3}^{4}-{3}^{3}}{37-\frac{2\times {4}^{4}-{4}^{3}}{\ldots }}}}

which currently remains unproven. The authors of the “machine” provide Python code that one can run to try uncover new conjectures, possibly named after the discoverer! The article is spending a large proportion of its contents to justify the appeal of generating such conjectures, with several unsuspected formulas later proven for real, but I remain unconvinced of the deeper appeal of the machine (as well as unhappy about the association of Ramanujan and machine, since S. Ramanujan had a mystical and unexplained relation to numbers, defeating Hardy’s logic,  “a mathematician of the highest quality, a man of altogether exceptional originality and power”). The difficulty is in separating worthwhile from anecdotal (true) conjectures, not to mention wrng conjectures. This is certainly of much deeper interest than separating chihuahua faces from blueberry muffins, but does it really “help to create mathematical knowledge”?

dependable AI/ML [France is AI]

Posted in Statistics with tags , , , , , on January 21, 2021 by xi'an

missing bit?

Posted in Books, Statistics, University life with tags , , , , , , , , on January 9, 2021 by xi'an

Nature of 7 December 2020 has a Nature Index (a supplement made of a series of articles, more journalistic than scientific, with corporate backup, which “have no influence over the content”) on Artificial Intelligence, including the above graph representing “the top 200 collaborations among 146 institutions based between 2015 and 2019, sized according to each institution’s share in artificial intelligence”, with only the UK, Germany, Switzerland and Italy identified for Europe… Missing e.g. the output from France and from its major computer science institute, INRIA. Maybe because “the articles picked up by [their] database search concern specific applications of AI in the life sciences, physical sciences, chemistry, and Earth and environmental sciences”.  Or maybe because of the identification of INRIA as such.

“Access to massive data sets on which to train machine-learning systems is one advantage that both the US and China have. Europe, on the other hand, has stringent data laws, which protect people’s privacy, but limit its resources for training AI algorithms. So, it seems unlikely that Europe will produce very sophisticated AI as a consequence”

This comment is sort of contradictory for the attached articles calling for a more ethical AI. Like making AI more transparent and robust. While having unrestricted access to personal is helping with social engineering and control favoured by dictatures and corporate behemoths, a culture of data privacy may (and should) lead to develop new methodology to work with protected data (as in an Alan Turing Institute project) and to infuse more trust from the public. Working with less data does not mean less sophistication in handling it but on the opposite! Another clash of events appears in one of the six trailblazers portrayed in the special supplement being Timnit Gebru, “former co-lead of the Ethical AI Team at Google”, who parted way with Google at the time the issue was published. (See Andrew’s blog for  discussion of her firing. And the MIT Technology Review for an analysis of the paper potentially at the source of it.)

AI for the sciences [PhD funding]

Posted in Statistics with tags , , , , , , , , , on December 9, 2020 by xi'an

Our mega-university, PSL, is calling PhD candidates to apply for one of the 15 PhD scholarships supported to work on one of the 24 PhD topics proposed in the call. Deadline is 22 February 2021, the only constraint for applicants being that they must have stayed or studied less than 12 months in France, since 27 Feb 2018 … Here are some of the 24 topics:

launch of ELLIS

Posted in Statistics, University life with tags , , , , , , , , , on September 15, 2020 by xi'an

The European Laboratory for Learning and Intelligent Systems (ELLIS) is a network (inspired by the Canadian LMB CIFAR network ) that has been recently created to keep European research in artificial intelligence and machine learning at the forefront, to keep up with North America and China where the AI investments are far superior. It has currently 30 units and will be officially launched this Tuesday, 15 September with live streaming. (I am part of the Paris Ellis Unit, directed by Gabiel Peyré.) It also organizes PhD and postdoc exchange programs.