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doc/src/week47/week47.do.txt

@@ -2013,6 +2013,25 @@ problems by logical reasoning.
 
 _Bayesian Machine Learning is one of the exciting research directions in this field_.
 
+
+!split
+===== Scientific Machine Learning =====
+
+An important and emerging field is what has been dubbed as scientific ML, see the article by Deiana et al "Applications and Techniques for Fast Machine Learning in Science, arXiv:2110.13041":"https://arxiv.org/abs/2110.13041"
+
+!bblock
+The authors discuss applications and techniques for fast machine
+learning (ML) in science -- the concept of integrating power ML
+methods into the real-time experimental data processing loop to
+accelerate scientific discovery. The report covers three main areas
+
+o applications for fast ML across a number of scientific domains;
+o techniques for training and implementing performant and resource-efficient ML algorithms;
+o and computing architectures, platforms, and technologies for deploying these algorithms.
+
+!eblock
+
+
 !split
 ===== Quantum machine learning =====
 
@@ -2110,6 +2129,21 @@ topics. Together, we will not just predict the future, but create it.
 
 
 
+!split
+=====  AI/ML and some statements you may have heard (and what do they mean?)  =====
+
+o Fei-Fei Li on ImageNet: _map out the entire world of objects_ ("The data that transformed AI research":"https://cacm.acm.org/news/219702-the-data-that-transformed-ai-research-and-possibly-the-world/fulltext")
+o Russell and Norvig in their popular textbook: _relevant to any intellectual task; it is truly a universal field_ ("Artificial Intelligence, A modern approach":"http://aima.cs.berkeley.edu/")
+o Woody Bledsoe puts it more bluntly: _in the long run, AI is the only science_ (quoted in Pamilla McCorduck, "Machines who think":"https://www.pamelamccorduck.com/machines-who-think")
+
+
+If you wish to have a critical read on AI/ML from a societal point of view, see "Kate Crawford's recent text Atlas of AI":"https://www.katecrawford.net/"
+
+_Here: with AI/ML we intend a collection of machine learning methods with an emphasis on statistical learning and data analysis_
+
+
+
+
 
 !split
 =====  Best wishes to you all and thanks so much for your heroic efforts this semester =====
@@ -2124,4 +2158,3 @@ FIGURE: [figures/Nebbdyr2.png, width=500 frac=0.6]
 
 
 
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