summer school

_posts/2023-11-2-creativity.md

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+Math is really a beautiful system (framework?) from which we can derive ideas of beauty through symmetry and geometry, study of complex systems through calculus, and also of creativity. 
+-	How would I define creativity?
+o	Imagine you’re an enthusiastic pursuer of truth.  In front of you are a some numbers and two operators: + (ordinary addition) and * (ordinary multiplication). Science, or the discovery of knowledge, is analogous to discovering new numbers. You randomly add two numbers, 1 and -1 and discover 0. Then you add 1 to 1 and obtain 2. Repeating this process you discover all the integers. From God’s point of view, addition and multiplication over integers is closed in this set, therefore you can’t discover anything beyond the horizon of integers, even though you can discover a lot. You can find patterns, such as properties of commutativity, transitivity and distributivity. 
+o	Creativity, in this scenario, would be proposing another operator such as division. Having this new operator in your arsenal of tools to perceive reality, you can now compute a new class of numbers, the rationals and thus discover the set of all real numbers. 
+o	The infiniteness of numbers is analogous to the infinity of knowledge. 
+	Further creativity would be introducing the square root, and this tool extends our perceptual horizon to encompass the realm of complex/imaginary numbers.
+	A different civilization, using a different set of symbols to encode numbers, may make similar discoveries, i.e., numbers obtained following the same principles of computation using + and *, discovering commutativity, transitivity and distributivity. This underlies/represents the universality of knowledge. 
+o	I’ve ignored letters, phonemes, words to simplify this overly-idealized world to get my ideas on what is creativity across. 

_posts/thoughts-deepmind-cell.md

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-> [J]ust as mathematics turned out to be the right description language for physics, AI may turn out to play a similar role for biology - Demis Hassabis, CEO of DeepMind
+>>... [J]ust as mathematics turned out to be the right description language for physics, AI may turn out to play a similar role for biology - Demis Hassabis, CEO of DeepMind
 
-# 
+# Is deep learning sufficient?
 
 Test set is a pseudo-replication of the training set.
 
-Cite Guy's paper on the paradox to learn to reason, and ObjectNet, and Stammer et al. ARC is also a dataset that makes sure the test set differes from the training set.  
+Cite Guy's paper on the paradox to learn to reason, and ObjectNet, and Stammer et al. ARC is also a dataset that makes sure the test set differs from the training set.  
 
 We have no control on what artifacts of the dataset a deep learning model is looking at. If you only want to get the job done, such as car plate recognition for a reserved parking spot, or sentimen analysis on restaurant reviews, it'd suffice to either output feature maps
 
@@ -16,4 +16,16 @@ It is still the human scientists deciding what sequence of genes to decode.
 
 At least in coursework, More challenging benchmarks, then should involve modifications of the testing distribution in order to not mislead the audience that a DNN is performing greatly. 
 
-In the future, however, I have confidence that AI can inspire future directions of research. 
+In the future, however, I have confidence that AI can inspire future directions of research. 
+
+### On the science of intelligence and how it impacts unrelated fields
+
+NeSy, despite pursuing the understanding of human intelligence, can yield unexpected insights into tackling problems in completely unrelated fields
+
+The above statement is supported by anecdotal evidence where scientific research translated into overarching technological applications for social good on completely unrelated fields. Our confidence on such an idea can come from Prof. Geoffrey Hinton's [interview with CBS](https://www.youtube.com/watch?v=qpoRO378qRY), among the endeavors of other researchers pursuing science whose work was converted into technologies benefiting humankind. Efforts include:
+- [Prof. Katalin Karikó](https://arstechnica.com/health/2023/10/after-being-demoted-and-forced-to-retire-mrna-researcher-wins-nobel/), whose pursuit in understanding the central dogma of biology, namely how messenger-RNA translates into proteins, laid the foundation for the design of mRNA vaccines against the coronavirus during the COVID-19 pandemic. 
+- Prof. Yann LeCun, Prof. Yoshua Bengio, Prof. Jürgen Schmidhuber and Prof. Geoffrey Hinton himself, whose research into how the human brain works, such as how to simulate the visual cortex, how to reproduce human language, how can a machine achieve self-reference or how machines can learn like human beings, kickstarted the Third Revolution of Artificial Intelligence that can translate into a plethora of applications spanning over biomedicine
+- Prof. Noam Chomsky's work on a universal grammar underlying Human thought for understanding human language, which helped inspire work like the design of the [FORTRAN programming language](https://en.wikipedia.org/wiki/Noam_Chomsky#Reception_and_influence)
+- And many more examples, where who knows how research on intelligence can help with simulating a biological cell. 
+
+If the above anecdotes remind you of the book [Why Greatness Cannot Be Planned](https://link.springer.com/book/10.1007/978-3-319-15524-1) by Prof. Kenneth O. Stanley and Joel Lehman, then there is another perspective from which to support the idea that basic science can fuel technological progress.