Simpler Rhythms could be made creative. I am not a drummer or expert in researching popular bands but e.g The Ting Tings have a very interesting rhythm section.
I don't know much music theory but the chord progression in the first 4 bars it seems to deliberately miss the final chord, which leaves us without resolution. The next chord sounds like a change but we don't know what the root it is going to (so any chord would make sense, may it be a minor 6th or 3rd). Then there's this pedal note that is through the whole tune. It can be a tonic or a 7th so very ambiguous.
It reminds me of some musicians that try to comp songs that they don't know (neither the theme melody or chords). Play this way they can easily add one or two notes from the keyboard to a big 7 major/minor/dominant chord and seem to follow the song's chord progression, while the singer will add colour and melody. The audience's brain will fill the gap by themselves.
Yes there was once a hype about these graphs and standards so called Resource Description Framework (RDF). It never took off. The knowledge itself requires hefty curation though, if it's in a field that requires low false positive rate such as pharmacology.
Not my area at all, just passing by and wondering to the extent and how they use knowledge graphs for drug discovery.
Some time back I had a peek at AstraZeneca's GitHub [0] and got me curious. I know in genomics they try to use custom hardware to accelerate the process using FPGAs and others [1].
Curious if anyone can shed light on knowledge graph use at scale is being accelerated.
I only know in my area you can infer gene and protein interaction network using knowledge graphs to some degree. In drug discovery I've seen graphs of chemical knowledges and what can be drugged and what not. https://pubs.acs.org/doi/10.1021/acs.jpca.2c06408
There might be more publications on mining literature and building such graphs but I'm not following it much since deep learning took over.
I thought it is pretty common to apply mixed / hierarchical linear models? I didn't study statistics but in our field of many problems of modelling biological effects we would do that.
They could help in stratifying patients and strategically targeted therapy. They can't be easily targeted (drugged) drirectly but they could lead to therapeutics if I understand correctly.
Genotyping assays for single nucleotide polymorphisms (SNPs) are relatively cheaper (I may not be up to date). In the space of 'polygenic risk score' of these genomice variants it is still a bit of debate how useful it is for screening.
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