- a “technology and tools” long article on picking the “right” loss function when constructing an algorithmic predictor or another ML tool,
although the author remains vague about the “rightness” part (with an incorrect entry for Huber loss). The message is however clearly that tuning the loss function to the problem one wants to address is (obviously) key. With additional advices about properly handling outliers, avoiding overfitting, and correctly modelling noise. In short, run a proper statistical analysis! - a call for neuroscientists not to be afraid of studying religions, which should sound like an obviousness, but believers and religious leaders are often so touchy about their faith that running representative scientific studies of the “brain processes associated with religiosity and spirituality” may prove inaccessible. I also find the statement “researchers might be able to get a better handle on what (if any) alterations happen in people’s brains in the rare instances when religious belief turns to radicalized action or sectarian hatred” closer to Brave New World or Clockwork Orange than to the purpose of Nature!
- the warmest summer ever, ever, ever…
- a scary story from South Korea where an academic got sentenced to two years in prison for sharing data with Chinese collaborators on “national core technology”, a case reminiscent of similar ones earlier in the US. And where the academic researcher is again seen as the sole culprit instead of their university or the government sharing the responsibility. In France, the imminent threat to turn mathematics and statistics labs into restrictive regime zones (ZRR), with much heavier constraints on visitors and students, and on publication contents, carried by the researchers themselves, pertains from the same tendency. (A personal illustration of the induced administrative absurdities: my datascience lab being next to a biomedical ZRR lab, I am not allowed to use the lift shared by both units, but can nonetheless reach the same spot using the nearby stairs.)
