This is a slippery slope, IMHO. It can easily get you to be the next "tactical tornado" of your team (cf. John Ousterhout, A Philosophy of Software Design).
I also worked for 10 years at a small movie theater in Italy, and very much share what you described. The noises, the lights, the repetitive and almost ritual actions.
A very nice illustration the projectionist's life is told in the excellent movie "Cinema Paradiso" [1,2].
Has anything changed significantly since 2014 that would make today's cellphones more efficient at detecting gammas?
IIRC the tiny size of the cmos camera was the limiting factor...
The CMOS sensors have gotten much bigger (4-6x area plus there's multiple cameras) and the amplifiers are now almost thermal noise limited... but there's so much AI between you and the image that without using RAW it would be stomped out.
I'm not sure how well the phone cameras would deal with cooling... since you don't really need the mechanical AF or zoom to work. That would be the next step, if you deconstructed them.
Considering the size of modern sensors (48MPix and more) I doubt there's any hope for any continuous processing of Raw sensor data on the phone. Or is it?
Agreed. You would want to black them out and set them for long exposures to minimize dead readout time. You can get RAW data out of iPhone Pros, though it's not something I've played with.
I'm the maintainer of human-learn. While I cannot speak on behalf of the maintainer of DataQA, but it does seem like this tool is more specific to the entity detection use-case. I imagine it has better support for tools that deal with text.
Human-Learn, on the other hand, is more focussed on tabular data and the scikit-learn stack. Since scikit-learn doesn't have a convenient pipeline for entity detection, I would certainly recommend exploring other tools than human-learn for this use-case.
I've not used DataQA before, but figured it'd be relevant to share my input.
Thanks for sharing! It looks very interesting. From a brief check, they do not seem to be UI-based like dataqa (although you can use it in a notebook), they do not offer a search engine and they are probably one level of abstraction below dataqa. You can do some of the stuff dataqa does but would need to code. Some of the rules offered by dataqa rely on complex operations with regular expressions, and are not so easy to program yourself.
Oh, yeah, for sure the target audience is python devs with human-learn. There are user-interfac-y things but those are accessed from a Jupyter notebook.
Your reply is fun to read and I really enjoyed it.
Of course the descriptions of the "typical day" in the original blog post is idealized. I suppose this idealization is there to make the contrast between the highly-effective day and the low-effective day. That is just the blog post.
Leaving aside this funny idealization and its comic interpretation of the blog post, in real life there are good habits and bad habits that can make a team work more efficiently and less efficiently. I have had first-hand experience with developers from ThoughtWorks, the consulting company behind that blog, and I can tell that they are indeed trying to apply those principles and strategies in their projects.
The fact that they are a consulting company gives them an advantage when trying to apply these principles. They only need to worry about the "small picture" of the project they're consulting on. They don't have to deal with all the "big picture" issues that might affect the employees working within the company they're consulting for (e.g. company politics, technical legacies, etc.)
So IMHO perhaps some of these techniques and strategies to become a more effective development team are less applicable if you're working in $BIG_CO rather than in $CONSULTING_CO.
"stable matter, and therefore life and intelligent beings, could not exist if its value were much different. For instance, were α to change by 4%, stellar fusion would not produce carbon, so that carbon-based life would be impossible. If α were greater than 0.1, stellar fusion would be impossible, and no place in the universe would be warm enough for life as we know it."
I know. But which direction? Higher, lower, or both? If it's 4% in both directions that's quite a coincidence.
And since we're talking about percentages of α, I will emphasize that going from .007 to .1 is a change of well over a thousand percent. That example is the exact opposite of the anthropic principle showing that we "could not exist if its value were much different"!
