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tsbischof

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https://www.thomasbischof.net

https://www.alprwatch.org/

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alpr.watch 7 months ago

Different datasets. deflock.me is for ALPR locations, alpr.watch shows where local government meetings are taking place

About 40k new cameras each year from what I have seen.

If you find yourself with some time, there is now a DeFlock app that helps with mapping. It also includes locations where people suspect there might be a camera, though that is limited to about a third of the states so far.

I will be surprised if there is not a startup in the coming years that pays you to run a surveillance mining app that shares data as a way to subsidize the cost of the hardware. The surveillance state equivalent of ads

Why accept surveillance and tracking without a narrow and well-defined scope? It is one thing to track cars for estimating traffic velocity, it is another entirely to create a national database of all locations any given individual has been seen, with minimal oversight to the purpose for collecting and using that data.

An app to screen properties based on your own esoteric criteria. Things like, "I want to have a balcony facing south, looking at a park." Then you can send a list of suitable properties to a real estate agent to scout, or set a notification in case any of them come into the market

One of the big changes was to make many basic tools into lazy iterators instead of greedy lists (map, filter, range, etc.). I can remember having to teach my fellow scientist/engineer colleagues not to just loop over an index variable when working with certain datasets, but this was a major bit of friction because they were so used to Matlab and other languages where direct indexing is the primary method. While lazy execution is great for many things, it is not something that is necessarily common knowledge among people who use coding as a means to an end.

Additionally, because so many of the core libraries were 32-bit only or Python 2 only, you ended up having to either write your own version of them or just go back to 32-bit Python 2. Numpy in particular (and therefore transitively anything halfway useful for science and engineering) took several years to stabilize and I have many memories of having to dig into things like https://www.lfd.uci.edu/~gohlke/pythonlibs/ to get unofficial but viable builds going for the Windows machines we used. It was enough of a pain to deal with dependencies that I actually ended up rolling my own ndarray class that was horrendous but just good enough to get the job done.

That depends heavily on the organization. Our works council technically approves hires but realistically has little influence on most decisions

It partly arises as a mechanism to pay per case, not just per visit. For example, if we put all payment for a breast cancer treatment into the first visit, there is now an incentive to either complete the treatment (ideal) or keep the patient from coming back (less ideal). You can use these follow-up codes to measure rates of return visits, which can be related to quality of care metrics.

A friend of mine founded a company in this space (https://www.joincake.com/). From what I know it is more on the side of helping you build your own solution, rather than delivering all of the technical aspects.

The technical integration would be some significant effort to work out: do you need to run a credential management service? Can you get away with just having account recovery codes, specifying beneficiaries for specific accounts, etc? At first glance it feels like a massive amount of integration work would be needed

I fantasize about this sometimes for scientific purposes. Part of the challenge is how to keep the barrier to entry low enough that people stay excited and creative, because the opposite is the world of regulated industries where your way of thinking is heavily influenced by the legal framework. Periodic synchronization helps and the best I have seen in person at the Gordon Research Conferences (GRC) since these tend to be narrow enough to have consensus but still broad enough to get a little bit of perspective

This is quite common in scientific research. The typical algorithm I follow is to reframe the problem in the language of different fields and see whether there is a more useful way of tackling it in that framework. There are always some leaks in the abstraction/translation but often by reframing the problem you find a good-enough solution.

It's definitely been my experience that reviews are hit-or-miss. Sometimes you get 1-2 reviews where there are valid points that need to be addressed, sometimes you wait 3 months for the reviews to come back, only to find that reviewers 2 and 3 dropped out and reviewer 1 basically said "looks fine".

Part of the challenge of peer review is that it comes _after_ the paper is written, when the cost of changing anything is quite high. I find much more value in peer review when planning experiments, and do so informally with my peers.

They also manage the review process (screen papers, find reviewers, communicate with authors and reviewers), make sure that papers are accessible long-term (decades to centuries), typeset manuscripts, print paper issues, and several other tasks.

But yes, reviewers are not paid. A half-decent review can easily take 3-4 hours, and a typical paper gets 2-3 reviews, so something like 8-12 hours of PhD-level labor which are not currently compensated.

There are several open access solutions but few (if any?) open source solutions. Arxiv is free but lacks reputation outside a small number of fields. PLOS One has a decent reputation in some fields and probably comes closest in being good value.

I know a couple of people working in this space, and ultimately it ends up being a networking issue: in order to get peer reviewers at a scale which is acceptable, you basically have to buy editors with networks of contacts. Since good or even mediocre reviewers are scarce, this ends up leading to significant competition for reviews. But reviewers are not compensated so there is no market pressure for reviewers to actually exist. Publishing is now a profit-driven system built on top of an informal network created by enthusiasts who were originally doing the work because it was important to them.

There have been a couple of attempts at matchmaking systems and rewards systems. https://www.reviewcommons.org/ is the most visible in my field, but they only get 1-2 preprint reviews out per day so far. This is still quite new and there are a couple of other platforms in development.

I issues with Outlook Web App (M365) often. Dropped characters are not so common, but it is common for the cursor to bug out and insist on returning the to start of a line with each new character.