It is unfortunate that the only way to get through the regulatory process is copious $ - but it does work. If this project were better funded, it would likely have gotten through.
There is an entire political party representing something like half the population of the US dedicated to shrinking the regulatory apparatus, including the FDA. That doesn't sound like career security to me.
My perception is that the parent commenter is referring at least partly to "subcriminal" or nearly subcriminal behaviour. There is/was nowhere to "put" this kind of individual when they come from these settings, for a whole host of reasons, ranging from: something like "it's your neighbour's mentally ill kid, you really gonna call the cops for THAT?" to "what cops?".
School shooters and "crazy people acting violently" are probably incredibly rare by comparison. Sub/urban environments probably reduce the impact of the mentally ill on their surrounding neighbours in a whole host of ways, in fact -- in no small part because treatment is much less available in rural areas. (There's more of them in a smaller area and they're more visible and increasingly less criminalized, so people get the idea that poverty and health issues of that variety are modern, urban problems.)
Keywords in the literature around this include "community impact" or "community health", but it's not my area.
This is cool. I hooked up Llama to an open-source TTS model for a recent project and there was lots of fun engineering that went into it.
On a different note:
I think the most useful coding copilot tools for me reduce "manual overhead" without attempting to do any hard thinking/problem solving for me (such as generating arguments and types from docstrings or vice-versa, etc.). For more complicated tasks you really have to give copilot a pretty good "starting point".
I often talk to myself while coding. It would be extremely, extremely futuristic (and potentially useful) if a tool like this embedded my speech into a context vector and used it to as an additional copilot input so the model has a better "starting point".
I'm a late adopter of copilot and don't use it all the time but if anyone is aware of anything like this I'd be curious to hear about it.
Prior evidence suggests that sedentary behaviour increases blood biomarkers of cardiometabolic dysfunction.
They studied a hunter-gatherer tribe in Tanzania and found that despite having similar patterns of sedentary behaviour, their blood biomarkers of cardiometabolic dysfunction were much lower than those in industrialized nations. The authors posit that one reason for this is that sedentary behaviour in this group of individuals does not involve furniture -- rather, it usually involves a "deep squat", and the authors show that in this position the muscles are much more engaged than when someone sits in a chair.
This is consistent with evidence that breaking up periods of sitting with movement is good for you.
Their open-access paper talks about some evolutionary context for this hypothesis [1].
Tree spiking is one example of this. It's so common as to be illegal in the United States [1]. Unfortunately, without strict worker protections, it's conceivable that workers would be the ones to pay for their employers' (or their upstream suppliers') illegal actions.
Eh, with one confirmed injury, I'm comfortable calling it "conceivable". The testimony of the injured worker in that case even reflects the fact that a spiked tree does not guarantee injury or death to the operator -- indeed, first there seems to be substantial damage to the machinery, and only then, a risk to the operator [1]:
> Alexander later filed a lawsuit against Louisiana-Pacific claiming that the band saw had been weakened from previous strikes with nails, but that he was forced to work with the saw or face dismissal.
I think there's good evidence that by the time it reaches common use, it will be used that way.
Consider ShotSpotter, which uses an array of microphones in an urban environment to detect gunshots (and often then deploy officers to the location) [1]:
> A ShotSpotter expert admitted in a 2016 trial, for example, that the company reclassified sounds from a helicopter to a bullet at the request of a police department customer, saying such changes occur “all the time” because “we trust our law enforcement customers to be really upfront and honest with us.”
In this case, it seems like it's more like "evidence laundering" - a cop found a bullet (presumably through legitimate means) and would like to use the ShotSpotter results as additional evidence that the shooting took place, and so requests a re-classification of the audio recording. Even in this case, where the parallel evidentiary construction is presumably legitimate, one can imagine the problem - a jury may put more stock in a ShotSpotter result than the cop's testimony about a bullet. But in this case, the ShotSpotter "result" is due precisely to that testimony.
Never mind the fact that ShotSpotter microphones are powerful enough to pick up loud conversations [2]:
> The apparent ability of ShotSpotter to record voices on the street raises questions about privacy rights and highlights another example of how emerging technologies can pose challenges to enforcing the law while also protecting civil liberties.
Predictive policing will require large-scale data collection, and policing institutions don't seem to always use it the way we'd want them to.
assuming bullets are supersonic (or nearly so) the shockwave should be conical (or nearly so). I have no clue what the hardware of a single "shotspotter" node looks like, but each such node should have multiple microphones so it can clearly distinguish the shape in wavefront of a bullet vs a helicopter blade vs conversations... the mere idea it requires manual reclassifications means their hardware deployment is either not up to the task, or used for evidence laundering.
Ideally the hardware has an open design, with a transparent protocol, with real time signed hashing of a hash tree of all nodes recordings. So that the reanalysis can happen transparently with open source software, and since its signed authorities can't bring a doctored audio file. On top any citizen should be able to test the local microphones unexpectedly by an open source speaker device, prove self-selection of a random nonce determining the audio to be played, so he can challenge the audio recording after the fact in a provable way (when nothing has happened). In this way they also can not indefinitely plan an audio substitution without getting caught eventually.
Thanks for outlining a defensive design. Could you recommend good references or example projects for learning how to design open hardware/software for sensor data acquisition, tamper-resistant signals storage, and decentralized analysis?
I won't refer you to specific projects, but I will list a number of keywords, as those should help anyone willing to contribute to explore these ideas further in journal articles, although it seems you already know relevant terms I didn't mention (like "tamper-resistant", although you may have more success with "security envelope").
Specifically regarding bullet detection, you may wish to consult ballistic software which takes into account air friction. Once you can generate random trajectories in air for a representative distribution of initial bullet speeds, it should be relatively simple to transform these to relative pulse arrival times at a 3D array of microphone locations.
For precise pulse arrival times one may wish to look at "constant fraction discriminaors", so that for rising pressures of the pulse, the timing is independent of pulse strength.
For decentralized analysis, and compatibility with the courts it would be best if it didn't output a "Holy Answer", but instead computes an interpretation of the recordings and why it believes in the trajectory it heard, so that at all times an alternative interpretation with a better fit can be proposed, and algorithms improved. This would require the decentralized code to effectively run a formal verifier on the audio evidence backed proof. Reimplementing the metamath verifier on a decentralized blockchain should work.
The devices themselves would best be constructed by and for the population, with individuals selected at random, trained to understand how the device works, and then implementing it and its security envelope.
It would be best if the protocol allowed new concerned citizen to continuously join the protocol, to use threshold cryptography so that the police can only consult the recordings with permission of civilian population, keeping an eye on how often they request to check for a bullet when there was none (some should be tolerated, but bulk collection denied).
The devices should store candidate recordings in a rotating buffer overwriting older / less probable bullet recordings, but always encrypted towards the group by treshold cryptography. These on-device recordings should be considered a backup failsafe only in case internet connectivity disappears. The usual operation is to (immediatly) send the encrypted shards to the group of civilians running the protocol (for time stamping purposes). Individuals or small groups can not decode the recordings on their own, only with sufficient ( K out of N ) civilians agreeing the recordings should be published can they be published, in which case that recording is public for all (including the police). Either everyone gets to hear the shots fired, or no one. Regarding the agreement procedure: that too would use formal verification, the rules and conditions when civilians are supposed to agree should fall under democratic control, and the user agent (software client) the civilians run automatically release or withhold according to these rules. Unreliable citizens that refuse to release their share of the secret when they are supposed to, or leak their share of the secret when they are not supposed to are temporarily banned from participating in the protocol (and will for such duration no longer be remunerated for their participation). This means you don't get cliques of interested parties joining up in large numbers amid a disinterested and unincentivized population cherry picking when to release a recording or not (by modifying the source code of their local client in order to cherry pick against due process when to release the recordings).
Thanks, this is super helpful, especially the civilian and clique game theory scenarios. Will use search terms to find related material.
There may be attempts to use WiFi 7 sensing/radar in 2024 Meteor Lake laptops and 2025 routers to make claims about the presence of specific humans (e.g. gait, breathing, typing signatures), https://www.lumenci.com/post/wi-fi-sensing-applications-and-.... Some of the techniques you've outlined above could be appplied to through-wall WiFi Sensing devices.
Yes, it's unclear how the FCC is allowing IEEE 802.11bf to proceed if it can be used to collect passwords and other typed data, not to mention what people are physically doing in different rooms of their homes and businesses. Good for vendors of 2FA and faraday rooms, but bad for the millions of buildings about to become transparent.
As for keystroke timing, it could theoretically have been collected for years by local and web (search?) services which offered autocomplete. Research and investment is ongoing, e.g. https://arxiv.org/pdf/2101.05570
> Our approach called TypeNet achieves state-of-the-art keystroke biometric authentication performance with an Equal Error Rate of 2.2% and 9.2% for physical and touchscreen keyboards, respectively ... the databases used in this work are the largest existing free-text keystroke databases available for research with more than 136 million keystrokes from 168,000 subjects in physical keyboards, and 60,000 subjects with more than 63 million keystrokes acquired on mobile touchscreens ... The global keystroke biometrics market is projected to grow from $129.8 million dollars (2017 estimate) to $754.9 million by 2025, a rate of up to 25% per year.
IANAL, so I genuinely can't answer that, but in this particular case I'd hope so, yes. More generally, I suspect circumstance dictates. Prosecutors' responsibilities under Brady do seem to be a topic of conversation in the context of "Big Data Policing" [1].
Nope, you're thinking of regression coefficients, where you'd be correct that usually the null hypothesis is $\beta = 0$. In this case, what's being reported are odds ratios, so the null hypothesis would be that OR = 1.
The parent comment's point is that although the reported effect is significant at $\alpha = 0.05$ (the usual "95% CI" you mentioned), there are other problems that render their test of this hypothesis less than valid.
Any evidence for them being a fad? I definitely remember my parents' generation having dedicated one-on-one meetings with their managers on a regular basis, regardless of what field they were working in (skilled labourers, but none of them in tech).
The first 15 years of my career, up until roughly 2010, I had no regular 1:1's in tech. Managers were generally more technical also (they would do non-critical path dev work.) Today there is more separation between "people management" and "technical management." Usually one or the other suffers.
Even in Western medicine (at the research stage, at least), that is not necessarily true in patients suffering from certain conditions.
There is some evidence (in the sense of evidence-based medicine) that a low-FODMAP (fermentable *saccharides) diet reduces symptoms in patients with irritable bowel syndrome. [1]
As far as vegetables go, according to one site high-FODMAP vegetables include alliums and artichokes. [2]
It is worth noting that the authors of the linked review paper caution that it is unknown whether a low-FODMAP diet may have long-term adverse effects.
There is an entire political party representing something like half the population of the US dedicated to shrinking the regulatory apparatus, including the FDA. That doesn't sound like career security to me.