The paper trains a model that a. requires training data in a specific environment. Meaning, to deploy this tech, you need access to the space first to train this model. b. once trained, will not transfer its knowledge if routers are moved, or setup is deployed in a new area. c. training was done with just a single person moving. multiple people moving was not evaluated by this tech/probably harder to achieve. With that in mind, I think privacy-invasion capability of this technology is exaggerated by some comments here.
> Indeed, it has been shown that SENS-based classifiers can infer privacy-critical information such as keyboard typing, gesture recognition and activity tracking ... since Wi- Fi signals can penetrate hard objects and can be used without the presence of light, end-users may not even realize they are being tracked .. individuals should be provided the opportunity to opt out of SENS services – to avoid being monitored and tracked by the Wi-Fi devices around them. This would require the widespread introduction of reliable SENS algorithm for human or animal identification.
> Meaning, to deploy this tech, you need access to the space first to train this model.
Government secret services have gone and re-built the houses of high-profile raid targets before. And it's only a matter of time until simulation technology becomes powerful enough to do a "good enough" digital recreation from blueprints.
> multiple people moving was not evaluated by this tech/probably harder to achieve
At least one scenario in the article mentions "a room with several people". People moving around is just a question of speeding up data collection and analysis.
> With that in mind, I think privacy-invasion capability of this technology is exaggerated by some comments here.
The key thing is, what is public research grade now, is likely already a developed asset in government toolkits. And now that the general public has access to such technology, it will - more likely than not, given it can be done on 50$ low-cost devices - be commoditized, particularly where there is a financial interest in tracking people. I think a good candidate will be supermarkets and similar stores - at least in Europe, stuff like running analytics on surveillance cameras is pretty frowned upon under GDPR, but something like wifi-based tracking should be relatively unproblematic.
Stores already commonly track people's movements and repeat visits by their cell phones. Bluetooth beacons are used to log any device that wanders near enough. No need for wifi tracking.
Not everyone is trying to display a widget, with data from a remote database. If you work with local/edge data, then having access to numpy/pandas/scikit-learn/pytorch can be quite handy
What problems did you have with android services? Have been using them without issues (sticky services work well enough), and with python machine learning/scikit-learn, scipy,numpy, pandas, opencv this framework is one of a kind for rapid moibile development if you are doing any kind of edge data processing.
Funny how blaming GIL for being a bottleneck is the least researched/not backed by performance measurement (before/after) part of the article. Everyone loves to hate GIL. maybe there should be T-shirts made for this for the C++ loving folks out there.
To me, seeing the GIL held for 40% of time and significant time spent waiting on GIL by other threads was a fairly strong indicator. Keen to hear your thoughts/experience on it.
Electric cars need a range extender. Due to lack of imagination on both consumers and manufacturers, this means buying a second ICE car to act as a range extender. Here is an example of planning camping trip on tesla route planner: https://www.tesla.com/en_CA/trips#/?v=M3_2015_74&o=Guelph,%2...
With an ICE, you save over 3 hours of trip time, and modern conveniences of a gas station. Priceless.
Also, women dont rate 'male attractiveness' to the same degree of importance as the other way around. So the distribution is skewed maybe for a different reason: women are asked to match men they 'rate' to pictures they see on public media, and only 20% make it.
Strong encryption is another tool of the rich and powerful to help evade public oversight and scrutiny. Unpopular thought here, cuz, well, most people commenting here are the top wealthy 5-10%, the rich and powerful. It would be a cognitive dissonance to blieve otherwise.
