375 karma · joined June 12, 2013
I wonder if this is also being done to limit marketplace data being scraped with the API or limit how this data gets used by limiting low margin business models. Increasing the fees will have these effects.
1) A coordinated effort among different sites will have a much greater chance of poisoning the data of a model so long as they can avoid any post scraping deduplication or filtering.
2) I wonder if copyright law can be used to amplify the cost of poisoning here. Perhaps if the poisoned content is something which has already been shown to be aggressively litigated against then the copyright owner will go after them when the model can be shown to contain that banned data. This may open up site owners to the legal risk of distributing this content though… not sure. A cooperative effort with a copyright holder may sidestep this risk but they would have to have the means and want to litigate.
> What we have aren't unified social credit systems…yet. They're fragmented behavioral scoring networks that don't directly communicate. Your Uber rating doesn't affect your mortgage rate, and your LinkedIn engagement doesn't determine your insurance premiums. But the infrastructure is being built to connect these systems. We're building the technical and cultural foundations that could eventually create comprehensive social credit systems. The question isn't whether we have Chinese-style social credit now (because we don't). The question is whether we're building toward it without acknowledging what we're creating.
I get why social media could possibly be the cause but what makes you so certain it is the cause or the largest contributing factor?
The DOI in the article is being reported as invalid. https://doi.org/10.1073/pnas.2517530122
Social Media getting big → larger perceived friend groups
Social Media getting big OR
screen time increasing OR
phones preferencing more limited forms of communication OR
… → more polarization
It could be due to a change in the PEW polling or the polling questions staying the same but the definition of terms shifting over time which caused the perceived increase in polarization. Or even the researchers’ definition of polarization which was stated as an increase in people stably identifying as either liberal or conservative. It is worth noting the article did say the PEW polling is supposed to be a stable source of data.
- The update now clears the shutdown log each boot.
> This led to the conclusion that a cleared shutdown.log could serve as a good heuristic for identifying suspicious devices.
> With iOS 26 Apple introduced a change—either an intentional design decision or an unforeseen bug—that causes the shutdown.log to be overwritten on every device reboot instead of appended with a new entry every time, preserving each as its own snapshot. This means that any user who updates to iOS 26 and subsequently restarts their device will inadvertently erase all evidence of older Pegasus and Predator detections that might have been present in their shutdown.log.
I think one must have a chat with our gods of capital in order to correct it. But I'm not sure they are listening.
https://www.catribunal.org.uk/judgments/14037721-dr-rachael-...
It sounds like HP is continuing to go the subscription route to use one of these “printers”.
In general using these medical/biological metaphors doesn't seem like a good idea in things like computer science research papers and similar.
Their use forces many inaccurate comparisons (when compared in detail) and they engender human qualities to what are already forgotten to be just computer models. I get this may be done with a slight tongue-in-cheek but with research papers there is also the risk that these terms start to be adopted. And undoing that would be a much taller order in either the research community or general media.
Maybe I am just yelling at clouds.
(It's a joke: The parent uses the same writing style they described as being indicative of LLMs)
What gives?
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https://www.risknet.de/uploads/tx_bxelibrary/Bookstaber-Unde...
https://www.consumerreports.org/electronics/personal-informa...
I would argue that the vast majority of people are unable to fairly evaluate this tradeoff due to the intentional lack of transparency in what is collected, how it is used, and who it gets shared with (and how they use it).
> Franaszek also says that “a significant amount of this geolocation dataset appears to be inferred by IP address to geolocation lookups, meaning the vendor or their source is deriving the user's geolocation by checking their IP address rather than by using GNSS [Global Navigation Satellite System]/GPS data. That would suggest that the data is not being sourced entirely from a location data SDK.”
Of note, the screen seems slower to update when waking up or going to the home screen and keyboard touch points seem slightly off and I'm not sure why that is.
The video links to a paper [1] titled "Airborne Circular W-Band SAR for Multiple Aspect Urban Site Monitoring" which mentions beam steering in the abstract.
If so, I see your point.
I still think in a more diverse set of scenarios where an intervention has more than a single and binary outcome, knowing the group probability can still be informative. For example if an intervention in a possibly fraudulent study shows a large upside but other known to be unfraudulent studies show a severe but unlikely downside then it may not be a good idea to do the intervention unless there is a good reason to (ex: all known safer interventions have been tried, known risk can be mitigated, end of life and patient agrees, …).
But I am beginning to wonder how useful of a signal a known fraud percent would be given how long it takes for fraud to be discovered and then disclosed.
I still think something can be done here with public statistics and perhaps reputation but I’ll have to think about it some more. Certainly if an author or institution were more at risk for discovered fraud or fraud discovery was more likely they would do a better job of policing or not doing it. Other incentives (as mentioned in the article) are at play as well.
I think in order to make a good decision in all these possible scenarios (since you don't know which one a specific study might be in) is to make sure you have a good understanding of what the likelihoods are any single study is in one of these scenarios (ex: fraudulent). Right now it would appear the perception and the reality of the likelihood a study is trustworthy is in disagreement.
Hopefully new incentives coupled with public statistics can help fix this.
This paper doesn’t show that simulation is the purpose of REM (though it may be) however they do go on to speculate that the simulation that is occurring could be used to improve the brain’s predictive models of movement actions and their outcomes without needing to move the muscles.
It is thus conceivable that the internal model that coordinates activity between SC and ADN observed during REM sleep may be at work also in the awake animal. This would allow the brain to predict shifts in head direction following the issuing of a motor command in the SC, before the motor command is executed and thus have a real time estimate of heading rather than depending on the necessarily delayed sensory feedback from the vestibular canals. … In the absence of error signals, these internal models are free to unfold and may represent the building blocks of the brain’s generative activity during REM or REM-like sleep in humans and animals.
…this is “the first time that the legs of a legged robot are concurrently utilized for locomotion and for a different task.” This is distinct from other robots that can (for example) open doors with their feet, because those robots stop using the feet as feet for a while and instead use them as manipulators.
So, this is about a lot more than cigarette butts, and the researchers suggest a variety of other potential use cases, including spraying weeds in crop fields, inspecting cracks in infrastructure, and placing nails and rivets during construction.
Some use cases include potentially doing multiple things at the same time, like planting different kinds of seeds, using different surface sensors, or driving both nails and rivets. And since quadrupeds have four feet, they could potentially host four completely different tools, and the software that the researchers developed for VERO can be slightly modified to put whatever foot you want on whatever spot you need.
So, to me, this sounds like a somewhat abstract research problem that some one found a fun concrete way to start progress on. The point isn’t that this is a usable product but rather something which moves the research forward.
Take a look at the history of boston dynamics and you will see similarly impractical real world robots.
For example, this is a video of one of their earlier much simpler robots: https://youtu.be/Bd5iEke6UlE
This Lex Friedman podcast interviews the founder of boston dynamics Marc Reibert and he goes into great detail how they started simple and built from there: https://lexfridman.com/marc-raibert/
I believe the goal is to infer the impact of impressions which do not require a click or user interaction.
Privacy-preserving attribution works as follows:
Websites that show you ads can ask Firefox to remember these ads. When this happens, Firefox stores an “impression” which contains a little bit of information about the ad, including a destination website.
If you visit the destination website and do something that the website considers to be important enough to count (a “conversion”), that website can ask Firefox to generate a report. The destination website specifies what ads it is interested in.
...
https://support.mozilla.org/en-US/kb/privacy-preserving-attr...