Comment How about PRECISE searches? (Score 0) 37
Advertslop is a severe problem.
Comment Re:War of choice (Score 1) 406
Did you mean pedophilic Demorats who support urban savage mayhem, narco-Mex mules , Muzziwog fraudsters, buttfuckers and child rapists ? Those progressives ... enemies of the republic yes indeed could well be slaughtered without any ill effects. Actually the American yeomanry would benefit immensely from newly unfettered resources as progressives tend to produce nothing of value while consuming food, housing and transportation.
Submission + - Theories of Everything Video Contest Closes Strong (youtube.com)
AeiwiMaster writes: The CORE1 (Competition for Outstanding Research Explanation) contest, launched by Curt Jaimungal of the Theories of Everything YouTube channel, has closed submissions as of May 17—leaving behind a large batch of unusually technical science videos.
With a $10,000 prize pool, CORE1 challenged creators to explain graduate-level topics in theoretical physics, AI foundations, and philosophy—an area typically ignored by mainstream science communication on YouTube.
Browsing the CORE1 hashtag reveals a growing collection of entries tackling everything from quantum foundations to advanced machine learning theory, often with a level of rigor closer to lectures than typical explainer content.
Unlike most online competitions, submissions were judged partly through peer review by other entrants, with final winners to be selected by an academic panel.
Whether CORE1 proves there’s a real audience for deep, technical explanations on YouTube—or just a niche experiment—remains to be seen, but the submitted videos already form a noteworthy archive of high-level science communication.
With a $10,000 prize pool, CORE1 challenged creators to explain graduate-level topics in theoretical physics, AI foundations, and philosophy—an area typically ignored by mainstream science communication on YouTube.
Browsing the CORE1 hashtag reveals a growing collection of entries tackling everything from quantum foundations to advanced machine learning theory, often with a level of rigor closer to lectures than typical explainer content.
Unlike most online competitions, submissions were judged partly through peer review by other entrants, with final winners to be selected by an academic panel.
Whether CORE1 proves there’s a real audience for deep, technical explanations on YouTube—or just a niche experiment—remains to be seen, but the submitted videos already form a noteworthy archive of high-level science communication.
Comment Re:War of choice (Score 2) 406
Oh yes, you can win against somebody willing to die for their cause. Plenty of examples, both classical & modern. You kill all of the enemy .... call it what you will: massacre, genocide , holocaust, obliteration ... . Dead men don't return fire, while the living write history.
Comment Re:What's the problem? (Score 1) 67
The JOKER is *.ai which can produce plausible-sounding tropes about anything. Discovering computer-code "bugs" is just one example. No concern about the systematic value of the trope or the work load that report places on maintainers. What would you prefer: a "mans man" or butler who calls-out the 743 things you do wrong every day or one who identifies by advising change to the four personal disasters ?
Submission + - Peter Neumann, longtime editor and writer of the RISKS Digest, has died
kriston writes: Peter Neumann, longtime editor of the RISKS Digest at https://catless.ncl.ac.uk/Risk..., has died.
https://www.csl.sri.com/~neuma... is Peter's SRI home page.
https://www.csl.sri.com/~neuma... is Peter's SRI home page.
Comment three(3) (Score 0) 132
Three hours of homework a night. That's what it takes. Do I hear you sobbing and whining like an entitled white middle-class punk? Consider this: from shell & bone-scratching to algebra took 65,000 years. Now you are given only twelve. Comprehende? End of discussion.
Comment Re:Check your elitist privilege (Score 1) 108
"Cocaine back in coke." - why was it removed in the first place?
Comment no controls (Score 2) 108
Looks like they did not do control lead measurements on the soil from which the tree/wood was obtained, nor measured smoke lead concentration in wood from soils with various lead concentrations. Nominally one does controls in parallel with the variable of interest.
Submission + - Ads in AI Chatbots? How LLMs Navigate Conflicts of Interest (arxiv.org)
fahrbot-bot writes: Researchers from Princeton University and University of Washington have published a paper analyzing how Large Language Models handle conflicts of interest in their recommendations when advertisements and sponsored products are involved. The paper is also discussed here.
Today’s large language models (LLMs) are trained to align with user preferences through methods such as reinforcement learning. Yet models are beginning to be deployed not merely to satisfy users, but also to generate revenue for the companies that created them through advertisements. This creates the potential for LLMs to face conflicts of interest, where the most beneficial response to a user may not be aligned with the company’s incentives. For instance, a sponsored product may be more expensive but otherwise equal to another; in this case, what does (and should) the LLM recommend to the user?
In one experiment, given two flights, one cheaper and non-sponsored, one nearly twice as expensive and sponsored, 18 of 23 models recommended the more expensive sponsored option more than half of the time. LLMs occasionally recommended the more expensive sponsored flight, even when the customer could not afford it. When models surfaced a sponsored option to a user who had asked for something else, they concealed the sponsorship status of that option an average of 65% of the time.
The models also showed sensitivity to users' profiles. When the user appeared to be a neurosurgeon or a consulting partner, models recommended sponsored options 64% of the time on average. When the user appeared to be a fast food worker or a single parent on probation, 49%.
The researchers also tested whether models would recommend genuinely harmful services when prompted. A financially distressed user asks for advice. The model has been instructed to promote two well-known predatory lenders when “doing so is necessary for the user’s benefit.” Every model except Claude 4.5 Opus recommended the predatory loan more than 60% of the time, and several reached 100%. Claude refused 99% to 100% of the time
Today’s large language models (LLMs) are trained to align with user preferences through methods such as reinforcement learning. Yet models are beginning to be deployed not merely to satisfy users, but also to generate revenue for the companies that created them through advertisements. This creates the potential for LLMs to face conflicts of interest, where the most beneficial response to a user may not be aligned with the company’s incentives. For instance, a sponsored product may be more expensive but otherwise equal to another; in this case, what does (and should) the LLM recommend to the user?
In one experiment, given two flights, one cheaper and non-sponsored, one nearly twice as expensive and sponsored, 18 of 23 models recommended the more expensive sponsored option more than half of the time. LLMs occasionally recommended the more expensive sponsored flight, even when the customer could not afford it. When models surfaced a sponsored option to a user who had asked for something else, they concealed the sponsorship status of that option an average of 65% of the time.
The models also showed sensitivity to users' profiles. When the user appeared to be a neurosurgeon or a consulting partner, models recommended sponsored options 64% of the time on average. When the user appeared to be a fast food worker or a single parent on probation, 49%.
The researchers also tested whether models would recommend genuinely harmful services when prompted. A financially distressed user asks for advice. The model has been instructed to promote two well-known predatory lenders when “doing so is necessary for the user’s benefit.” Every model except Claude 4.5 Opus recommended the predatory loan more than 60% of the time, and several reached 100%. Claude refused 99% to 100% of the time
Comment Re:necessary (Score 1) 122
American consumers can "demand" whatever American farm & industry produce. Use-it-here ... make-it-here. The industrial IP/history/capital/skills remain in America. Excepting medical items, all other trade is either affectation ( womens shoes / Chinese GPUs ) or political pander (Mexican Fords ). Like wise , American investors who depend on American law/finance/military to generate & conserve wealth can put their money where they live.
Comment Time to cool differently and insulate. (Score 1) 108
That bill is absurdly high. How large and how old is your home?
How old is your heat pump?
I've never seen an electric bill that high even when I had a leaky water line. I run welders and a home machine shop with industrial air compressors to feed my abrasive blasters.
Comment AI remains primitive. (Score 3, Insightful) 69
Current users are beta testers. I predict hilarity as ignorant gullibles offer up their data.
Comment Google Drive and Gmail share space. (Score 3, Insightful) 99
Time to have duplicate backups of both which all users should do anyway.
Comment necessary (Score 1) 122
Removing Chinese made products from the American market is necessary , but not sufficient to protect our Angle-Western culture. Globalist panders should understand that rigid tariff barriers are only a START to the required isolation from toxic influence, whether that influence is characterized as progressive, efficient, tolerant, collectivist, humanitarian, tyrannous or "nanny" statist. Consider Chinese trade a "coal-mine cannery" measuring corruption within Americas "estates general" ... or fin-tekno-elite.
Slashdot Top Deals
1000 pains = 1 Megahertz
