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upstart writes:

How Police Have Undermined the Promise of Body Cameras:

RepublishCo-published with The New York Times Magazine

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When Barbara and Belvett Richards learned that the police had killed their son, they couldn't understand it. How, on that September day in 2017, did their youngest child come to be shot in his own apartment by officers from the New York Police Department?

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When Barbara and Belvett Richards learned that the police had killed their son, they couldn't understand it. How, on that September day in 2017, did their youngest child come to be shot in his own apartment by officers from the New York Police Department?

Original Submission

upstart writes:

Vaccines delivered through the nose or mouth should help stop infection where it begins:

The federal government is working to speed things along with an injection of cash through Project NextGen, a $5 billion effort to usher new and improved covid vaccines to market. In October, the Department of Health and Human Services announced that nearly $20 million would go to two companies developing mucosal vaccines—Codagenix and CastleVax. That money will help the companies gear up for studies to test how well their vaccines work to prevent symptomatic infections.

Codagenix's candidate, a nasal vaccine called CoviLiv, is already part of a phase 3 global efficacy trial coordinated by the World Health Organization. And in October, the company reported results from a safety study in adults in the UK who had never been vaccinated for covid before. The nasal mist prompted robust immunity, at least as measured by markers in the blood. But evidence of an immune response in the blood doesn't necessarily indicate an immune response in the mucosal lining of the airways. Or, as one physician puts it, "just like the 'far, dark side of the Moon', which is invisible from the earth, the mucosal response to pathogens is a far, dark side of immunity that is poorly or not visible from the peripheral blood and more complicated to probe than systemic immunity."

What's the best way to elicit mucosal immunity?

TBD. Different groups are trying a variety of strategies. The goal is to induce immunity in the airways that is robust, broad, and durable. But which strategy will succeed is a bit of a question mark at the moment. Mucosal vaccines fall into a few categories depending on how they're administered and the platform they use. Some are sprays that are squirted into the nose (CovLiv, for example). Others are meant to be inhaled into the lungs (such as one developed by CanSinBIO in China).

Sometimes these two routes of administration get lumped together, but they actually are very different, says Mangalakumari Jeyanathan, a researcher at McMaster University and coauthor of an editorial that accompanies the new inhalable-vaccine paper. With a nasal vaccine, the contents go into the nasal cavity. But Jeyanathan thinks inhaled vaccines, which go deep into the lungs, are likely to work better. Her team's research suggests that nasal vaccines induce immune responses only in the upper respiratory tract, not in the lower respiratory tract. That means, she says, that if the vaccine doesn't prevent infection, the lungs are still vulnerable, and "we really need the immune responses to prevent any sort of serious damage to the lung."

Original Submission

canopic jug writes:

Public Domain Day 2024 is coming up in a few weeks. The Duke University's Center for the Study of the Public Domain has a briefing document, Mickey, Disney, and the Public Domain: a 95-year Love Triangle, about what happens when the earlier versions of Mickey Mouse finally elevate to the public domain at the start of 2024. Included is a Venn diagram of what you can and can't work with.

Steamboat Willie and the characters it depicts – which include both Mickey and Minnie Mouse – will be in the public domain. As indicated in the green circle, this means that anyone can share, adapt, or remix that material. You can start your creative engines too—full steam ahead! You could take a page out of the Winnie-the-Pooh: the Deforested Edition playbook and create “Steamboat Willie: the Climate Change Edition,” in which Mickey’s boat is grounded in a dry riverbed. You could create a feminist remake with Minnie Mouse as the central figure. You could reimagine Mickey and Minnie dedicating themselves to animal welfare. (The animals in Steamboat Willie are contorted rather uncomfortably into musical instruments. PETA would not approve.)

You can do all of this and more, so long as you steer clear of the subsisting rights indicated by the orange circles, namely:

• Use the original versions of Mickey and Minnie Mouse from 1928, without copyrightable elements of later iterations (though not every later iteration will be copyrightable, as I explain below) and

• Do not confuse consumers into thinking that your creation is produced or sponsored by Disney as a matter of trademark law. One way to help ensure that your audience is not confused is to make the actual source of the work – you or your company – clear on the title screen or cover, along with a prominent disclaimer indicating that your work was not produced, endorsed, licensed, or approved by Disney.

So, is January 1, 2024 doomsday for Disney? No. Disney still retains copyright over newer iterations of Mickey such as the “Sorcerer’s Apprentice” Mickey from Fantasia (1940) as well as trademarks over Mickey as a brand identifier. People will still go to its theme parks, pay to see its movies, buy its merchandise. Its brand identity will remain intact.

In sum, yes, you can use Mickey in new creative works. There are some more complex peripheral legal issues, but here is your guide through them.

Cory Doctorow has an analysis of this upcoming milestone event in a recent post on his blog.

Previously:
(2023) What Happens When 'Steamboat Willie' Hits The Public Domain In 2024?

Original Submission

Freeman writes:

https://arstechnica.com/ai/2023/12/turing-test-on-steroids-chatbot-arena-crowdsources-ratings-for-45-ai-models/

As the AI landscape has expanded to include dozens of distinct large language models (LLMs), debates over which model provides the "best" answers for any given prompt have also proliferated (Ars has even delved into these kinds of debates a few times in recent months). For those looking for a more rigorous way of comparing various models, the folks over at the Large Model Systems Organization (LMSys) have set up Chatbot Arena, a platform for generating Elo-style rankings for LLMs based on a crowdsourced blind-testing website.

[...] Since its public launch back in May, LMSys says it has gathered over 130,000 blind pairwise ratings across 45 different models (as of early December). Those numbers seem poised to increase quickly after a recent positive review from OpenAI's Andrej Karpathy that has already led to what LMSys describes as "a super stress test" for its servers.

[...] Chatbot Arena's latest public leaderboard update shows a few proprietary models easily beating out a wide range of open-source alternatives. OpenAI's ChatGPT-4 Turbo leads the pack by a wide margin, with only an older GPT-4 model ("0314," which was discontinued in June) coming anywhere close on the ratings scale. But even months-old, defunct versions of GPT-3.5 Turbo outrank the highest-rated open-source models available in Chatbot Arena's testbed.

[...] Chatbot Arena users may also naturally gravitate towards certain types of prompts that favor certain types of models.

[...] To balance out these potential human biases, LMSys has also developed a completely automated ranking system called LLM Judge

[...] LMSys's academic paper on the subject finds that "strong LLM judges like GPT-4 can match both controlled and crowdsourced human preferences well, achieving over 80% agreement, the same level of agreement between humans." From those results, the organization suggests that having LLMs rank other LLMs provides "a scalable and explainable way to approximate human preferences, which are otherwise very expensive to obtain."

Original Submission

upstart writes:

A new report reveals that the world's largest publisher may be selling readers' intimate personal data to the highest bidder:

Three in ten Americans read digital books. Whether they're accessing online textbooks or checking out the latest bestselling e-book from the public library, the majority of these readers are subject to both the greed of Big Publishing and the priorities of Big Tech. In fact, Amazon's Kindle held 72% of the e-reader market in 2022. And if there's one thing we know about Big Tech companies like Amazon, their real product isn't the book. It's the user data.

Major publishers are giving Big Tech free rein to watch what you read and where, including books on sensitive topics, like if you check out a book on self care after an abortion. Worse, tech and publishing corporations are gobbling up data beyond your reading habits—today, there are no federal laws to stop them from surveilling people who read digital books across the entire internet.

Reader surveillance is a deeply intersectional threat, according to a congressional letter issued last week from a coalition of groups whose interests span civil rights, anti-surveillance, anti-book ban, racial justice, reproductive justice, LGBTQ+, immigrant, and antimonopoly. Our letter calls on federal lawmakers to investigate the harms of tech and publishing corporations' powerful hold over digital book access.

[...] In the age of artificial intelligence, the ability to analyze unfathomably detailed data on individual people, create reports and inferences about those people, and use the whole lot of it to train AI models is constantly improving. The incentives to exploit the data of readers are the strongest they have ever been.

Big Publishing is clearly seeing nothing but dollar signs as apps like Hoopla gobble up identity-linked data on readers—and so it would be natural to put our hope in public libraries, which view patron privacy as a fundamental right essential to a functioning democracy. In the human rights community, libraries' resistance against government surveillance under the Patriot Act is legendary.

Arthur T Knackerbracket has processed the following story:

Intel today is entering the "AI PC" era with the launch of its new Core Ultra notebook chips. Originally codenamed "Meteor Lake," these are Intel's first processors to include an NPU, or neural processing unit, for accelerating AI tasks. The launch comes a week after AMD revealed its upcoming Ryzen 8040 hardware, its second batch of chips to include NPUs. While Intel is playing a bit of AI catch-up, the Core Ultra chips still sound like a solid step forward — at least according to the company's benchmarks.

Intel claims the Core Ultra chips use up to 79 percent less power than AMD's last-gen Ryzen 7840U while idling in Windows, and they're also up to 11 percent faster than AMD's hardware for multithreaded tasks. Intel didn't have the upcoming Ryzen 8040 chips to test, but it'll be interesting to see how they both compare next year.

[...] The Core Ultra family launches with the Ultra 7 165H at the high end, offering 16 cores/22 threads (6P cores, 8 E cores and 2 low-power E cores and a 5GHz Max Turbo frequency. A beefier Ultra 9 185H will arrive in the first quarter of 2024 with a 5.1GHz Max Turbo speed, slightly faster GPU and higher power draw (45 watts, compared to the Ultra 7's 28 watts). As usual, there's also a lower-power "U" series of chips for the thinnest machines.

taylorvich writes:

https://phys.org/news/2023-12-neanderthals-morning-people.html

A new research paper finds that genetic material from Neanderthal ancestors may have contributed to the propensity of some people today to be "early risers," the sort of people who are more comfortable getting up and going to bed earlier.

The findings are published in the journal Genome Biology and Evolution.

All anatomically modern humans trace their origin to Africa around 300,000 years ago, where environmental factors shaped many of their biological features. Approximately 70,000 years ago, the ancestors of modern Eurasian humans began to migrate out to Eurasia, where they encountered diverse new environments, including higher latitudes with greater seasonal variation in daylight and temperature.

But other hominins, such as the Neanderthals and Denisovans, had lived in Eurasia for more than 400,000 years. These archaic hominins diverged from modern humans around 700,000 years ago, and as a result, our ancestors and archaic hominins evolved under different environmental conditions. This resulted in the accumulation of lineage-specific genetic variation and phenotypes. When humans came to Eurasia, they interbred with the archaic hominins on the continent, and this created the potential for humans to gain genetic variants already adapted to these new environments.

[...] The Eurasian environments where Neanderthals and Denisovans lived for several hundred thousand years are located at higher latitudes with more variable daylight times than the landscape where modern humans evolved before leaving Africa. Thus, the researchers explored whether there was genetic evidence for differences in the circadian clocks of Neanderthals and modern humans.

[...] This indicated that there were likely functional differences between in the circadian clocks in archaic hominins and modern humans. Since the ancestors of Eurasian modern humans and Neanderthals interbred, it was thus possible that some humans could have obtained circadian variants from Neanderthals.

Freeman writes:

https://arstechnica.com/tech-policy/2023/12/michael-cohens-lawyer-cited-three-fake-cases-in-possible-ai-fueled-screwup/

A lawyer representing Donald Trump's former attorney Michael Cohen filed a court brief that cited three cases that do not exist, according to a federal judge.

[...] "On November 29, 2023, David M. Schwartz, counsel of record for Defendant Michael Cohen, filed a motion for early termination of supervised release," US District Judge Jesse Furman wrote in an order to show cause yesterday. "In the letter brief, Mr. Cohen asserts that, '[a]s recently as 2022, there have been District Court decisions, affirmed by the Second Circuit Court, granting early termination of supervised release.'"

Schwartz's letter brief named "three such examples," citing United States v. Figueroa-Florez, United States v. Ortiz, and United States v. Amato. The brief provided case numbers, summaries, and ruling dates, but Furman concluded that the cases are fake.

[...] "If he is unable to do so, Mr. Schwartz shall, by the same date, show cause in writing why he should not be sanctioned pursuant to (1) Rule 11(b)(2) & (c) of the Federal Rules of Civil Procedure, (2) 28 U.S.C. § 1927, and (3) the inherent power of the Court for citing non-existent cases to the Court," Furman wrote.

Assuming he can't turn up those cases, Schwartz must also provide "a thorough explanation of how the motion came to cite cases that do not exist and what role, if any, Mr. Cohen played in drafting or reviewing the motion before it was filed."

[...] In Texas, one federal judge imposed a rule banning submissions written by artificial intelligence unless the AI's output is checked by a human. In another federal court in the District of Columbia, convicted rapper Prakazrel "Pras" Michel argued that he should get a new trial because his lawyer "used an experimental AI program to write" a "frivolous and ineffectual closing argument."

[...] In the Cohen case, Furman's order to show cause said that one of the three apparently bogus citations "refers to a page in the middle of a Fourth Circuit decision that has nothing to do with supervised release." A second "corresponds to a decision of the Board of Veterans Appeals," and the third "appears to correspond to nothing at all."

Original Submission

AnonTechie writes:

A few theories on why American productivity is on the decline.

The key to a nation's long-run prosperity is increased productivity. If workers can produce more in an hour, day, or week then they can collectively work less or enjoy more of the fruits of their labor: More pickleball courts and more time to play pickleball.

With all the astonishing improvements that we see on our computers and smartphones, it might seem that productivity is about to explode, that our concern will soon be how to distribute income and manage leisure when machines do all the work that people used to do. The reality is the opposite. The annual rate of increase of productivity in the United States averaged nearly 3% between 1870 and 1970 but has since slowed to less than 1%, according to data from the Bureau of Labor Statistics. That 2-percentage-point drop isn't much in the short run, but it is everything in the long run. If productivity continues to increase at 1% annual rate instead of 3%, workers will produce a third less output in 20 years, 50% less in 35 years.

A 2020 study published in the American Economic Review, the flagship journal of the American Economics Association, focused on research productivity because this is a key driver of overall productivity improvements.

They looked at specific industries and concluded that

Our robust finding is that research productivity is falling sharply everywhere we look. Taking the US aggregate number as representative, research productivity falls in half every 13 years: ideas are getting harder and harder to find. Put differently, just to sustain constant growth in GDP per person, the United States must double the amount of research effort every 13 years to offset the increased difficulty of finding new ideas.

The authors don't offer a compelling explanation for the drop in research productivity. We will suggest several possibilities. The title of the article, "Are Ideas Harder to Find?," suggests that productive ideas are increasingly scarce and illusive—that the low-ranking fruit have been harvested.

What are your views on this ??

Fast Company

Original Submission

Freeman writes:

https://arstechnica.com/information-technology/2023/12/dropbox-spooks-users-by-sending-data-to-openai-for-ai-search-features/

On Wednesday, news quickly spread on social media about a new enabled-by-default Dropbox setting that shares Dropbox data with OpenAI for an experimental AI-powered search feature, but Dropbox says data is only shared if the feature is actively being used. Dropbox says that user data shared with third-party AI partners isn't used to train AI models and is deleted within 30 days.

Even with assurances of data privacy laid out by Dropbox on an AI privacy FAQ page, the discovery that the setting had been enabled by default upset some Dropbox users. The setting was first noticed by writer Winifred Burton, who shared information about the Third-party AI setting through Bluesky on Tuesday, and frequent AI critic Karla Ortiz shared more information about it on X.

[...] In a statement to Ars Technica, a Dropbox representative said, "The third-party AI toggle is only turned on to give all eligible customers the opportunity to view our new AI features and functionality, like Dropbox AI. It does not enable customers to use these features without notice. Any features that use third-party AI offer disclosure of third-party use, and link to settings that they can manage. Only after a customer sees the third-party AI transparency banner and chooses to proceed with asking a question about a file, will that file be sent to a third-party to generate answers. Our customers are still in control of when and how they use these features."

Original Submission

Arthur T Knackerbracket has processed the following story:

One important tool in this work is the LLL algorithm, named after the researchers who published it in 1982 — Arjen Lenstra, Hendrik Lenstra Jr. and László Lovász. LLL, along with its many descendants, can break cryptographic schemes in some cases; studying how they behave helps researchers design systems that are less vulnerable to attack. And the algorithm's talents stretch beyond cryptography: It's also a useful tool in advanced mathematical arenas such as computational number theory.

Over the years, researchers have honed variants of LLL to make the approach more practical — but only up to a point. Now, a pair of cryptographers have built a new LLL-style algorithm with a significant boost in efficiency. The new technique, which won the Best Paper award at the 2023 International Cryptology Conference, widens the range of scenarios in which computer scientists and mathematicians can feasibly use LLL-like approaches.

"It was really exciting," said Chris Peikert, a cryptographer at the University of Michigan who was not involved in the paper. The tool has been the focus of study for decades, he said. "It's always nice when a target that has been worked on for so long ... shows that there's still surprises to be found."

[...] The new technique has already started to prove useful. Aurel Page, a mathematician with the French national research institute Inria, said that he and his team have put an adaptation of the algorithm to work on some computational number theory tasks.

LLL-style algorithms can also play a role in research related to lattice-based cryptography systems designed to remain secure even in a future with powerful quantum computers. They don't pose a threat to such systems, since taking them down requires finding shorter vectors than these algorithms can achieve. But the best attacks researchers know of use an LLL-style algorithm as a "basic building block," said Wessel van Woerden, a cryptographer at the University of Bordeaux. In practical experiments to study these attacks, that building block can slow everything down. Using the new tool, researchers may be able to expand the range of experiments they can run on the attack algorithms, offering a clearer picture of how they perform.

The new paper mentioned:
Ryan, K., Heninger, N. (2023). Fast Practical Lattice Reduction Through Iterated Compression. In: Handschuh, H., Lysyanskaya, A. (eds) Advances in Cryptology – CRYPTO 2023. CRYPTO 2023. Lecture Notes in Computer Science, vol 14083. Springer, Cham. https://doi.org/10.1007/978-3-031-38548-3_1

Original Submission

Freeman writes:

https://arstechnica.com/culture/2023/12/netflix-finally-reveals-viewing-data-across-its-entire-catalog/

Netflix, the streaming service that has been long criticized for a lack of transparency about how shows and films perform on its platform, will begin publishing a “comprehensive deep dive” into what its subscribers are watching twice a year.

Its first report, released on Tuesday, provided viewer data on more than 18,000 titles, representing a total of nearly 100 billion hours viewed, Netflix said. The Night Agent, a political thriller, was the most watched show on Netflix globally in the first half of 2023, with 812 million hours.

[...] “In the early days, it wasn’t really in our interest to be that transparent because we were building a new business and we needed room to learn. But we also didn’t want to provide road maps to future competitors.”

Original Submission

taylorvich writes:

https://newatlas.com/health-wellbeing/live-longer-calorie-restriction/

Scientists fed fruit flies a diet to make them extra plump. In their old age, the researchers put them on a diet and found remarkable results. If the findings transfer to humans, it might mean we can improve our health at any age by cutting calories.

While fruit flies might not seem like the closest human relatives, the diminutive insects actually share about 75% of our DNA, so they are frequently used in scientific studies. They also share a fair amount of the same metabolic pathways as humans, so studies relating to diet can be particularly useful for findings that might apply to human health.

For this go around, researchers at the University of Connecticut School of Medicine put a batch of male fruit flies on a high calorie diet to cause them to become obese. They also restricted the calorie intake of a different group of flies. The calorie-restricted flies were able to live to a maximum of 120 days, which is relatively old for the flies. The fat flies on the high-calorie diet only lived, on average, less than 80 days.

But what really surprised the researchers is that switching diets, even later in life, was able to extend the flies' lifespans. When young flies were switched from a high-calorie to a low-calorie diet at 20 days, they lived almost as long as the flies that had spent their whole lives eating less. Even more notably, when the fat flies were switched to a low-calorie diet at 50 or 60 days – a point at which most of their plump cohorts had already died – the researchers saw extended lifespans and improved metabolisms.

Original Submission

Arthur T Knackerbracket has processed the following story:

Google is about to launch its grand plan to block third-party cookies in Chrome that many websites use to track your activity across the web for profit.

Starting on January 4th, Google will start testing its new Tracking Protection feature that will eventually restrict website access to third-party cookies by default. It will come to a very small subset of Chrome users at the start, specifically to one percent of users globally. Afterward, Google plans to phase out the use of third-party cookies for all users in the second half of 2024.

[...] Google’s approach to cookie-free advertising sounds helpful to both privacy-focused users and the overall advertiser business in comparison to other web browsers that take more stone-walled approaches to block cross-site tracking. However, Google’s competitors and privacy advocates aren’t fully convinced about its cookie-replacing tech.

Meanwhile, regulators like the UK’s Competition and Markets Authority (CMA) is keeping an eye on Google’s new Tracking Protection to ensure it doesn’t give the company an unfair advantage in selling its own ads. With that in mind, Google says it’s hedging that H2 2024 target for turning the feature on globally in case it needs time to address “any remaining competition concerns.”

Original Submission

Arthur T Knackerbracket has processed the following story:

NASA's veteran Voyager 1 spacecraft has stopped transmitting engineering and science data back to Earth.

The issue appears to be with the Flight Data System (FDS), which is not communicating correctly with one of the probe's subsystems - the Telemetry Modulation Unit (TMU).

Rather than useful data, the TMU is simply transmitting a repeating pattern of ones and zeroes as if it were "stuck," according to NASA.

The FDS is responsible for collecting data from Voyager 1's science instruments as well as on the general health of the spacecraft. This is all packaged up and sent back to Earth by the TMU. Having worked through the possibilities, the Voyager team reckons the issue lies with the FDS.

"This past weekend the team tried to restart the FDS and return it to the state it was in before the issue began, but the spacecraft still isn't returning useable [sic] data," NASA says.

Engineers face multiple challenges. First, the Voyagers are famously old – dealing with their quirks involves poring through decades-old documents. Commands sent to the probes must be meticulously verified to prevent unintended consequences.

And then there is the sheer amount of time it takes to communicate with the Voyagers. A command from mission control on Earth will take more than 22 hours to reach Voyager 1. It can, therefore, take 45 hours to determine whether a given instruction worked as expected.

NASA reckons it will be several weeks of work for engineers to devise a new plan to deal with the problem.

Voyager 1 suffered a telemetry glitch in 2022 that resulted in garbled data on the probe's attitude being sent back to Earth. That issue was resolved by switching to a different computer. However, in that instance, Voyager 1 continued returning science data. The latest problem has stopped that.

The next time you find yourself having to diagnose and fix a problem remotely, remember that it could always be worse, even if sometimes it feels as though that misbehaving server is also 15 billion(*) miles away.

Given the limit imposed by the speed of light, a signal sent to Voyager 1 and immediately returned takes more than 16.6 hours. That's more than 2/3 of a *day*!

Original Submission