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Autonomous Vehicle International (a trade mag) is running the story, Aurora announces release of open-source autonomous driving data set to support advances within the sector, which describes a large vehicle sensor data set being made available to university researchers.

In partnership with the University of Toronto, Aurora Innovation has publicly released the Aurora Multi-Sensor Dataset, a large-scale multi-sensor data set with localization ground truth. The data set consists of rich metadata which includes semantic segmentation and a variety of weather patterns such as rain, snow, overcast cloud and sunshine, in addition to different times of day and varying traffic conditions.
[...]
By releasing the data set to the academic sector, Aurora aims to contribute "meaningful engineering research and development" to support progress within the autonomous systems field. Additionally, due to the size and the diversity of Aurora's Multi-Sensor Datatset, it can be used for 3D reconstruction, HD map construction, map compression and more.

The data set was captured by Uber Advanced Technologies Group (ATG) in the metropolitan area of Pittsburgh, USA between January 2017 and February 2018. Aurora acquired the data set in January 2021. Uber ATG used a 64-beam Velodyne HDL-64E lidar sensor and seven 1920×1200-pixel resolution cameras, in addition to a forward-facing stereo pair and five wide-angle lenses providing a 360-degree view around the vehicle to capture the data.

The dataset is available at https://registry.opendata.aws/aurora_msds/ and the license information on that page is,

License
This data is intended for non-commercial academic use only. It is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Documentation
A third-party development kit authored by Andrei Bârsan of the University of Toronto, made available under the MIT License, can be found here: https://github.com/pit30m/pit30m. Aurora makes no representations as to the functionality or performance of the dev-kit.

It's Pittsburgh, they have below freezing temps, the roads develop potholes, construction changes the roads and so on. My guess, while this dataset is large and rich, by now it's also less than accurate. Still, better than nothing for grant-starved university researchers.

Original Submission

looorg writes:

Taurine deficiency as a driver of aging: Lab mice that got taurine supplements lived 10-12% longer lives. So all the kids that are pounding Red Bull (and all the other energy-drinks) might live longer if their hearts don't explode from over-consumption.

Taurine May Be a Key to Longer and Healthier Life:

A deficiency of taurine—a nutrient produced in the body and found in many foods—is a driver of aging in animals, according to a new study led by Columbia researchers and involving dozens of aging researchers around the world.

The same study also found that taurine supplements can slow down the aging process in worms, mice, and monkeys and can even extend the healthy lifespans of middle-aged mice by up to 12%.

[...] “For the last 25 years, scientists have been trying to find factors that not only let us live longer, but also increase healthspan, the time we remain healthy in our old age,” says the study’s leader, Vijay Yadav, PhD, assistant professor of genetics & development at Columbia University Vagelos College of Physicians and Surgeons.

“This study suggests that taurine could be an elixir of life within us that helps us live longer and healthier lives.”

Journal Reference:
Parminder Singh et. al. Taurine deficiency as a driver of aging, Science (DOI: 10.1126/science.abn9257)

Original Submission

upstart writes:

US sanctions ignite booming black market for Nvidia AI chips in China:

What do you do when US sanctions prevent the purchase of high-performance Nvidia AI GPUs? In China, universities and businesses are turning to underground dealers to secure these chips, and paying a premium to get their hands on them.

In September last year, the US further tightened sanctions against China by instructing Nvidia and AMD to stop selling their high-performance AI-focused GPUs to the country (and Russia), a restriction aimed at preventing the US companies' top hardware from being used by or diverted to military users and finding their way into the nation's supercomputers.

The sanctions mean that China cannot import Nvidia A100 or H100 GPUs, while AMD's MI250 Instinct card is also prohibited, leaving less powerful options such as the MI100 accelerator and the Nvidia A800, which went into production in Q3 last year as another alternative to the A100 GPU. The chip has an interconnect speed of 400 GB/s, down from the A100's 600 GB/s.

Reuters reports that this year's generative AI boom led by OpenAI's ChatGPT has seen demand for Nvidia's high-end chips skyrocket in China. That's led to an underground market in the Asian nation, where everyone from startups to universities is paying large premiums to secure these GPUs - buying or selling the chips within China is not illegal.

Reuters visited the famous Huaqiangbei electronics area in the southern Chinese city of Shenzhen where two vendors told reporters they could provide small numbers of A100 chips for $20,000 each, double the usual price of around $10,000.

A Hong Kong startup founder said he experienced the same thing when quoted $19,150 each for two to four A100 cards, which were needed to run its latest AI models. In addition to paying much more than their MSRP, these cards lack any kind of warranty or support.

Original Submission

So, just keeping some updates here.

Infrastructure wise, we've got all the base Docker images, and compose files put together to the point that it's fairly easy to simply run "docker compose up", and get a working rehash installation with the infrastructure playbook. We've got it working on staging.soylentnews.org, albeit with some hiccups.

This also includes all auxiliary services needed for both sides, as well as things like IRC server and necessary bots are included. I had to spend quite a few hours dealing with the remains of the MySQL cluster install, but I managed to recover the soylentdev database from the NDB backups I took before decommissioning the old cluster. Dev.soylentnews.org is back online as of writing.

mechanicjay has set a PR for getting rehash running on Apache 2.4, which I've spent some time getting working in a Docker branch, but haven't reviewed in-depth. I've mostly been working on getting everything else rebuilt as is before introducing a potentially unstable update into the stack. My understanding is there's some dependency problems, but just getting index.pl and such rendering is a big step forward.

So in short, the technical aspects of the site are at least getting worked on. I'll cover the business side of it below the fold.

The Reddit blackout, explained: Why thousands of subreddits are protesting third-party app charges

liar writes:

The Reddit blackout, explained: Why thousands of subreddits are protesting third-party app charges:

Thousands of Reddit discussion forums have gone dark this week to protest a new policy that will charge some third-party apps to access data on the site, leading to worries about content moderation and accessibility.

"Reddit is killing third-party applications (and itself)," multiple subreddits wrote in posts seen on the platform's homepage this week.

The new fees are part of broader changes to Reddit's API, or application programming interface, that the company announced recently.

[...] Nearly 9,000 subreddits went dark this week and more than 4,000 remained dark on Friday, including communities with tens of millions of subscribers like r/music and r/videos — according to a tracker of the boycott. While some returned to their public settings after 48 hours, others say they will stay private indefinitely, until Reddit meets their demands.

hubie writes:

Language used for app tracking privacy settings causes consumer confusion:

Privacy and security features that aim to give consumers more control over the sharing of their data by smartphone apps are widely misunderstood, shows new research from the University of Bath's School of Management.

43 per cent of phone users in the study were confused or unclear about what app tracking means. People commonly mistook the purpose of tracking, thinking that it was intrinsic to the app function, or that it would provide a better user experience.

App tracking is used by companies to deliver targeted advertising to smartphone users.

[...] The most common misapprehension (24 per cent) was that tracking refers to sharing the physical location of the device - rather than tracing the use of apps and websites. People thought they needed to accept tracking for food delivery and collection services, such as Deliveroo, or for health and fitness apps, because they believed their location was integral to the functioning of the app.

While just over half of participants (51 per cent) said they were concerned about privacy or security – including security of their data after it had been collected - analysis showed no association between their concern for privacy in their daily life and a lower rate of tracking acceptance.

[...] "Some of the confusion is likely to be due to lack of clarity in wording chosen by companies in the tracking prompts, which are easy to misinterpret. For example, when ASOS said 'We'll use your data to give you a more personalised ASOS experience and to make our app even more amazing' it's probably no surprise that people thought they were opting for additional functionality rather than just more relevant adverts."

[...] Other misconceptions included believing that consenting to sharing for health apps (such as period tracking apps) would mean private data being shared, or that denying tracking would remove adverts from the app.

[...] "While people are now familiar with the benefits of having PIN numbers and facial recognition to protect our devices, more work needs to be done so people can make transparent decisions about what other data is used for in the digital age."

Journal Reference:
Hannah J Hutton and David A Ellis, Exploring User Motivations Behind iOS App Tracking Transparency Decisions, CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023. https://doi.org/10.1145/3544548.3580654

Original Submission

hubie writes:

Here's why it matters to you:

New University of Colorado Boulder research shows the number of farms globally will shrink in half as the size of the average existing farms doubles by the end of the 21st century, posing significant risks to the world's food systems.

Published today in the journal Nature Sustainability, the study is the first to track the number and size of farms year-over-year, from the 1960s and projecting through 2100.

The study shows that even rural, farm-dependent communities in Africa and Asia will experience a drop in the number of operating farms.

[...] His analysis found that the number of farms around the world would drop from 616 million in 2020 to 272 million in 2100. A key reason: As a country's economy grows, more people migrate to urban areas, leaving fewer people in rural areas to tend the land.

A decline in the number of farms and an increase in farm size has been happening in the United States and Western Europe for decades. The most recent data from the U.S. Department of Agriculture indicates there were 200,000 fewer farms in 2022 than in 2007.

canopic jug writes:

Educator Lionel Dricot explores the historical prescience of Richard Stallman's (RMS) warnings and prophecies which have been spot on since the beginning, including his proposed solutions. Dricot points out that the problem with acceptance of the solutions is not with RMS or the Free Software Foundation (FSF), instead the problem is us and that we didn't listen. In addition to the Four Freedoms, he points out one obligation which has been taken for granted and left unspoken until now: the obligation to prevent privatization of the Commons.

There was one weakness in RMS theory: copyleft was not part of the four freedoms he theorised. Business-compatible licenses like BSD/MIT or even public domain are "Free Software" because they respect the four freedoms.

But they can be privatised.

And that's the whole point. For the last 30 years, businesses and proponents of Open Source, including Linus Torvalds, have been decrying the GPL because of the essential right of "doing business" aka "privatising the common".

They succeeded so much that the essential mission of the FSF to guarantee the common was seen as "useless" or, worse, "reactionary". What was the work of the FSF? The most important thing is that they proof-bombed the GPL against weaknesses found later. They literally patched vulnerabilities. First the GPLv3, to fight "Tivoisation" and then AGPL, to counteract proprietary online services running on free software but taking away freedom of users.

upstart writes:

Quantum weirdness applies to sound as well as to light and atomic particles:

You can't divide the indivisible, unless you use quantum mechanics. Physicists have now turned to quantum effects to split phonons, the smallest bits of sound, researchers report in the June 9 Science.

It's a breakthrough that mirrors the sort of quantum weirdness that's typically demonstrated with light or tiny particles like electrons and atoms (SN: 7/27/22). The achievement may one day lead to sound-based versions of quantum computers or extremely sensitive measuring devices. For now, it shows that mind-bending quantum weirdness applies to sound as well as it does to light.

"There was no one that had really explored that," says engineering physicist Andrew Cleland of the University of Chicago. Doing so allows researchers "to draw parallels between sound waves and light."

Phonons have much in common with photons, the tiniest chunks of light. Turning down the volume of a sound is the same as dialing back the number of phonons, much like dimming a light reduces the number of photons. The very quietest sounds of all consist of individual — and indivisible — phonons.

Unlike photons, which can travel through empty space, phonons need a medium such as air or water — or in the case of the new study, the surface of an elastic material. "What's really kind of, in my mind, amazing about that is that these sound waves [carry] a very, very small amount of energy, because it's a single quantum," Cleland says. "But it involves the motion of a quadrillion atoms that are all working together to [transmit] this sound wave."

upstart writes:

AI is going to eat itself: Experiment shows people training bots are using bots

Workers hired via crowdsource services like Amazon Mechanical Turk are using large language models to complete their tasks – which could have negative knock-on effects on AI models in the future.

Data is critical to AI. Developers need clean, high-quality datasets to build machine learning systems that are accurate and reliable. Compiling valuable, top-notch data, however, can be tedious. Companies often turn to third party platforms such as Amazon Mechanical Turk to instruct pools of cheap workers to perform repetitive tasks – such as labeling objects, describing situations, transcribing passages, and annotating text.

Their output can be cleaned up and fed into a model to train it to reproduce that work on a much larger, automated scale.

AI models are thus built on the backs of human labor: people toiling away, providing mountains of training examples for AI systems that corporations can use to make billions of dollars.

But an experiment conducted by researchers at the École polytechnique fédérale de Lausanne (EPFL) in Switzerland has concluded that these crowdsourced workers are using AI systems – such as OpenAI's chatbot ChatGPT – to perform odd jobs online.

Training a model on its own output is not recommended. We could see AI models being trained on data generated not by people, but by other AI models – perhaps even the same models. That could lead to disastrous output quality, more bias, and other unwanted effects.

fliptop writes:

MSI's latest PSU series aims to mitigate user error with one minor change:

MSI has launched its MAG GL power supplies, showcased at Computex 2023. These new power supplies are PCIe 5.0 compatible and are compliant with the ATX 3.0 standard. In addition to meeting new spec guidelines, they have the bonus of featuring yellow pin connectors on both ends of the cable. The idea behind the subtle change is to make it easier for users to see whether or not the cable is completely inserted, preventing a few common hardware failures, such as the 16-pin connector meltdowns on the GeForce RTX 4090, one of the best graphics cards.

According to MSI, users frequently reported problems with burnt power supply connectors when using them with newer high-end GPUs. Upon investigation, the team realized one of the most common causes of this issue was improperly connected cables. With the new yellow pin connectors, users can easily see whether or not the cable has been fully inserted when assembling their PC.

The new MAG GL series PSUs are designed to handle Nvidia GeForce RTX 40-series graphics cards. They are also compatible with Intel's Power Supply Design Guide (PSDG) ATX 3.0 standard. This support only waivers when the power supply isn't correctly installed, which is always necessary, especially given the latest hardware demands.

Previously: Another 16-pin RTX 4090 Power Adapter Has Melted, but From the PSU Side This Time

Original Submission

takyon writes:

Submarine on expedition to Titanic wreck missing with 5 aboard; "search and rescue operation" underway

A search and rescue mission was underway Monday for a submarine that went missing in the North Atlantic on an expedition to explore the wreckage of the Titanic. Lt. Jordan Hart of the U.S. Coast Guard in Boston first confirmed to CBS News that personnel were "currently undergoing a search and rescue operation" when asked about the rescue efforts off the coast of Newfoundland.

At a news conference Monday afternoon, Rear Admiral John Mauger confirmed that five people were on board. A Coast Guard official identified them as an operator and four mission specialists — a term the company uses for its passengers.

The vessel submerged on a dive Sunday morning, and the crew of the Polar Prince — the ship that ferried the submersible and expedition members to the dive site — "lost contact with them approximately 1 hour and 45 minutes into the vessel's dive," the Coast Guard said in a tweet.

Original Submission

upstart writes:

Is the US trying to kill crypto?:

[...] The sector was already under pressure, after prices of virtual currencies collapsed last year. Further damage came from the meltdown of several high-profile firms, including FTX, run by the so-called "Crypto King" Sam Bankman-Fried, whom prosecutors have accused of conducting "one of the biggest financial frauds" in US history.

Jolted by the turmoil, US regulators stepped up their policing of the sector, which authorities say has been on notice since at least 2017 that their activity runs afoul of US financial rules intended to protect investors.

The campaign has yielded a steady drumbeat of charges against crypto firms and executives, alleging violations ranging from failing to register properly with authorities and provide adequate disclosure of their activity to, in some cases, more damaging claims such as mishandling of consumer funds and fraud.

[...] Gary Gensler, the chairman of the Securities and Exchange Commission, defended the moves this month, comparing the state of affairs in the industry to the 1920s, before the US put in place many of the rules in question: "Hucksters. Fraudsters. Scam artists. Ponzi schemes. The public left in line at the bankruptcy court."

[...] Critics accuse the SEC under Mr Gensler of hostile "regulation by enforcement" aimed at boosting his own political profile.

[...] Whether the SEC's moves could actually kill the industry - in which by at least one estimate one in every six Americans has invested - is another question.

upstart writes:

IBM Says It's Made a Big Breakthrough in Quantum Computing:

[...] Scientists at IBM say they've developed a method to manage the unreliability inherent in quantum processors, possibly providing a long-awaited breakthrough toward making quantum computers as practical as conventional ones — or even moreso.

The advancement, detailed in a study published in the journal Nature, comes nearly four years after Google eagerly declared "quantum supremacy" when its scientists claimed they demonstrated that their quantum computer could outperform a classical one.

Though still a milestone, those claims of "quantum supremacy" didn't exactly pan out. Google's experiment was criticized as having no real world merit, and it wasn't long until other experiments demonstrated classical supercomputers could still outpace Google's.

IBM's researchers, though, sound confident that this time the gains are for real.

"We're entering this phase of quantum computing that I call utility," Jay Gambetta, an IBM Fellow and vice president of IBM Quantum Research, told The New York Times. "The era of utility."

[...] These spooky principles allow for a far smaller number of qubits to rival the processing power of regular bits, which can only be a binary one or zero. Sounds great, but at the quantum level, particles eerily exist at uncertain states, arising in a pesky randomness known as quantum noise.

Managing this noise is key to getting practical results from a quantum computer. A slight change in temperature, for example, could cause a qubit to change state or lose superposition.

owl writes:

https://fanael.github.io/is-x86-risc-internally.html

There is a widespread idea that modern high-performance x86 processors work by decoding the "complex" x86 instructions into "simple" RISC-like instructions that the rest of the pipeline then operates on. But how close is this idea to how the processors actually work internally?

To answer this question, let's analyze how different x86 processors, ranging from the first "modern" Intel microarchitecture, P6, to their current designs, handle the following simple loop (the code is 32-bit just to allow us to discuss very old x86 processors):

x86 assembly
.loop:
add [edx], eax
add edx, 4
sub eax, 1
jnz .loop

Original Submission