DGIST Professor Yoonkyu Lee’s research team used intense light on the surface of a copper wire to synthesize graphene, thereby increasing the production rate and lowering the production cost of the high-quality transparent-flexible electrode materials and consequently enabling its mass production. The results were published in the February 23 issue of Nano Energy.
This technology is applicable to various 2D materials, and its applicability can be extended to the synthesis of various metal-2D material nanowires.
The research team used copper-graphene nanowires to implement high-performance transparent-flexible electronic devices such as transparent-flexible electrodes, transparent supercapacitors and transparent heaters and to thereby demonstrate the commercial viability of this material.
DGIST Professor Yoonkyu Lee said, “We developed a method of mass-producing at a low production cost the next-generation transparent-flexible electrode material based on high-quality copper-graphene nanowires. In the future, we expect that this technology will contribute to the production of core electrode materials for high-performance transparent-flexible electronic devices, semitransparent solar cells, or transparent displays.”
More information: Jongyoun Kim et al, Ultrastable 2D material-wrapped copper nanowires for high-performance flexible and transparent energy devices, Nano Energy (2022). DOI: 10.1016/j.nanoen.2022.108067
Italy’s privacy watchdog said Friday it had blocked the controversial robot ChatGPT, saying the artificial intelligence app did not respect user data and could not verify users’ age.
The decision “with immediate effect” will result in “the temporary limitation of the processing of Italian user data vis-a-vis OpenAI”, the Italian Data Protection Authority said.
The agency has launched an investigation.
[…]
The watchdog said that on March 20, the app experienced a data breach involving user conversations and payment information.
It said there was no legal basis to justify “the mass collection and storage of personal data for the purpose of ‘training’ the algorithms underlying the operation of the platform”.
It also said that since there was no way to verify the age of users, the app “exposes minors to absolutely unsuitable answers compared to their degree of development and awareness.”
It said the company had 20 days to respond how it would address the watchdog’s concerns, under penalty of a 20-million-euro ($21.7-million) fine, or up to 4 percent of annual revenues.
I am pretty sure none of the search engines verify age and store user data (ok duckduckgo is an exception) or give answers that may “expose” the little snowflake “minors to absolutely unsuitable answers compared to their degree of development and awareness.”
There is a race on to catch up to OpenAI and people are obviously losing, so crushing OpenAI is the way to go.
[…] The software engineers behind these systems are employees of NTC Vulkan. On the surface, it looks like a run-of-the-mill cybersecurity consultancy. However, a leak of secret files from the company has exposed its work bolstering Vladimir Putin’s cyberwarfare capabilities.
Thousands of pages of secret documents reveal how Vulkan’s engineers have worked for Russian military and intelligence agencies to support hacking operations, train operatives before attacks on national infrastructure, spread disinformation and control sections of the internet.
The company’s work is linked to the federal security service or FSB, the domestic spy agency; the operational and intelligence divisions of the armed forces, known as the GOU and GRU; and the SVR, Russia’s foreign intelligence organisation.
A diagram showing a Vulkan hacking reconnaissance system codenamed Scan, developed since 2018.
One document links a Vulkan cyber-attack tool with the notorious hacking group Sandworm, which the US government said twice caused blackouts in Ukraine, disrupted the Olympics in South Korea and launched NotPetya, the most economically destructive malware in history. Codenamed Scan-V, it scours the internet for vulnerabilities, which are then stored for use in future cyber-attacks.
Another system, known as Amezit, amounts to a blueprint for surveilling and controlling the internet in regions under Russia’s command, and also enables disinformation via fake social media profiles. A third Vulkan-built system – Crystal-2V – is a training program for cyber-operatives in the methods required to bring down rail, air and sea infrastructure. A file explaining the software states: “The level of secrecy of processed and stored information in the product is ‘Top Secret’.”
The Vulkan files, which date from 2016 to 2021, were leaked by an anonymous whistleblower angered by Russia’s war in Ukraine. Such leaks from Moscow are extremely rare. Days after the invasion in February last year, the source approached the German newspaper Süddeutsche Zeitung and said the GRU and FSB “hide behind” Vulkan.
[…]
Five western intelligence agencies confirmed the Vulkan files appear to be authentic. The company and the Kremlin did not respond to multiple requests for comment.
The leak contains emails, internal documents, project plans, budgets and contracts. They offer insight into the Kremlin’s sweeping efforts in the cyber-realm, at a time when it is pursuing a brutal war against Ukraine. It is not known whether the tools built by Vulkan have been used for real-world attacks, in Ukraine or elsewhere.
[…]
Some documents in the leak contain what appear to be illustrative examples of potential targets. One contains a map showing dots across the US. Another contains the details of a nuclear power station in Switzerland.
A map of the US found in the leaked Vulkan files as part of the multi-faceted Amezit system.
One document shows engineers recommending Russia add to its own capabilities by using hacking tools stolen in 2016 from the US National Security Agency and posted online.
John Hultquist, the vice-president of intelligence analysis at the cybersecurity firm Mandiant, which reviewed selections of the material at the request of the consortium, said: “These documents suggest that Russia sees attacks on civilian critical infrastructure and social media manipulation as one and the same mission, which is essentially an attack on the enemy’s will to fight.”
[…]
One of Vulkan’s most far-reaching projects was carried out with the blessing of the Kremlin’s most infamous unit of cyberwarriors, known as Sandworm. According to US prosecutors and western governments, over the past decade Sandworm has been responsible for hacking operations on an astonishing scale. It has carried out numerous malign acts: political manipulation, cyber-sabotage, election interference, dumping of emails and leaking.
Sandworm disabled Ukraine’s power grid in 2015. The following year it took part in Russia’s brazen operation to derail the US presidential election. Two of its operatives were indicted for distributing emails stolen from Hillary Clinton’s Democrats using a fake persona, Guccifer 2.0. Then in 2017 Sandworm purloined further data in an attempt to influence the outcome of the French presidential vote, the US says.
That same year the unit unleashed the most consequential cyber-attack in history. Operatives used a bespoke piece of malware called NotPetya. Beginning in Ukraine, NotPetya rapidly spread across the globe. It knocked offline shipping firms, hospitals, postal systems and pharmaceutical manufacturers – a digital onslaught that spilled over from the virtual into the physical world.
[…]
Hacking groups such as Sandworm penetrate computer systems by first looking for weak spots. Scan-V supports that process, conducting automated reconnaissance of potential targets around the world in a hunt for potentially vulnerable servers and network devices. The intelligence is then stored in a data repository, giving hackers an automated means of identifying targets.
[…]
One part of Amezit is domestic-facing, allowing operatives to hijack and take control of the internet if unrest breaks out in a Russian region, or the country gains a stronghold over territory in a rival nation state, such as Ukraine. Internet traffic deemed to be politically harmful can be removed before it has a chance to spread.
A 387-page internal document explains how Amezit works. The military needs physical access to hardware, such as mobile phone towers, and to wireless communications. Once they control transmission, traffic can be intercepted. Military spies can identify people browsing the web, see what they are accessing online, and track information that users are sharing.
[…]
the firm developed a bulk collection program for the FSB called Fraction. It combs sites such as Facebook or Odnoklassniki – the Russian equivalent – looking for key words. The aim is to identify potential opposition figures from open source data.
[…]
This Amezit sub-system allows the Russian military to carry out large-scale covert disinformation operations on social media and across the internet, through the creation of accounts that resemble real people online, or avatars. The avatars have names and stolen personal photos, which are then cultivated over months to curate a realistic digital footprint.
The leak contains screenshots of fake Twitter accounts and hashtags used by the Russian military from 2014 until earlier this year. They spread disinformation, including a conspiracy theory about Hillary Clinton and a denial that Russia’s bombing of Syria killed civilians. Following the invasion of Ukraine, one Vulkan-linked fake Twitter account posted: “Excellent leader #Putin”.
A tweet from a fake social media account linked to Vulkan.
Another Vulkan-developed project linked to Amezit is far more threatening. Codenamed Crystal-2V, it is a training platform for Russian cyber-operatives. Capable of allowing simultaneous use by up to 30 trainees, it appears to simulate attacks against a range of essential national infrastructure targets: railway lines, electricity stations, airports, waterways, ports and industrial control systems.
A public challenge could put a temporary stop to the deployment of ChatGPT and similar AI systems. The nonprofit research organization Center for AI and Digital Policy (CAIDP) has filed a complaint with the Federal Trade Commission (FTC) alleging that OpenAI is violating the FTC Act through its releases of large language AI models like GPT-4. That model is “biased, deceptive” and threatens both privacy and public safety, CAIDP claims. Likewise, it supposedly fails to meet Commission guidelines calling for AI to be transparent, fair and easy to explain.
The Center wants the FTC to investigate OpenAI and suspend future releases of large language models until they meet the agency’s guidelines. The researchers want OpenAI to require independent reviews of GPT products and services before they launch. CAIDP also hopes the FTC will create an incident reporting system and formal standards for AI generators.
We’ve asked OpenAI for comment. The FTC has declined to comment. CAIDP president Marc Rotenberg was among those who signed an open letter demanding that OpenAI and other AI researchers pause work for six months to give time for ethics discussions. OpenAI founder Elon Musk also signed the letter.
Critics of ChatGPT, Google Bard and similar models have warned of problematic output, including inaccurate statements, hate speech and bias. Users also can’t repeat results, CAIDP says. The Center points out that OpenAI itself warns AI can “reinforce” ideas whether or not they’re true. While upgrades like GPT-4 are more reliable, there’s a concern people may rely on the AI without double-checking its content.
There’s no guarantee the FTC will act on the complaint. If it does set requirements, though, the move would affect development across the AI industry. Companies would have to wait for assessments, and might face more repercussions if their models fail to meet the Commission’s standards. While this might improve accountability, it could also slow the currently rapid pace of AI development.
Every LLN AI being released right now is pretty clear that it’s not a single source of truth, that mistakes will be made and that you need to check the output yourself. The signing of the letter to stop AI development smacks of people who are so far behind in the race wanting to quietly catch up until the moratorium is lifted and this action sounds a lot like this organisation being in someone’s pocket.
Virgin Orbit’s days of slinging satellites into space aboard aircraft-launched rockets have come to an end Thursday. After six years in business, Virgin’s satellite launch subsidiary has announced via SEC filing that it does not have the funding to continue operations and will be shuttering for “the foreseeable future,” per CNBC. Nearly 90 percent of Virgin Orbit’s employees — 675 people in total — will be laid off immediately.
Virgin Orbit was founded in 2017 for the purpose of developing and commercializing LauncherOne, a satellite launch system fitted under a modified 747 airliner, dubbed Cosmic Girl. The system was designed to put 500 pounds of cubesats into Low Earth Orbit by firing them in a rocket from said airliner flying at an altitude of 30,000 – 50,000 feet. Despite a string of early successes — both in terms of development milestones and expanding service contracts with the UK military, LauncherOne’s first official test in May of 2020 failed to deliver its simulated payload into orbit.
In all, Virgin Orbit made six total flights between 2020 and 2023, only four successfully. The most recent attempt was dubbed the Start Me Up event and was supposed to mark the first commercial space launch from UK soil. Despite the rocket successfully separating from its parent aircraft, an upper stage “anomaly” prevented the rocket’s payload from entering orbit. It was later determined that a $100 fuel filter had failed and resulted in the fault.
As TechCrunch points out, Virgin Group founder, Sir Richard Branson, “threw upwards of $55 million to the sinking space company,” in recent months but Start Me Up’s embarrassing failure turned out to be the final straw. On March 16th, Virgin Orbit announced an “operational pause” and worker furlough for its roughly 750 employees as company leadership scrambled to find new funding sources. The company extended the furlough two weeks later and called it quits on Thursday.
“Unfortunately, we’ve not been able to secure the funding to provide a clear path for this company,” Virgin CEO Dan Hart said in an all-hands call obtained by CNBC. “We have no choice but to implement immediate, dramatic and extremely painful changes.”
Impacted employees will reportedly receive severance packages, according to Hart, including a cash payment, continued benefits and a “direct pipeline” to Virgin Galactic’s hiring department. Virgin Orbit’s two top executives will also receive “golden parachute” severances which were approved by the company’s board, conveniently, back in mid-March right when the furloughs first took effect.
Several months ago, Socket, which makes a freemium security scanner for JavaScript and Python projects, connected OpenAI’s ChatGPT model (and more recently its GPT-4 model) to its internal threat feed.
The results, according to CEO Feross Aboukhadijeh, were surprisingly good. “It worked way better than expected,” he told The Register in an email. “Now I’m sitting on a couple hundred vulnerabilities and malware packages and we’re rushing to report them as quick as we can.”
Socket’s scanner was designed to detect supply chain attacks. Available as a GitHub app or a command line tool, it scans JavaScript and Python projects in an effort to determine whether any of the many packages that may have been imported from the npm or PyPI registries contain malicious code.
Aboukhadijeh said Socket has confirmed 227 vulnerabilities, all using ChatGPT. The vulnerabilities fall into different categories and don’t share common characteristics.
The Register was provided with numerous examples of published packages that exhibited malicious behavior or unsafe practices, including: information exfiltration, SQL injection, hardcoded credentials, potential privilege escalation, and backdoors.
We were asked not to share several examples as they have yet to be removed, but here’s one that has already been dealt with.
mathjs-min“Socket reported this to npm and it has been removed,” said Aboukhadijeh. “This was a pretty nasty one.”
AI analysis: “The script contains a discord token grabber function which is a serious security risk. It steals user tokens and sends them to an external server. This is malicious behavior.”
“There are some interesting effects as well, such as things that a human might be persuaded of but the AI is marking as a risk,” Aboukhadijeh added.
“These decisions are somewhat subjective, but the AI is not dissuaded by comments claiming that a dangerous piece of code is not malicious in nature. The AI even includes a humorous comment indicating that it doesn’t trust the inline comment.”
Example trello-enterprise
AI analysis: “The script collects information like hostname, username, home directory, and current working directory and sends it to a remote server. While the author claims it is for bug bounty purposes, this behavior can still pose a privacy risk. The script also contains a blocking operation that can cause performance issues or unresponsiveness.”
Aboukhadijeh explained that the software packages at these registries are vast and it’s difficult to craft rules that thoroughly plumb the nuances of every file, script, and bit of configuration data. Rules tend to be fragile and often produce too much detail or miss things a savvy human reviewer would catch.
Applying human analysis to the entire corpus of a package registry (~1.3 million for npm and ~450,000 for PyPI) just isn’t feasible, but machine learning models can pick up some of the slack by helping human reviewers focus on the more dubious code modules.
“Socket is analyzing every npm and PyPI package with AI-based source code analysis using ChatGPT,” said Aboukhadijeh.
“When it finds something problematic in a package, we flag it for review and ask ChatGPT to briefly explain its findings. Like all AI-based tooling, this may produce some false positives, and we are not enabling this as a blocking issue until we gather more feedback on the feature.”
Aboukhadijeh provided The Register with a sample report from its ChatGPT helper that identifies risky, though not conclusively malicious behavior. In this instance, the machine learning model offered this assessment, “This script collects sensitive information about the user’s system, including username, hostname, DNS servers, and package information, and sends it to an external server.”
Screenshot of ChatGPT report for Socket security scanner – Click to enlarge
What a ChatGPT-based Socket advisory looks like … Click to enlarge
According to Aboukhadijeh, Socket was designed to help developers make informed decisions about risk in a way that doesn’t interfere with their work. So raising the alarm about every install script – a common attack vector – can create too much noise. Analysis of these scripts using a large language model dials the alarm bell down and helps developers recognize real problems. And these models are becoming more capable.
What does a stressed plant sound like? A bit like bubble-wrap being popped. Researchers in Israel report in the journal Cell on March 30 that tomato and tobacco plants that are stressed—from dehydration or having their stems severed—emit sounds that are comparable in volume to normal human conversation. The frequency of these noises is too high for our ears to detect, but they can probably be heard by insects, other mammals, and possibly other plants.
“Even in a quiet field, there are actually sounds that we don’t hear, and those sounds carry information,” says senior author Lilach Hadany, an evolutionary biologist and theoretician at Tel Aviv University. “There are animals that can hear these sounds, so there is the possibility that a lot of acoustic interaction is occurring.”
Although ultrasonic vibrations have been recorded from plants before, this is the first evidence that they are airborne, a fact that makes them more relevant for other organisms in the environment. “Plants interact with insects and other animals all the time, and many of these organisms use sound for communication, so it would be very suboptimal for plants to not use sound at all,” says Hadany.
The researchers used microphones to record healthy and stressed tomato and tobacco plants, first in a soundproofed acoustic chamber and then in a noisier greenhouse environment. They stressed the plants via two methods: by not watering them for several days and by cutting their stems. After recording the plants, the researchers trained a machine-learning algorithm to differentiate between unstressed plants, thirsty plants, and cut plants.
The team found that stressed plants emit more sounds than unstressed plants. The plant sounds resemble pops or clicks, and a single stressed plant emits around 30–50 of these clicks per hour at seemingly random intervals, but unstressed plants emit far fewer sounds. “When tomatoes are not stressed at all, they are very quiet,” says Hadany.
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An audio recording of plant sounds. The frequency was lowered so that it is audible to human ears. Credit: Khait et al.
Water-stressed plants began emitting noises before they were visibly dehydrated, and the frequency of sounds peaked after five days with no water before decreasing again as the plants dried up completely. The types of sound emitted differed with the cause of stress. The machine-learning algorithm was able to accurately differentiate between dehydration and stress from cutting and could also discern whether the sounds came from a tomato or tobacco plant.
Although the study focused on tomato and tobacco plants because of their ease to grow and standardize in the laboratory, the research team also recorded a variety of other plant species. “We found that many plants—corn, wheat, grape, and cactus plants, for example—emit sounds when they are stressed,” says Hadany.
A photo of a cactus being recorded. Credit: Itzhak Khait
The exact mechanism behind these noises is unclear, but the researchers suggest that it might be due to the formation and bursting of air bubbles in the plant’s vascular system, a process called cavitation.
Whether or not the plants are producing these sounds in order to communicate with other organisms is also unclear, but the fact that these sounds exist has big ecological and evolutionary implications. “It’s possible that other organisms could have evolved to hear and respond to these sounds,” says Hadany. “For example, a moth that intends to lay eggs on a plant or an animal that intends to eat a plant could use the sounds to help guide their decision.”
Other plants could also be listening in and benefiting from the sounds. We know from previous research that plants can respond to sounds and vibrations: Hadany and several other members of the team previously showed that plants increase the concentration of sugar in their nectar when they “hear” the sounds made by pollinators, and other studies have shown that plants change their gene expression in response to sounds. “If other plants have information about stress before it actually occurs, they could prepare,” says Hadany.
An illustration of a dehydrated tomato plant being recorded using a microphone. Credit: Liana Wait
Sound recordings of plants could be used in agricultural irrigation systems to monitor crop hydration status and help distribute water more efficiently, the authors say.
“We know that there’s a lot of ultrasound out there—every time you use a microphone, you find that a lot of stuff produces sounds that we humans cannot hear—but the fact that plants are making these sounds opens a whole new avenue of opportunities for communication, eavesdropping, and exploitation of these sounds,” says co-senior author Yossi Yovel, a neuro-ecologist at Tel Aviv University.
“So now that we know that plants do emit sounds, the next question is—’who might be listening?'” says Hadany. “We are currently investigating the responses of other organisms, both animals and plants, to these sounds, and we’re also exploring our ability to identify and interpret the sounds in completely natural environments.”
This is not a newly discovered phenomenon, plants, grasses and trees are very good at detecting and warning, eg
Stressed plants show altered phenotypes, including changes in color, smell, and shape. Yet, the possibility that plants emit airborne sounds when stressed – similarly to many animals – has not been investigated. Here we show, to our knowledge for the first time, that stressed plants emit airborne sounds that can be recorded remotely, both in acoustic chambers and in greenhouses. We recorded ∼65 dBSPL ultrasonic sounds 10 cm from tomato and tobacco plants, implying that these sounds could be detected by some organisms from up to several meters away. We developed machine learning models that were capable of distinguishing between plant sounds and general noises, and identifying the condition of the plants – dry, cut, or intact – based solely on the emitted sounds. Our results suggest that animals, humans, and possibly even other plants, could use sounds emitted by a plant to gain information about the plant’s condition. More investigation on plant bioacoustics in general and on sound emission in plants in particular may open new avenues for understanding plants and their interactions with the environment, and it may also have a significant impact on agriculture.
Source: Plants emit informative airborne sounds under stress
The remarkable ability of plants to respond to their environment has led some scientists to believe it’s a sign of conscious awareness. A new opinion paper argues against this position, saying plants “neither possess nor require consciousness.”
To explain these apparent behaviors, a subset of scientists known as plant neurobiologists has argued that plants possess a form of consciousness. Most notably, evolutionary ecologist Monica Gagliano has performed experiments that allegedly hint at capacities such as habituation (learning from experience) and classical conditioning (like Pavlov’s salivating dogs). In these experiments, plants apparently “learned” to stop curling their leaves after being dropped repeatedly or to spread their leaves in anticipation of a light source. Armed with this experimental evidence, Gagliano and others have claimed, quite controversially, that because plants can learn and exhibit other forms of intelligence, they must be conscious.
Nonsense, argues a new paper published today in Trends in Plant Science. The lead author of the new paper, biologist Lincoln Taiz from the University of California at Santa Cruz, isn’t denying plant intelligence, but makes a strong case against their being conscious.
Ultrasonic acoustic emission (UAE) in trees is often related to collapsing water columns in the flow path as a result of tensions that are too strong (cavitation). However, in a decibel (dB) range below that associated with cavitation, a close relationship was found between UAE intensities and stem radius changes.
UAE was continuously recorded on the stems of mature field-grown trees of Scots pine (Pinus sylvestris) and pubescent oak (Quercus pubescens) at a dry inner-Alpine site in Switzerland over two seasons. The averaged 20-Hz records were related to microclimatic conditions in air and soil, sap-flow rates and stem-radius fluctuations de-trended for growth (ΔW).•
Within a low-dB range (27 ± 1 dB), UAE regularly increased and decreased in a diurnal rhythm in parallel with ΔW on cloudy days and at night. These low-dB emissions were interrupted by UAE abruptly switching between the low-dB range and a high-dB range (36 ± 1 dB) on clear, sunny days, corresponding to the widely supported interpretation of UAE as sound from cavitations.•
It is hypothesized that the low-dB signals in drought-stressed trees are caused by respiration and/or cambial growth as these physiological activities are tissue water-content dependent and have been shown to produce courses of CO2 efflux similar to our courses of ΔW and low-dB UAE.
