TL;DR: As of June 17, get the Luminar Neo AI photo editing software for just

TL;DR: A lifetime subscription to Babbel is on sale for £141.50, saving you 54% on

Florida rejected nearly 35% of social studies textbooks submitted by publishers for approval, including those that referenced social justice and "other information that was not aligned with Florida Law," the state's Department of Education announced Tuesday.

SEOUL LG Electronics said on Wednesday it is targetting 100 trillion won ($77 billion) in sales by 2030

The federal government is reportedly investing at least $22m into developing clothes that “can record audio, video, and geolocation data.” According to a 22 August press release from the office of the Director of National Intelligence’s Intelligence Advanced Research Projects Activity (IARPA), the research and development arm of the organisation, “recently launched a cutting-edge program that aims to make performance-grade, computerized clothing a reality”. The DNI touted the SMART ePANTS program, which stands for Smart Electrically Powered and Networked Textile Systems, that “seeks to develop clothing with integrated audio, video, and geolocation sensor systems that feature the same stretchability, bendability, washability, and comfort of regular textiles,” IARPA stated. They will be used by the intelligence community, IARPA wrote. Since the surveillance technology will be woven into the clothing, “Intelligence Community staff will be able to record information from their environment hands-free, without the need to wear uncomfortable, bulky, and rigid devices.” For example, according to the release, the technology could “assist personnel and first responders in dangerous, high-stress environments, such as crime scenes and arms control inspections without impeding their ability to swiftly and safely operate.” The SMART ePANTS program’s mission is to to incorporate “sensor systems” into clothes, like shirts, pants, socks, and underwear. The Intercept reported that the federal government has dedicated at least $22m in funding to the program. It’s unclear just how big of a gamble IARPA might be making with its investment. Its website describes itself as investing “federal funding into high-risk, high-reward projects to address challenges facing the intelligence community.” “A lot of the IARPA and DARPA programs are like throwing spaghetti against the refrigerator,” Annie Jacobsen, author of a book called The Pentagon’s Brain about ​​the Defense Advanced Research Projects Agency, told the outlet. “It may or may not stick.” Dr Dawson Cagle, an IARPA program manager leading the SMART ePANTS program, said that while he is “proud of the intelligence aspect” of the program, he’s “excited about the possibilities that the program’s research will have for the greater world.” He said that he was inspired in part to create the program by his father, who was a diabetic, and therefore had to monitor his health multiple times a day. His father’s experience paired with the research that supports that the components of a computer “have already been developed, just as individual pieces,” he explained. If you can convert all of the components into a single, wearable device, the program’s goal will have been achieved, Dr Cagle said. Ms Jacobsen warned that the advancement of smart wearables could lead to future concerns over biometric surveillance by the government. “They’re now in a position of serious authority over you. In TSA, they can swab your hands for explosives,” Ms Jacobsen told The Intercept. “Now suppose SMART ePANTS detects a chemical on your skin — imagine where that can lead.” But IARPA pushed back on this assertion, as spokesperson Nicole de Haay told the outlet: “IARPA programs are designed and executed in accordance with, and adhere to, strict civil liberties and privacy protection protocols. Further, IARPA performs civil liberties and privacy protection compliance reviews throughout our research efforts.” Read More Swedish citizen goes on trial on charges of collecting information for Russia Seoul's spy agency says Russia has likely proposed North Korea to join three-way drills with China Biden says he is ‘disappointed’ at Xi Jinping skipping India’s G20 summit Vodafone users say they can’t call people World’s first solar-powered hybrid truck tested on public roads Apple is about to make a huge change to the iPhone that it never wanted to do

Vimeo Inc. Chief Executive Officer Anjali Sud will step down from her position at the business video software

The UK should work with its democratic allies to discuss defenses against hostile uses of artificial intelligence, according

OTTAWA Canadian Finance Minister Chrystia Freeland said on Tuesday she was cautiously optimistic about settling a dispute with

REDMOND, Wash.--(BUSINESS WIRE)--Nov 16, 2023--

The return of El Niño after nearly four years is raising the specter of extreme weather, economic pain,

Future generations of artificial intelligence chatbots trained using data from other AIs could lead to a downward spiral of gibberish on the internet, a new study has found. Large language models (LLMs) such as ChatGPT have taken off on the internet, with many users adopting the technology to produce a whole new ecosystem of AI-generated texts and images. But using the output data from such AI systems to further train subsequent generations of AI models could result in “irreversible defects” and junk content, according to a new, yet-to-be peer-reviewed study. AI models like ChatGPT are trained using vast amounts of data pulled across internet platforms that have mostly remained human generated until now. But AI-generated data using such models have a growing presence on the internet. Researchers, including those from the University of Oxford in the UK, attempted to understand what happened when several subsequent generations of AIs are trained off each other. They found the widespread use of LLMs to publish content on the internet on a large scale “will pollute the collection of data to train them” and lead to “model collapse”. “We discover that learning from data produced by other models causes model collapse – a degenerative process whereby, over time, models forget the true underlying data distribution,” scientists wrote in the study, posted as a preprint in arXiv. The new findings suggested there to be a “first mover advantage” when it comes to training LLMs. Scientists liken this change to what happens when AI models are trained on music created by human composers and played by human musicians. The subsequent AI output then trains other models, leading to a diminishing quality of music. With subsequent generations of AI models likely to encounter poorer quality data at their source, they may start misinterpreting information by inserting false information in a process scientists call “data poisoning”. They warned that the scale at which data poisoning can happen drastically changes after the advent of LLMs. Just a few iterations of data can lead to major degradation, even when the original data is preserved, scientists said. And over time, this could lead to mistakes compounding and forcing models that learn from generated data to misunderstand reality. “This in turn causes the model to misperceive the underlying learning task,” researchers said. Scientists cautioned that steps must be taken to label AI-generated content from human-generated ones, along with efforts to preserve original human-made data for future AI training. “To make sure that learning is sustained over a long time period, one needs to make sure that access to the original data source is preserved and that additional data not generated by LLMs remain available over time,” they wrote in the study. “Otherwise, it may become increasingly difficult to train newer versions of LLMs without access to data that was crawled from the Internet prior to the mass adoption of the technology, or direct access to data generated by humans at scale.” Read More ChatGPT ‘grandma exploit’ gives users free keys for Windows 11 Protect personal data when introducing AI, privacy watchdog warns businesses How Europe is leading the world in the push to regulate AI ‘Miracle material’ solar panels to finally enter production Meta reveals new AI that is too powerful to release Reddit user’s protests against the site’s rules have taken an even more bizarre turn

SPRING GROVE, Pa.--(BUSINESS WIRE)--Sep 13, 2023--