By John Irish PARIS (Reuters) -British-born actress and singer Jane Birkin, a 1960s wildchild who became a beloved figure in

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

A federal appeals court narrowed a judge's order that blocked Biden administration officials from communicating with social media companies, in a lawsuit brought by Republican attorneys general that claimed the administration engaged in unconstitutional censorship in its efforts to combat Covid-19 disinformation.

According to the 22-second recording, Terry Janway calmly gave her address to the dispatcher and said, 'There's somebody here with a gun'

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Sarah Murdoch is also the ambassador of Murdoch Children's Research Institute

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By Steve Scherer OTTAWA (Reuters) -A consortium of Ford Motor Co and South Korean companies on Thursday said they would

A Ukrainian drone sparked a fire at an oil refinery in southern Russia and shelling hit a Russian town close to the border for the third time in a week, damaging buildings and setting vehicles ablaze, Russian officials said on Wednesday. A day after Russia accused Ukraine of sending drones to attack buildings in Moscow, the governor of Russia’s Krasnodar region said a drone was the likely cause of a fire that broke out at the Afipsky oil refinery. The report could not be immediately independently verified. Earlier, Vladimir Putin accused Ukraine of “terrorist activity” after Moscow was hit with a drone attack for the first time since the war in the besieged country began. The Russian president accused Ukraine, which has denied any involvement in the drone attack, of choosing the path of attempting “to intimidate Russia, Russian citizens and attacks on residential buildings”. Drones hit several buildings in Moscow, forcing some people to evacuate their homes after Russia launched its third attack on Kyiv in 24 hours. Read More New US aid package for Ukraine will total about $300 million and include munitions for drones UN nuclear chief urges Russia and Ukraine to ban attacks at Europe's largest nuclear power plant ‘Putin’s only response is violence’: How Russia is expected react to the drone attack on Moscow Drone attacks on Moscow pose a significant problem for Putin