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"All of this probably means I should be worried about recent trends in artificial intelligence, which is encroaching on voice-over work in a manner similar to how it threatens the labour of visual artists and writers-both financially and ethically. The creep is only just beginning, with dubbing companies training software to replace human actors and tech companies introducing digital audiobook narration. But AI poses a threat to work opportunities across the board by giving producers the tools to recreate their favourite voices on demand, without the performer's knowledge or consent and without additional compensation. It's clear that AI will transform the arts sector, and the voice-over industry offers an early, unsettling model for what this future may look like."

"Wooldridge says copyright is a "coming storm" for AI companies. LLMs are likely to have accessed copyrighted material, such as news articles. Indeed the GPT-4-assisted chatbot attached to Microsoft's Bing search engine cites news sites in its answers. "I didn't give explicit permission for my works to be used as training data, but they almost certainly were, and now they contribute to what these models know," he says. "Many artists are gravely concerned that their livelihoods are at risk from generative AI. Expect to see legal battles," he adds."

"And Israeli company Optimove is helping. It normally gathers customer data to create targeted online ads, but as a service to gambling companies it has trained its AI to flag the online players who are most at risk.  It analyzes the behavior patterns characteristic of gambling addicts, which include the hours of the day and night when they place bets, the time they spend on the betting site, and how much they keep on playing to 'chase their losses'."

"He's right to be annoyed - these tracks are a violation of an artist's creativity and personhood - and the fakes are noticeably more sophisticated than those from a few years ago, when Jay-Z was made to rap Shakespeare (this is the kind of humour beloved of AI dorks). The tech will continue to improve to the point where the differences become indistinguishable. Perhaps lazy artists will soon use AI to generate their latest album, not so much phoning it in as texting it. AI composes its music by regurgitating things it's been trained to listen to in vast song databases, and that's not so different than the way human-composed pop music is recombined from prior influences. Producers, engineers, lyricists and all the other people who work behind a star could be usurped or at least have their value driven down by cheap AI tools."

""As the deceptive capabilities of AI systems become more advanced, the dangers they pose to society will become increasingly serious," said Dr Peter Park, an AI existential safety researcher at MIT and author of the research. Park was prompted to investigate after Meta, which owns Facebook, developed a program called Cicero that performed in the top 10% of human players at the world conquest strategy game Diplomacy. Meta stated that Cicero had been trained to be "largely honest and helpful" and to "never intentionally backstab" its human allies."

"A pilot study by academics at the University of Oxford found some care providers had been using generative AI chatbots such as ChatGPT and Bard to create care plans for people receiving care. That presents a potential risk to patient confidentiality, according to Dr Caroline Green, an early career research fellow at the Institute for Ethics in AI at Oxford, who surveyed care organisations for the study. "If you put any type of personal data into [a generative AI chatbot], that data is used to train the language model," Green said. "That personal data could be generated and revealed to somebody else." She said carers might act on faulty or biased information and inadvertently cause harm, and an AI-generated care plan might be substandard."

"Training a massive AI model, the size of GPT-4, would currently take about 8,000 H100 chips, and 15 megawatts of power, Nvidia said - enough to power about 30,000 typical British homes."

"In the last year or so, though, the rise of AI has upended that equation. For many publishers and platforms, having their data crawled for training data felt less like trading and more like stealing. "What we found pretty quickly with the AI companies," Stubblebine says, "is not only was it not an exchange of value, we're getting nothing in return. Literally zero." When Stubblebine announced last fall that Medium would be blocking AI crawlers, he wrote that "AI companies have leached value from writers in order to spam Internet readers." "

"Trying to shake humanity from its complacency about this, Yudkowsky published an op-ed in Time last spring that advised shutting down the computer farms where AIs are grown and trained. In clear, crisp prose, he speculated about the possible need for airstrikes targeted on datacentres; perhaps even nuclear exchange. Was he on to something?"

" Virtual reality games helping UK's deaf children to understand speech Scientists have found that immersing kids in computer games can train their brains to localise sounds better Robin McKie Science Editor Sat 25 May 2024 13.00 BST Share Scientists have recruited an unusual ally in their efforts to help children overcome profound deafness. They are using computer games to boost the children's ability to localise sounds and understand speech. The project is known as Bears - for Both Ears - and it is aimed at youngsters who have been given twin cochlea implants because they were born with little or no hearing. "These are children who are profoundly deaf," said audio engineer Lorenzo Picinali, a scientist on the project from Imperial College London. "They require major interventions to restore their hearing and we have found that computer games can make these much more effective.""

"Ultimately, he suggests, each user would have their own "large language model" (LLM), the underlying technology of services such as ChatGPT, which would be trained on their own speech and behaviour patterns, to let them generate extremely personalised responses to queries and requests. Such systems could be a natural progression from AI tools that already exist today. Services such as Gmail can summarise and suggest replies to emails based on previous messages, while Microsoft Teams will transcribe and summarise video conferences, automatically generating a to-do list from the contents."

"Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study."

"The system used historical data, including arrest records and electronic police reports, to forecast crime and help shape public safety strategies, according to company and city government materials. At no point did those materials suggest any effort to clean or amend the data to address the violations revealed by the DOJ. In all likelihood, the corrupted data was fed directly into the system, reinforcing the department's discriminatory practices."

"MIT researcher's at CSAIL have developed a lane-changing algorithm for self-driving cars. the algorithm allows for aggressive lane changes much like the kind only real drivers would be capable of.   it works by computing 'buffer zones' around autonomous vehicles and reassessing them on the fly. MIT uses a mathematically efficient approach which calculates new buffer zones if the default buffer zones lead to performance that's far worse than a human's driver."

"Virtual reality company, AVRT, has been collaborating with the force to create realistic computer generated scenarios officers might be in, such as dealing with a person in an alleyway or a rooftop"