DENVER--(BUSINESS WIRE)--Sep 13, 2023--

The iPhone 15 has gone on sale – though customers might struggle to actually get hold of one today. The four new versions of the iPhone as well as updated Apple Watches were revealed at an event in California last week, and opened for pre-orders on Friday, 15 September. A week later, those pre-orders have arrived in the hands of the first customers and the iPhones are now available in stores. In recent years, Apple has discouraged the long queues that used to greet the launch of the iPhone, instead encouraging people to pre-order online even if they intend to eventually pick them up in store. The new launch was nonetheless met with lines at large Apple Stores. Some versions of the phones are already showing long waiting periods until they are delivered, however. Most models of the iPhone 15 Pro Max are not expected to be delivered until the end of October – and some even later than that. Numerous rumours had suggested that Apple would increase the price of this year’s models. But in fact the cost remained the same – and was reduced in the UK, in a surprise move. The iPhone 15 line-up comes in four different options: the base iPhone 15, a Plus model, and the iPhone 15 Pro and Pro Max. The iPhone 15 gets many of the upgrades that came to the Pro phones last year – an updated chip, better cameras and the “Dynamic Island” at the top of the screen – while this year’s Pro models feature a new titanium design, camera improvements and a much faster processor. It also released a new version of the Apple Watch, the Series 9, which brings an improved display and a “Double Tap” feature that lets people control the device just by using their hands. The Apple Watch Ultra was also updated to get that feature.

The entire Starlink internet experience is remarkably hands-off. You set up your dish on your

Projections range from zero to low single-digit growth. The evidence from early reporters so far is positive, but then there are unusual surprises—up or down.

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

IRVING, Texas--(BUSINESS WIRE)--Aug 8, 2023--

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