India has successfully landed on the Moon – for less than the cost of the film Interstellar. The Indian space agency announced on Wednesday that it had completed a “soft landing” on the lunar surface, near its southern pole. It becomes the first ever to land there, and just the fourth country to successfully send a mission to the Moon at all. And it did so on a very restrictive budget. The Chandrayaan-3 cost was sent to the Moon at a cost of about 6.15 billion rupees, or $75 million, according to Reuters. That is less than the cost of most blockbuster space films. Gravity cost $100 million, The Martian cost $108 million – and it was less than half the cost of Interstellar, which was filmed on a budget of $165 million. It even costs less than some houses. The UK’s most expensive house, for instance, went on sale at £200 million, or nearly three-and-a-half missions to the Moon. The budget is even less than India allocated to Chandrayaan-2, the previous attempt to land on the Moon in 2019, which ended in failure when the lander crashed. That cost around 8 billion rupees, or about 30 per cent more than the latest successful mission, though engineers have made clear that many of the learnings from that earlier launch had been integrated into the latest one. India has looked to build a reputation for cost-effective but still successful missions to space. It comes as the country encourages investment in the private space industry and businesses focused on satellites. The price of the whole Indian mission is similar to that charged by SpaceX for one Falcon 9 launch. That is charged at $67 million, according to its website. Read More AI can detect Parkinson’s up to seven years before symptoms appear, study finds Justin Trudeau slams Facebook for blocking news stories about wildfires

DirecTV and Nexstar announced Monday that they had largely resolved a bitter carriage dispute that had left millions of the satellite carrier's subscribers unable to access local television giant Nexstar's large array of channels.

Shakira fans rip Gerard Pique, Dusty Baker announces retirement, Craig Counsell to interview with the Mets and more in the Roundup.

BOCA RATON, Fla.--(BUSINESS WIRE)--Nov 17, 2023--

SAN FRANCISCO--(BUSINESS WIRE)--Oct 26, 2023--

HARTFORD, Conn. (AP) — Tristen Newton scored 22 points to lead No. 6 UConn to a 107-67 rout of Stonehill College on Saturday.

After years of being labelled part of a “freak folk” movement by fans, Devendra Banhart says he has finally embraced being one of its leaders.

CRANBERRY TOWNSHIP, Pa.--(BUSINESS WIRE)--May 16, 2023--

The involuntary manslaughter charges against Alec Baldwin were formally dropped earlier

ESPN's College GameDay is celebrating the ultimate college football underdog story in Week 11.

Here's a breakdown of everything you need to know about Weapons Mastery Challenges in Call of Duty: Modern Warfare 2.

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