Latest news with #HuggingFace
7NEWS
a day ago
- Science
- 7NEWS
Being polite to AI could be harmful to the environment
Whether it's answering work emails or drafting wedding vows, generative artificial intelligence tools have become a trusty copilot in many people's lives. ut a growing body of research shows that for every problem AI solves, hidden environmental costs are racking up. Each word in an AI prompt is broken down into clusters of numbers called 'token IDs' and sent to massive data centres — some larger than football fields — powered by coal or natural gas plants. There, stacks of large computers generate responses through dozens of rapid calculations. The whole process can take up to 10 times more energy to complete than a regular Google search, according to a frequently cited estimation by the Electric Power Research Institute. So, for each prompt you give AI, what's the damage? To find out, researchers in Germany tested 14 large language model (LLM) AI systems by asking them both free-response and multiple-choice questions. Complex questions produced up to six times more carbon dioxide emissions than questions with concise answers. In addition, 'smarter' LLMs with more reasoning abilities produced up to 50 times more carbon emissions than simpler systems to answer the same question, the study reported. 'This shows us the tradeoff between energy consumption and the accuracy of model performance,' Maximilian Dauner, a doctoral student at Hochschule München University of Applied Sciences and first author of the Frontiers in Communication study published Wednesday, said. Typically, these smarter, more energy intensive LLMs have tens of billions more parameters — the biases used for processing token IDs — than smaller, more concise models. 'You can think of it like a neural network in the brain. The more neuron connections, the more thinking you can do to answer a question,' Dauner said. What you can do to reduce your carbon footprint Complex questions require more energy in part because of the lengthy explanations many AI models are trained to provide, Dauner said. If you ask an AI chatbot to solve an algebra question for you, it may take you through the steps it took to find the answer, he said. 'AI expends a lot of energy being polite, especially if the user is polite, saying 'please' and 'thank you',' Dauner said. 'But this just makes their responses even longer, expending more energy to generate each word.' For this reason, Dauner suggests users be more straightforward when communicating with AI models. Specify the length of the answer you want and limit it to one or two sentences, or say you don't need an explanation at all. Most important, Dauner's study highlights that not all AI models are created equally, Sasha Luccioni, the climate lead at AI company Hugging Face, said. Users looking to reduce their carbon footprint can be more intentional about which model they chose for which task. 'Task-specific models are often much smaller and more efficient, and just as good at any context-specific task,' Luccioni said. If you are a software engineer who solves complex coding problems every day, an AI model suited for coding may be necessary. But for the average high school student who wants help with homework, relying on powerful AI tools is like using a nuclear-powered digital calculator. Even within the same AI company, different model offerings can vary in their reasoning power, so research what capabilities best suit your needs, Dauner said. When possible, Luccioni recommends going back to basic sources — online encyclopedias and phone calculators — to accomplish simple tasks. Why it's hard to measure AI's environmental impact Putting a number on the environmental impact of AI has proved challenging. The study noted that energy consumption can vary based on the user's proximity to local energy grids and the hardware used to run AI models. That's partly why the researchers chose to represent carbon emissions within a range, Dauner said. Furthermore, many AI companies don't share information about their energy consumption — or details like server size or optimisation techniques that could help researchers estimate energy consumption, Shaolei Ren, an associate professor of electrical and computer engineering at the University of California, Riverside who studies AI's water consumption, said. 'You can't really say AI consumes this much energy or water on average — that's just not meaningful. We need to look at each individual model and then (examine what it uses) for each task,' Ren said. One way AI companies could be more transparent is by disclosing the amount of carbon emissions associated with each prompt, Dauner suggested. 'Generally, if people were more informed about the average (environmental) cost of generating a response, people would maybe start thinking, 'Is it really necessary to turn myself into an action figure just because I'm bored?' Or 'do I have to tell ChatGPT jokes because I have nothing to do?'' Dauner said. Additionally, as more companies push to add generative AI tools to their systems, people may not have much choice how or when they use the technology, Luccioni said. 'We don't need generative AI in web search. Nobody asked for AI chatbots in (messaging apps) or on social media,' Luccioni said. 'This race to stuff them into every single existing technology is truly infuriating, since it comes with real consequences to our planet.' With less available information about AI's resource usage, consumers have less choice, Ren said, adding that regulatory pressures for more transparency are unlikely to the United States anytime soon. Instead, the best hope for more energy-efficient AI may lie in the cost efficacy of using less energy. 'Overall, I'm still positive about (the future). There are many software engineers working hard to improve resource efficiency,' Ren said. 'Other industries consume a lot of energy too, but it's not a reason to suggest AI's environmental impact is not a problem. 'We should definitely pay attention.'
Yahoo
a day ago
- Business
- Yahoo
Hugging Face Co-Founder Challenges AI Optimists: 'Models Can't Ask Original Scientific Questions'
Thomas Wolf, co-founder and chief science officer at Hugging Face, has cast doubt on the belief that current artificial intelligence systems will lead to major scientific breakthroughs. Wolf told Fortune that today's large language models, or LLMs, excel at providing answers but fall short when it comes to formulating original questions. 'In science, asking the question is the hard part,' he said. 'Once the question is asked, often the answer is quite obvious, but the tough part is really asking the question, and models are very bad at asking great questions.' Don't Miss: GoSun's breakthrough rooftop EV charger already has 2,000+ units reserved — become an investor in this $41.3M clean energy brand today. Invest early in CancerVax's breakthrough tech aiming to disrupt a $231B market. Back a bold new approach to cancer treatment with high-growth potential. Wolf's comments were in response to a blog post by Anthropic CEO Dario Amodei, who argues that artificial intelligence could compress a century's worth of scientific breakthroughs into just a few years. Wolf said he initially found the post compelling but became skeptical after rereading. 'It was saying AI is going to solve cancer, and it's going to solve mental health problems—it's going to even bring peace into the world. But then I read it again and realized there's something that sounds very wrong about it, and I don't believe that,' he told Fortune. San Francisco-based Anthropic is backed by tech giants, including Inc. (NASDAQ:AMZN) and Alphabet Inc. (NASDAQ:GOOG, GOOGL)), and is also known for its Claude family of AI models. For Wolf, the core issue lies in how LLMs are trained. In another blog post, Wolf argues that today's AI systems are built to predict likely outcomes, act as "yes-men on servers," capable of mimicking human responses but incapable of challenging assumptions or generating original ideas. "To create an Einstein in a data center, we don't just need a system that knows all the answers, but rather one that can ask questions nobody else has thought of or dared to ask," Wolf wrote. He cited that real scientific progress often comes from paradigm shifts—like Copernicus proposing heliocentrism or the invention of CRISPR-based gene editing—rather than from answering existing questions. Trending: This Jeff Bezos-backed startup will allow you to become a landlord in just 10 minutes, with minimum investments as low as $100. Wolf also questioned how AI performance is measured today. In his blog post, he pointed to benchmarks like Humanity's Last Exam or Frontier Math, which test how well AI models can answer complex but well-defined questions. "These are exactly the kinds of exams where I excelled," Wolf wrote, referencing his academic background. "But real scientific breakthroughs come not from answering known questions, but from asking challenging new ones and questioning previous ideas." He argued that AI needs to demonstrate the ability to challenge its training data, take counterfactual approaches, and identify new research directions from incomplete information. Using the board game Go as an analogy, Wolf said the landmark 2016 victory of DeepMind's AlphaGo over world champions made headlines but was not revolutionary. "Move 37, while impressive, is still essentially a straight-A student answer to the question posed by the rules of the game of Go," he wrote in his blog. "An Einstein-level breakthrough in Go would involve inventing the rules of Go itself." Hugging Face is a prominent open-source platform in the AI community, known for its collaborative development of open-source machine learning models and tools. The company is backed by investors including Sequoia Capital and Lux Capital, and it plays a leading role in developing transparent and accessible AI systems. Wolf concluded that while current models are useful as assistants, true scientific progress requires a different kind of intelligence—one that can formulate disruptive questions rather than repeat what is already known. See Next: $100k in assets? Maximize your retirement and cut down on taxes: Schedule your free call with a financial advisor to start your financial journey – no cost, no obligation. Warren Buffett once said, "If you don't find a way to make money while you sleep, you will work until you die." Here's how you can earn passive income with just $100. UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock analysis from Benzinga? (AMZN): Free Stock Analysis Report ALPHABET (GOOG): Free Stock Analysis Report This article Hugging Face Co-Founder Challenges AI Optimists: 'Models Can't Ask Original Scientific Questions' originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
a day ago
- Business
- Yahoo
Hugging Face Co-Founder Challenges AI Optimists: 'Models Can't Ask Original Scientific Questions'
Thomas Wolf, co-founder and chief science officer at Hugging Face, has cast doubt on the belief that current artificial intelligence systems will lead to major scientific breakthroughs. Wolf told Fortune that today's large language models, or LLMs, excel at providing answers but fall short when it comes to formulating original questions. 'In science, asking the question is the hard part,' he said. 'Once the question is asked, often the answer is quite obvious, but the tough part is really asking the question, and models are very bad at asking great questions.' Don't Miss: GoSun's breakthrough rooftop EV charger already has 2,000+ units reserved — become an investor in this $41.3M clean energy brand today. Invest early in CancerVax's breakthrough tech aiming to disrupt a $231B market. Back a bold new approach to cancer treatment with high-growth potential. Wolf's comments were in response to a blog post by Anthropic CEO Dario Amodei, who argues that artificial intelligence could compress a century's worth of scientific breakthroughs into just a few years. Wolf said he initially found the post compelling but became skeptical after rereading. 'It was saying AI is going to solve cancer, and it's going to solve mental health problems—it's going to even bring peace into the world. But then I read it again and realized there's something that sounds very wrong about it, and I don't believe that,' he told Fortune. San Francisco-based Anthropic is backed by tech giants, including Inc. (NASDAQ:AMZN) and Alphabet Inc. (NASDAQ:GOOG, GOOGL)), and is also known for its Claude family of AI models. For Wolf, the core issue lies in how LLMs are trained. In another blog post, Wolf argues that today's AI systems are built to predict likely outcomes, act as "yes-men on servers," capable of mimicking human responses but incapable of challenging assumptions or generating original ideas. "To create an Einstein in a data center, we don't just need a system that knows all the answers, but rather one that can ask questions nobody else has thought of or dared to ask," Wolf wrote. He cited that real scientific progress often comes from paradigm shifts—like Copernicus proposing heliocentrism or the invention of CRISPR-based gene editing—rather than from answering existing questions. Trending: This Jeff Bezos-backed startup will allow you to become a landlord in just 10 minutes, with minimum investments as low as $100. Wolf also questioned how AI performance is measured today. In his blog post, he pointed to benchmarks like Humanity's Last Exam or Frontier Math, which test how well AI models can answer complex but well-defined questions. "These are exactly the kinds of exams where I excelled," Wolf wrote, referencing his academic background. "But real scientific breakthroughs come not from answering known questions, but from asking challenging new ones and questioning previous ideas." He argued that AI needs to demonstrate the ability to challenge its training data, take counterfactual approaches, and identify new research directions from incomplete information. Using the board game Go as an analogy, Wolf said the landmark 2016 victory of DeepMind's AlphaGo over world champions made headlines but was not revolutionary. "Move 37, while impressive, is still essentially a straight-A student answer to the question posed by the rules of the game of Go," he wrote in his blog. "An Einstein-level breakthrough in Go would involve inventing the rules of Go itself." Hugging Face is a prominent open-source platform in the AI community, known for its collaborative development of open-source machine learning models and tools. The company is backed by investors including Sequoia Capital and Lux Capital, and it plays a leading role in developing transparent and accessible AI systems. Wolf concluded that while current models are useful as assistants, true scientific progress requires a different kind of intelligence—one that can formulate disruptive questions rather than repeat what is already known. See Next: $100k in assets? Maximize your retirement and cut down on taxes: Schedule your free call with a financial advisor to start your financial journey – no cost, no obligation. Warren Buffett once said, "If you don't find a way to make money while you sleep, you will work until you die." Here's how you can earn passive income with just $100. UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock analysis from Benzinga? (AMZN): Free Stock Analysis Report ALPHABET (GOOG): Free Stock Analysis Report This article Hugging Face Co-Founder Challenges AI Optimists: 'Models Can't Ask Original Scientific Questions' originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved. Se produjo un error al recuperar la información Inicia sesión para acceder a tu portafolio Se produjo un error al recuperar la información Se produjo un error al recuperar la información Se produjo un error al recuperar la información Se produjo un error al recuperar la información
TechCrunch
4 days ago
- TechCrunch
Google rolls out new Gemini model that can run on robots locally
Google DeepMind on Tuesday released a new language model called Gemini Robotics On-Device that can run tasks locally on robots without requiring an internet connection. Building on the company's previous Gemini Robotics model that was released in March, Gemini Robotics On-Device can control a robot's movements. Developers can control and fine-tune the model to suit various needs using natural language prompts. In benchmarks, Google claims the model performs at a level close to the cloud-based Gemini Robotics model. The company says it outperforms other on-device models in general benchmarks, though it didn't name those models. Image Credits: Google In a demo, the company showed robots running this local model doing things like unzipping bags and folding clothes. Google says that while the model was trained for ALOHA robots, it later adapted it to work on a bi-arm Franka FR3 robot and the Apollo humanoid robot by Apptronik. Google claims the bi-arm Franka FR3 was successful in tackling scenarios and objects it hadn't 'seen' before, like doing assembly on an industrial belt. Google DeepMind is also releasing a Gemini Robotics SDK. The company said developers can show robots 50 to 100 demonstrations of tasks to train them on new tasks using these models on the MuJoCo physics simulator. Other AI model developers are also dipping their toes in robotics. Nvidia is building a platform to create foundation models for humanoids; Hugging Face is not only developing open models and datasets for robotics, it is actually working on robots too; and Mirae Asset-backed Korean startup RLWRLD is working on creating foundational models for robots.
The Verge
5 days ago
- Entertainment
- The Verge
Fanfiction writers battle AI, one scrape at a time
In the online world of fanfiction writers, who pen stories inspired by their favorite movies, books, and games, and share them for free, there are unspoken codes of conduct. Among the most important: never charge money for your fanfic, and never steal other people's work. It makes sense then that fanfic writers were among the first creators to raise the alarm about their work being fed into learning language models powering generative AI without their knowledge or permission. But their efforts to stop the encroachment of AI into fan spaces is an uphill battle. The latest salvo came in early April, when user nyuuzyou scraped 12.6 million fanfics from the online repository Archive of Our Own (AO3) and uploaded the dataset to Hugging Face, a company that hosts open-source AI models and software. Nyuuzyou's upload was quickly discovered by the Reddit community r/AO3, where hundreds of users posted furious reactions. A Tumblr account, ao3scrapesearch, built a search engine that allowed authors to search their usernames and see if their work had been scraped by Nyuuzyou. 'This is something that takes time and effort and your heart and your soul, and you do this in a community.' Fanfic writers flooded the comment section of the dataset on Hugging Face, getting into arguments with AI defenders. Dckchili defended nyuuzyou's scrape, claiming that it didn't matter because Big Tech crawler bots have already scraped the archive numerous times. RaraeAves argued that 'the creeps' are depending on fanfic writers to not fight back when their labor and creativity are being exploited. When Nikki, a Star Wars fanfic writer who goes by infinitegalaxies online, typed her name in the search engine, she saw that more than 70 of her fics had been scraped. But one jumped out. It was a collective essay she'd co-authored with 11 other writers to raise awareness about the threat of AI to fandom and uploaded to AO3. The irony did not escape her. Nikki mostly writes fanfiction about Reylo, the romantic pairing (or 'ship') of the characters Rey and Kylo Ren from the Star Wars sequel trilogy. The Reylo fandom is close-knit and prolific, with more than 30,000 Reylo stories posted to AO3. About half are set in the canon Star Wars universe of light sabers and space adventures, but the other half take place in alternative universes and explore everything from coffee-shop romances and workplace dramas to medieval knights and fairy kingdoms. One particularly beloved fic in the fandom is set in 1994 and recasts Kylo Ren as Kyril, a mafia boss in newly post-Soviet Russia. The fandom has produced writers like Ali Hazelwood and Thea Guazon, who have made the leap from fanfic to become highly successful, published romance authors. For Nikki, the Reylo fandom offered a new sense of belonging. She found a home in the supportive community of writers and readers and relished the freedom to write whatever she wanted. 'Fandom is largely a gift economy. We're just here to have fun and do things out of the goodness of our heart. And to give things to each other and make work in community,' Nikki says. This sentiment is echoed by many others in the Reylo community, including Em, who writes under the pen name okapijones. Em fell in love with the characters of Rey and Kylo Ren because they represented the enemies-to-lovers light / dark archetypes that reminded her of Beauty and the Beast and Pride and Prejudice. But she hated the way their story ended in the Star Wars sequel trilogy and went looking for other fans who wanted a different ending. 'Fic changed my life. I have met some of the best friends that I have ever had through fic and through the fanfiction community,' Em says. 'There's no rules, there's no editors. It's a pure creative playground, and that is going to breed innovation. Some of the most creative stories I've ever read, some of the wildest storytelling, is fanfic. And that excites me as a creator, because you can just do whatever you want.' 'This is something that takes time and effort and your heart and your soul, and you do this in a community,' Nikki says. 'And then you're telling me you're just going to poop it out two seconds on a screen. And I was just like, who asked for this? This is gross.' In 2023 came Sudowrite's Story Engine, powered in part by OpenAI's ChatGPT. Nikki remembers watching a video about the new 'writing assistant' AI software that allows users to enter details about characters and plot points and generate an entire novel. She was so appalled that it made her cry. Nikki, who works for a software company, had already seen her workplace shift toward integrating AI. But she hadn't imagined her hobby would be impacted by it too. 'Trying to knock this stuff down, that's probably the best thing that one can be doing now.' Later that year, the prevalence of highly specific sexual terms related to the wolf-biology fanfiction trope of Omegaverse appeared in Sudowrite, revealing that ChatGPT had likely been trained on fanfic without the authors' knowledge. Since then, Nikki and many others have been advocating against AI in all its forms in fandom, including using AI to generate fanfic or fanart. 'It's theft at its core. There's no ethical use of something that's built on stolen labor,' Nikki says. Although she's against genAI in principle because of its reliance on data taken without consent, she also says it breaks with fandom norms of free exchange. 'I did it because I love those characters, because I wanted to play in that sandbox, because I wanted people who also love them to read it. It is a gift.' Em says. 'They stole it without my permission.' But over the last few years, fanfic writers say there have been numerous examples of genAI entrepreneurs trying to cash in on their work — such as people like Cliff Weitzman, the CEO of text-to-voice app Speechify, who was found to have scraped thousands of fics from AO3 and uploaded them to WordStream, a website linked to his app, without the authors' permission. (He swiftly removed that after fans pushed back on social media.) Then there was a text-to-speech app from Wishroll Inc, which marketed itself on TikTok as 'Audible for AO3.' The app was announced in May 2024 but was withdrawn later that month after fan pushback. 'It's like a whack-a-mole thing. Every time you turn around, there's, like, another grifter trying to steal your shit,' Nikki says. It may seem odd to hear such a strong sentiment from a writer who, like most fanfic creators, uses copyrighted intellectual property as a 'sandbox' to make up their own stories. But advocates for fanworks say they are 'transformative,' meaning a 'fanwork creator holds the rights to their own content, just the same as any professional author, artist, or other creator,' according to AO3. This is very different from what a LLM does when, for example, it generates a novel based on prompts. AI can't replicate the creative human process of 'transformation,' which involves inventing and integrating new ideas. LLMs can only reshuffle and regurgitate content that already exists. And, unlike the AI-generated books flooding Amazon, one of the principles of fanfiction is that writers do not make any profit from their work. That hasn't stopped AI infiltrating fandom in other controversial ways. Some readers, eager to get new updates of their favorite fics, have taken to uploading them into ChatGPT to generate new chapters, much to the consternation of some authors. Some have taken to locking their stories, requiring readers to have an AO3 account to access them or deleting them from the internet altogether. In the case of nyuuzou's scrape, fans coordinated online to file take-down notices under the Digital Millennium Copyright Act (DMCA), and the Organization for Transformative Works (OTW), the nonprofit that administers AO3, also filed a takedown. On April 9, Hugging Face disabled the dataset. OTW responded to user concerns about fanfics being scraped in a board meeting on April 26, saying, 'We have added a CloudFlare tool to prevent AI scraping and other bots. This helps a lot but is not perfect. However, more robust solutions would have a significant negative impact on some of our users, especially those using older devices.' Nyuuzou remained unrepentant, filing a counternotice and reuploading the dataset to sites hosted in Russia and China, which are far less responsive to DMCA complaints. Contacted by The Verge via a Telegram account linked on his Hugging Face profile, nyuuzou said he was an 18-year-old student and IT worker in Russia who is 'not interested in fanfiction' and uploaded the dataset for 'legitimate research purposes.' 'My goal was to support community research in areas like content moderation, anti-plagiarism tools, recommendation systems, and archival preservation,' nyuuzou wrote via Telegram. 'I think a lot of the disagreement comes from misunderstandings about why these datasets exist. This was never about creating chatbots or large language models for commercial use.' Founded in 2016 by French entrepreneurs, Hugging Face started out building chatbots for teenagers. Since then, the company has expanded to hosting open-source models with the stated aim of 'democratizing AI' by making machine-learning development accessible to the public. 'Our goal is to enable every company in the world to build their own AI,' Jeff Boudier, Hugging Face's head of product, told Amazon Web Services (AWS) in February. But Hugging Face is deeply connected to large companies. In addition to its ongoing collaboration with AWS, IBM invested $235 million in Hugging Face in 2023 and announced it was collaborating with the company on watsonx, IBM's generative AI platform. Nyuuzou said he was surprised by OTW's aggressive reaction to the dataset, writing, 'I had hoped for dialogue about how research datasets might align with preservation goals.' 'That's really disingenuous,' says Alex Hanna, director of research at the Distributed AI Research Institute and author of The AI Con: How to Fight Big Tech's Hype and Create the Future We Want. She's skeptical of the idea that any dataset uploaded to Hugging Face wouldn't ultimately be used to train LLMs. 'Why would you have a large tranche of unstructured data available on the web if not to train a language model?' Although individual scrapers like nyuuzou are small fry in the wider economy of genAI, which is dominated by billion-dollar companies like OpenAI, Hanna says it's still up to sites like AO3 to aggressively protect their users' work. As for fanfic writers themselves, she thinks Nikki's strategy of whack-a-mole is the way to go. 'Trying to knock this stuff down, that's probably the best thing that one can be doing now,' Hanna says. Nikki and Em, the fanfic writers, had a more heated response to nyuuzou's explanation for the scrape. 'Fuck you, dude,' Em says. 'We do free labor for the love of the game and are not profiting off of it — other than creating a community, gaining practice for our craft and creating content for characters and stories that we love. And that is being stolen to fuel things that have such larger implications.' Nikki says she's determined to keep pushing back against AI's encroachment into fandom spaces. 'I don't go looking for a fight,' she says. 'But when people come to us with a fight, I will fight.'
