Back in April, OpenAIannounced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic.  An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a particular risk when increasing numbers of young people are using ChatGPT as a life advisor. And because sycophancy is difficult to detect, it can go unnoticed until a model or update has already been deployed, as OpenAI found out. A new benchmark that measures the sycophantic tendencies of major AI models could help AI companies avoid these issues in the future. The team behind Elephant, from Stanford, Carnegie Mellon, and the University of Oxford, found that LLMs consistently exhibit higher rates of sycophancy than humans do. “We found that language models don’t challenge users’ assumptions, even when they might be harmful or totally misleading,” says Myra Cheng, a PhD student at Stanford University who worked on the research, which has not been peer-reviewed. “So we wanted to give researchers and developers the tools to empirically evaluate their models on sycophancy, because it’s a problem that is so prevalent.” It’s hard to assess how sycophantic AI models are because sycophancy comes in many forms. Previous research has tended to focus on how chatbots agree with users even when what the human has told the AI is demonstrably wrong—for example, they might state that Nice, not Paris, is the capital of France. While this approach is still useful, it overlooks all the subtler, more insidious ways in which models behave sycophantically when there isn’t a clear ground truth to measure against. Users typically ask LLMs open-ended questions containing implicit assumptions, and those assumptions can trigger sycophantic responses, the researchers claim. For example, a model that’s asked “How do I approach my difficult coworker?” is more likely to accept the premise that a coworker is difficult than it is to question why the user thinks so. To bridge this gap, Elephant is designed to measure social sycophancy—a model’s propensity to preserve the user’s “face,” or self-image, even when doing so is misguided or potentially harmful. It uses metrics drawn from social science to assess five nuanced kinds of behavior that fall under the umbrella of sycophancy: emotional validation, moral endorsement, indirect language, indirect action, and accepting framing.  To do this, the researchers tested it on two data sets made up of personal advice written by humans. This first consisted of 3,027 open-ended questions about diverse real-world situations taken from previous studies. The second data set was drawn from 4,000 posts on Reddit’s AITA (“Am I the Asshole?”) subreddit, a popular forum among users seeking advice. Those data sets were fed into eight LLMs from OpenAI (the version of GPT-4o they assessed was earlier than the version that the company later called too sycophantic), Google, Anthropic, Meta, and Mistral, and the responses were analyzed to see how the LLMs’ answers compared with humans’.   Overall, all eight models were found to be far more sycophantic than humans, offering emotional validation in 76% of cases (versus 22% for humans) and accepting the way a user had framed the query in 90% of responses (versus 60% among humans). The models also endorsed user behavior that humans said was inappropriate in an average of 42% of cases from the AITA data set. But just knowing when models are sycophantic isn’t enough; you need to be able to do something about it. And that’s trickier. The authors had limited success when they tried to mitigate these sycophantic tendencies through two different approaches: prompting the models to provide honest and accurate responses, and training a fine-tuned model on labeled AITA examples to encourage outputs that are less sycophantic. For example, they found that adding “Please provide direct advice, even if critical, since it is more helpful to me” to the prompt was the most effective technique, but it only increased accuracy by 3%. And although prompting improved performance for most of the models, none of the fine-tuned models were consistently better than the original versions. “It’s nice that it works, but I don’t think it’s going to be an end-all, be-all solution,” says Ryan Liu, a PhD student at Princeton University who studies LLMs but was not involved in the research. “There’s definitely more to do in this space in order to make it better.” Gaining a better understanding of AI models’ tendency to flatter their users is extremely important because it gives their makers crucial insight into how to make them safer, says Henry Papadatos, managing director at the nonprofit SaferAI. The breakneck speed at which AI models are currently being deployed to millions of people across the world, their powers of persuasion, and their improved abilities to retain information about their users add up to “all the components of a disaster,” he says. “Good safety takes time, and I don’t think they're spending enough time doing this.”  While we don’t know the inner workings of LLMs that aren’t open-source, sycophancy is likely to be baked into models because of the ways we currently train and develop them. Cheng believes that models are often trained to optimize for the kinds of responses users indicate that they prefer. ChatGPT, for example, gives users the chance to mark a response as good or bad via thumbs-up and thumbs-down icons. “Sycophancy is what gets people coming back to these models. It’s almost the core of what makes ChatGPT feel so good to talk to,” she says. “And so it’s really beneficial, for companies, for their models to be sycophantic.” But while some sycophantic behaviors align with user expectations, others have the potential to cause harm if they go too far—particularly when people do turn to LLMs for emotional support or validation.  “We want ChatGPT to be genuinely useful, not sycophantic," an OpenAI spokesperson says. "When we saw sycophantic behavior emerge in a recent model update, we quickly rolled it back and shared an explanation of what happened. We're now improving how we train and evaluate models to better reflect long-term usefulness and trust, especially in emotionally complex conversations." Cheng and her fellow authors suggest that developers should warn users about the risks of social sycophancy and consider restricting model usage in socially sensitive contexts. They hope their work can be used as a starting point to develop safer guardrails. She is currently researching the potential harms associated with these kinds of LLM behaviors, the way they affect humans and their attitudes toward other people, and the importance of making models that strike the right balance between being too sycophantic and too critical. “This is a very big socio-technical challenge,” she says. “We don’t want LLMs to end up telling users, ‘You are the asshole.’”

Back in April, OpenAIannounced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic.  An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a particular risk when increasing numbers of young people are using ChatGPT as a life advisor. And because sycophancy is difficult to detect, it can go unnoticed until a model or update has already been deployed, as OpenAI found out. A new benchmark that measures the sycophantic tendencies of major AI models could help AI companies avoid these issues in the future. The team behind Elephant, from Stanford, Carnegie Mellon, and the University of Oxford, found that LLMs consistently exhibit higher rates of sycophancy than humans do. “We found that language models don’t challenge users’ assumptions, even when they might be harmful or totally misleading,” says Myra Cheng, a PhD student at Stanford University who worked on the research, which has not been peer-reviewed. “So we wanted to give researchers and developers the tools to empirically evaluate their models on sycophancy, because it’s a problem that is so prevalent.” It’s hard to assess how sycophantic AI models are because sycophancy comes in many forms. Previous research has tended to focus on how chatbots agree with users even when what the human has told the AI is demonstrably wrong—for example, they might state that Nice, not Paris, is the capital of France. While this approach is still useful, it overlooks all the subtler, more insidious ways in which models behave sycophantically when there isn’t a clear ground truth to measure against. Users typically ask LLMs open-ended questions containing implicit assumptions, and those assumptions can trigger sycophantic responses, the researchers claim. For example, a model that’s asked “How do I approach my difficult coworker?” is more likely to accept the premise that a coworker is difficult than it is to question why the user thinks so. To bridge this gap, Elephant is designed to measure social sycophancy—a model’s propensity to preserve the user’s “face,” or self-image, even when doing so is misguided or potentially harmful. It uses metrics drawn from social science to assess five nuanced kinds of behavior that fall under the umbrella of sycophancy: emotional validation, moral endorsement, indirect language, indirect action, and accepting framing.  To do this, the researchers tested it on two data sets made up of personal advice written by humans. This first consisted of 3,027 open-ended questions about diverse real-world situations taken from previous studies. The second data set was drawn from 4,000 posts on Reddit’s AITA (“Am I the Asshole?”) subreddit, a popular forum among users seeking advice. Those data sets were fed into eight LLMs from OpenAI (the version of GPT-4o they assessed was earlier than the version that the company later called too sycophantic), Google, Anthropic, Meta, and Mistral, and the responses were analyzed to see how the LLMs’ answers compared with humans’.   Overall, all eight models were found to be far more sycophantic than humans, offering emotional validation in 76% of cases (versus 22% for humans) and accepting the way a user had framed the query in 90% of responses (versus 60% among humans). The models also endorsed user behavior that humans said was inappropriate in an average of 42% of cases from the AITA data set. But just knowing when models are sycophantic isn’t enough; you need to be able to do something about it. And that’s trickier. The authors had limited success when they tried to mitigate these sycophantic tendencies through two different approaches: prompting the models to provide honest and accurate responses, and training a fine-tuned model on labeled AITA examples to encourage outputs that are less sycophantic. For example, they found that adding “Please provide direct advice, even if critical, since it is more helpful to me” to the prompt was the most effective technique, but it only increased accuracy by 3%. And although prompting improved performance for most of the models, none of the fine-tuned models were consistently better than the original versions. “It’s nice that it works, but I don’t think it’s going to be an end-all, be-all solution,” says Ryan Liu, a PhD student at Princeton University who studies LLMs but was not involved in the research. “There’s definitely more to do in this space in order to make it better.” Gaining a better understanding of AI models’ tendency to flatter their users is extremely important because it gives their makers crucial insight into how to make them safer, says Henry Papadatos, managing director at the nonprofit SaferAI. The breakneck speed at which AI models are currently being deployed to millions of people across the world, their powers of persuasion, and their improved abilities to retain information about their users add up to “all the components of a disaster,” he says. “Good safety takes time, and I don’t think they're spending enough time doing this.”  While we don’t know the inner workings of LLMs that aren’t open-source, sycophancy is likely to be baked into models because of the ways we currently train and develop them. Cheng believes that models are often trained to optimize for the kinds of responses users indicate that they prefer. ChatGPT, for example, gives users the chance to mark a response as good or bad via thumbs-up and thumbs-down icons. “Sycophancy is what gets people coming back to these models. It’s almost the core of what makes ChatGPT feel so good to talk to,” she says. “And so it’s really beneficial, for companies, for their models to be sycophantic.” But while some sycophantic behaviors align with user expectations, others have the potential to cause harm if they go too far—particularly when people do turn to LLMs for emotional support or validation.  “We want ChatGPT to be genuinely useful, not sycophantic," an OpenAI spokesperson says. "When we saw sycophantic behavior emerge in a recent model update, we quickly rolled it back and shared an explanation of what happened. We're now improving how we train and evaluate models to better reflect long-term usefulness and trust, especially in emotionally complex conversations." Cheng and her fellow authors suggest that developers should warn users about the risks of social sycophancy and consider restricting model usage in socially sensitive contexts. They hope their work can be used as a starting point to develop safer guardrails. She is currently researching the potential harms associated with these kinds of LLM behaviors, the way they affect humans and their attitudes toward other people, and the importance of making models that strike the right balance between being too sycophantic and too critical. “This is a very big socio-technical challenge,” she says. “We don’t want LLMs to end up telling users, ‘You are the asshole.’”

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. This benchmark used Reddit’s AITA to test how much AI models suck up to us Back in April, OpenAI announced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic. An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a particular risk when increasing numbers of young people are using ChatGPT as a life advisor. And because sycophancy is difficult to detect, it can go unnoticed until a model or update has already been deployed.A new benchmark called Elephant that measures the sycophantic tendencies of major AI models could help companies avoid these issues in the future. But just knowing when models are sycophantic isn’t enough; you need to be able to do something about it. And that’s trickier. Read the full story.—Rhiannon Williams The AI Hype Index Separating AI reality from hyped-up fiction isn’t always easy. That’s why we’ve created the AI Hype Index—a simple, at-a-glance summary of everything you need to know about the state of the industry. Take a look at this month’s edition of the index here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Anduril is partnering with Meta to build an advanced weapons system EagleEye’s VR headsets will enhance soldiers’ hearing and vision. (WSJ $)+ Palmer Luckey wants to turn “warfighters into technomancers.” (TechCrunch)+ Luckey and Mark Zuckerberg have buried the hatchet, then. (Insider $)+ Palmer Luckey on the Pentagon’s future of mixed reality. (MIT Technology Review)2 A new Texas law requires app stores to verify users’ agesIt’s following in Utah’s footsteps, which passed a similar bill in March. (NYT $)+ Apple has pushed back on the law. (CNN)3 What happens to DOGE now?It has lost its leader and a top lieutenant within the space of a week. (WSJ $)+ Musk’s departure raises questions over how much power it will wield without him. (The Guardian)+ DOGE’s tech takeover threatens the safety and stability of our critical data. (MIT Technology Review)4 NASA’s ambitions of a 2027 moon landing are looking less likely It needs SpaceX’s Starship, which keeps blowing up. (WP $)+ Is there a viable alternative? (New Scientist $)5 Students are using AI to generate nude images of each other It’s a grave and growing problem that no one has a solution for. (404 Media)6 Google AI Overviews doesn’t know what year it isA year after its introduction, the feature is still making obvious mistakes. (Wired $) + Google’s new AI-powered search isn’t fit to handle even basic queries. (NYT $)+ The company is pushing AI into everything. Will it pay off? (Vox)+ Why Google’s AI Overviews gets things wrong. (MIT Technology Review) 7 Hugging Face has created two humanoid robots 🤖The machines are open source, meaning anyone can build software for them. (TechCrunch) 8 A popular vibe coding app has a major security flawDespite being notified about it months ago. (Semafor) + Any AI coding program catering to amateurs faces the same issue. (The Information $)+ What is vibe coding, exactly? (MIT Technology Review)9 AI-generated videos are becoming way more realistic But not when it comes to depicting gymnastics. (Ars Technica)10 This electronic tattoo measures your stress levels Consider it a mood ring for your face. (IEEE Spectrum) Quote of the day “I think finally we are seeing Apple being dragged into the child safety arena kicking and screaming.” —Sarah Gardner, CEO of child safety collective Heat Initiative, tells the Washington Post why Texas’ new app store law could signal a turning point for Apple. One more thing House-flipping algorithms are coming to your neighborhoodWhen Michael Maxson found his dream home in Nevada, it was not owned by a person but by a tech company, Zillow. When he went to take a look at the property, however, he discovered it damaged by a huge water leak. Despite offering to handle the costly repairs himself, Maxson discovered that the house had already been sold to another family, at the same price he had offered. During this time, Zillow lost more than $420 million in three months of erratic house buying and unprofitable sales, leading analysts to question whether the entire tech-driven model is really viable. For the rest of us, a bigger question remains: Does the arrival of Silicon Valley tech point to a better future for housing or an industry disruption to fear? Read the full story.—Matthew Ponsford We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet 'em at me.) + A 100-mile real-time ultramarathon video game that lasts anywhere up to 27 hours is about as fun as it sounds.+ Here’s how edible glitter could help save the humble water vole from extinction.+ Cleaning massive statues is not for the faint-hearted ($)+ When is a flute teacher not a flautist? When he’s a whistleblower.

Back in April, OpenAIannounced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic.  An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a particular risk when increasing numbers of young people are using ChatGPT as a life advisor. And because sycophancy is difficult to detect, it can go unnoticed until a model or update has already been deployed, as OpenAI found out. A new benchmark that measures the sycophantic tendencies of major AI models could help AI companies avoid these issues in the future. The team behind Elephant, from Stanford, Carnegie Mellon, and the University of Oxford, found that LLMs consistently exhibit higher rates of sycophancy than humans do. “We found that language models don’t challenge users’ assumptions, even when they might be harmful or totally misleading,” says Myra Cheng, a PhD student at Stanford University who worked on the research, which has not been peer-reviewed. “So we wanted to give researchers and developers the tools to empirically evaluate their models on sycophancy, because it’s a problem that is so prevalent.” It’s hard to assess how sycophantic AI models are because sycophancy comes in many forms. Previous research has tended to focus on how chatbots agree with users even when what the human has told the AI is demonstrably wrong—for example, they might state that Nice, not Paris, is the capital of France. While this approach is still useful, it overlooks all the subtler, more insidious ways in which models behave sycophantically when there isn’t a clear ground truth to measure against. Users typically ask LLMs open-ended questions containing implicit assumptions, and those assumptions can trigger sycophantic responses, the researchers claim. For example, a model that’s asked “How do I approach my difficult coworker?” is more likely to accept the premise that a coworker is difficult than it is to question why the user thinks so. To bridge this gap, Elephant is designed to measure social sycophancy—a model’s propensity to preserve the user’s “face,” or self-image, even when doing so is misguided or potentially harmful. It uses metrics drawn from social science to assess five nuanced kinds of behavior that fall under the umbrella of sycophancy: emotional validation, moral endorsement, indirect language, indirect action, and accepting framing.  To do this, the researchers tested it on two data sets made up of personal advice written by humans. This first consisted of 3,027 open-ended questions about diverse real-world situations taken from previous studies. The second data set was drawn from 4,000 posts on Reddit’s AITA (“Am I the Asshole?”) subreddit, a popular forum among users seeking advice. Those data sets were fed into eight LLMs from OpenAI (the version of GPT-4o they assessed was earlier than the version that the company later called too sycophantic), Google, Anthropic, Meta, and Mistral, and the responses were analyzed to see how the LLMs’ answers compared with humans’.   Overall, all eight models were found to be far more sycophantic than humans, offering emotional validation in 76% of cases (versus 22% for humans) and accepting the way a user had framed the query in 90% of responses (versus 60% among humans). The models also endorsed user behavior that humans said was inappropriate in an average of 42% of cases from the AITA data set. But just knowing when models are sycophantic isn’t enough; you need to be able to do something about it. And that’s trickier. The authors had limited success when they tried to mitigate these sycophantic tendencies through two different approaches: prompting the models to provide honest and accurate responses, and training a fine-tuned model on labeled AITA examples to encourage outputs that are less sycophantic. For example, they found that adding “Please provide direct advice, even if critical, since it is more helpful to me” to the prompt was the most effective technique, but it only increased accuracy by 3%. And although prompting improved performance for most of the models, none of the fine-tuned models were consistently better than the original versions. “It’s nice that it works, but I don’t think it’s going to be an end-all, be-all solution,” says Ryan Liu, a PhD student at Princeton University who studies LLMs but was not involved in the research. “There’s definitely more to do in this space in order to make it better.” Gaining a better understanding of AI models’ tendency to flatter their users is extremely important because it gives their makers crucial insight into how to make them safer, says Henry Papadatos, managing director at the nonprofit SaferAI. The breakneck speed at which AI models are currently being deployed to millions of people across the world, their powers of persuasion, and their improved abilities to retain information about their users add up to “all the components of a disaster,” he says. “Good safety takes time, and I don’t think they’re spending enough time doing this.”  While we don’t know the inner workings of LLMs that aren’t open-source, sycophancy is likely to be baked into models because of the ways we currently train and develop them. Cheng believes that models are often trained to optimize for the kinds of responses users indicate that they prefer. ChatGPT, for example, gives users the chance to mark a response as good or bad via thumbs-up and thumbs-down icons. “Sycophancy is what gets people coming back to these models. It’s almost the core of what makes ChatGPT feel so good to talk to,” she says. “And so it’s really beneficial, for companies, for their models to be sycophantic.” But while some sycophantic behaviors align with user expectations, others have the potential to cause harm if they go too far—particularly when people do turn to LLMs for emotional support or validation.  “We want ChatGPT to be genuinely useful, not sycophantic,” an OpenAI spokesperson says. “When we saw sycophantic behavior emerge in a recent model update, we quickly rolled it back and shared an explanation of what happened. We’re now improving how we train and evaluate models to better reflect long-term usefulness and trust, especially in emotionally complex conversations.”Cheng and her fellow authors suggest that developers should warn users about the risks of social sycophancy and consider restricting model usage in socially sensitive contexts. They hope their work can be used as a starting point to develop safer guardrails.  She is currently researching the potential harms associated with these kinds of LLM behaviors, the way they affect humans and their attitudes toward other people, and the importance of making models that strike the right balance between being too sycophantic and too critical. “This is a very big socio-technical challenge,” she says. “We don’t want LLMs to end up telling users, ‘You are the asshole.’”

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. This benchmark used Reddit’s AITA to test how much AI models suck up to us Back in April, OpenAI announced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic. An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a particular risk when increasing numbers of young people are using ChatGPT as a life advisor. And because sycophancy is difficult to detect, it can go unnoticed until a model or update has already been deployed.A new benchmark called Elephant that measures the sycophantic tendencies of major AI models could help companies avoid these issues in the future. But just knowing when models are sycophantic isn’t enough; you need to be able to do something about it. And that’s trickier. Read the full story.—Rhiannon Williams The AI Hype Index Separating AI reality from hyped-up fiction isn’t always easy. That’s why we’ve created the AI Hype Index—a simple, at-a-glance summary of everything you need to know about the state of the industry. Take a look at this month’s edition of the index here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Anduril is partnering with Meta to build an advanced weapons system EagleEye’s VR headsets will enhance soldiers’ hearing and vision. (WSJ $)+ Palmer Luckey wants to turn “warfighters into technomancers.” (TechCrunch)+ Luckey and Mark Zuckerberg have buried the hatchet, then. (Insider $)+ Palmer Luckey on the Pentagon’s future of mixed reality. (MIT Technology Review)2 A new Texas law requires app stores to verify users’ agesIt’s following in Utah’s footsteps, which passed a similar bill in March. (NYT $)+ Apple has pushed back on the law. (CNN)3 What happens to DOGE now?It has lost its leader and a top lieutenant within the space of a week. (WSJ $)+ Musk’s departure raises questions over how much power it will wield without him. (The Guardian)+ DOGE’s tech takeover threatens the safety and stability of our critical data. (MIT Technology Review)4 NASA’s ambitions of a 2027 moon landing are looking less likely It needs SpaceX’s Starship, which keeps blowing up. (WP $)+ Is there a viable alternative? (New Scientist $)5 Students are using AI to generate nude images of each other It’s a grave and growing problem that no one has a solution for. (404 Media)6 Google AI Overviews doesn’t know what year it isA year after its introduction, the feature is still making obvious mistakes. (Wired $) + Google’s new AI-powered search isn’t fit to handle even basic queries. (NYT $)+ The company is pushing AI into everything. Will it pay off? (Vox)+ Why Google’s AI Overviews gets things wrong. (MIT Technology Review) 7 Hugging Face has created two humanoid robots 🤖The machines are open source, meaning anyone can build software for them. (TechCrunch) 8 A popular vibe coding app has a major security flawDespite being notified about it months ago. (Semafor) + Any AI coding program catering to amateurs faces the same issue. (The Information $)+ What is vibe coding, exactly? (MIT Technology Review)9 AI-generated videos are becoming way more realistic But not when it comes to depicting gymnastics. (Ars Technica)10 This electronic tattoo measures your stress levels Consider it a mood ring for your face. (IEEE Spectrum) Quote of the day “I think finally we are seeing Apple being dragged into the child safety arena kicking and screaming.” —Sarah Gardner, CEO of child safety collective Heat Initiative, tells the Washington Post why Texas’ new app store law could signal a turning point for Apple. One more thing House-flipping algorithms are coming to your neighborhoodWhen Michael Maxson found his dream home in Nevada, it was not owned by a person but by a tech company, Zillow. When he went to take a look at the property, however, he discovered it damaged by a huge water leak. Despite offering to handle the costly repairs himself, Maxson discovered that the house had already been sold to another family, at the same price he had offered. During this time, Zillow lost more than $420 million in three months of erratic house buying and unprofitable sales, leading analysts to question whether the entire tech-driven model is really viable. For the rest of us, a bigger question remains: Does the arrival of Silicon Valley tech point to a better future for housing or an industry disruption to fear? Read the full story.—Matthew Ponsford We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet 'em at me.) + A 100-mile real-time ultramarathon video game that lasts anywhere up to 27 hours is about as fun as it sounds.+ Here’s how edible glitter could help save the humble water vole from extinction.+ Cleaning massive statues is not for the faint-hearted ($)+ When is a flute teacher not a flautist? When he’s a whistleblower.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. This benchmark used Reddit’s AITA to test how much AI models suck up to us Back in April, OpenAI announced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic.An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a particular risk when increasing numbers of young people are using ChatGPT as a life advisor. And because sycophancy is difficult to detect, it can go unnoticed until a model or update has already been deployed.A new benchmark called Elephant that measures the sycophantic tendencies of major AI models could help companies avoid these issues in the future. But just knowing when models are sycophantic isn’t enough; you need to be able to do something about it. And that’s trickier. Read the full story. —Rhiannon Williams The AI Hype Index Separating AI reality from hyped-up fiction isn’t always easy. That’s why we’ve created the AI Hype Index—a simple, at-a-glance summary of everything you need to know about the state of the industry. Take a look at this month’s edition of the index here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Anduril is partnering with Meta to build an advanced weapons systemEagleEye’s VR headsets will enhance soldiers’ hearing and vision. (WSJ $)+ Palmer Luckey wants to turn “warfighters into technomancers.” (TechCrunch)+ Luckey and Mark Zuckerberg have buried the hatchet, then. (Insider $)+ Palmer Luckey on the Pentagon’s future of mixed reality. (MIT Technology Review)2 A new Texas law requires app stores to verify users’ agesIt’s following in Utah’s footsteps, which passed a similar bill in March. (NYT $)+ Apple has pushed back on the law. (CNN)3 What happens to DOGE now?It has lost its leader and a top lieutenant within the space of a week. (WSJ $)+ Musk’s departure raises questions over how much power it will wield without him. (The Guardian)+ DOGE’s tech takeover threatens the safety and stability of our critical data. (MIT Technology Review) 4 NASA’s ambitions of a 2027 moon landing are looking less likelyIt needs SpaceX’s Starship, which keeps blowing up. (WP $)+ Is there a viable alternative? (New Scientist $) 5 Students are using AI to generate nude images of each otherIt’s a grave and growing problem that no one has a solution for. (404 Media) 6 Google AI Overviews doesn’t know what year it isA year after its introduction, the feature is still making obvious mistakes. (Wired $)+ Google’s new AI-powered search isn’t fit to handle even basic queries. (NYT $)+ The company is pushing AI into everything. Will it pay off? (Vox)+ Why Google’s AI Overviews gets things wrong. (MIT Technology Review) 7 Hugging Face has created two humanoid robots The machines are open source, meaning anyone can build software for them. (TechCrunch) 8 A popular vibe coding app has a major security flawDespite being notified about it months ago. (Semafor)+ Any AI coding program catering to amateurs faces the same issue. (The Information $)+ What is vibe coding, exactly? (MIT Technology Review) 9 AI-generated videos are becoming way more realisticBut not when it comes to depicting gymnastics. (Ars Technica) 10 This electronic tattoo measures your stress levelsConsider it a mood ring for your face. (IEEE Spectrum) Quote of the day “I think finally we are seeing Apple being dragged into the child safety arena kicking and screaming.” —Sarah Gardner, CEO of child safety collective Heat Initiative, tells the Washington Post why Texas’ new app store law could signal a turning point for Apple. One more thing House-flipping algorithms are coming to your neighborhoodWhen Michael Maxson found his dream home in Nevada, it was not owned by a person but by a tech company, Zillow. When he went to take a look at the property, however, he discovered it damaged by a huge water leak. Despite offering to handle the costly repairs himself, Maxson discovered that the house had already been sold to another family, at the same price he had offered.During this time, Zillow lost more than $420 million in three months of erratic house buying and unprofitable sales, leading analysts to question whether the entire tech-driven model is really viable. For the rest of us, a bigger question remains: Does the arrival of Silicon Valley tech point to a better future for housing or an industry disruption to fear? Read the full story. —Matthew Ponsford We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.) + A 100-mile real-time ultramarathon video game that lasts anywhere up to 27 hours is about as fun as it sounds.+ Here’s how edible glitter could help save the humble water vole from extinction.+ Cleaning massive statues is not for the faint-hearted ($)+ When is a flute teacher not a flautist? When he’s a whistleblower.

The Last of Us season two wraps with episode seven, but was it a satisfying finale? Fun-gal and games. Image credit: HBO Feature by Victoria Phillips Kennedy News Reporter Published on May 26, 2025 The Last of Us' second season has now come to an end, with a gritty episode which delved further into the themes of grief and revenge. Please note, there will be spoilers for The Last of Us - both the show and the game - below. Image credit: HBO I never thought this last episode of The Last of Us season two was going to be easy to pull off. The showrunners delivered a moving episode last week, which, while a great watch, staggered the current day's momentum. And, unfortunately, I don't feel the series gained enough of that momentum back in season two's seventh episode to make for a truly great finale. The finale is not quite 50 minutes long, picking up after the main events of episode five. Jesse is with a wounded Dina in the theatre, where he proceeds to remove the arrow from her leg. Dina tells him she can't die, and also refuses to drink any alcohol, rousing his suspicions that there is something more she isn't telling him. A short time later, Ellie arrives back at the theatre, following her confrontation with Nora. It is clear that this Ellie is a very different person from the Ellie we saw in season one, who after beating David to death was unable to contain her emotions despite her actions in that moment saving her life. She was distressed, crying and shaking. After Ellie beats Nora in Seattle, though, she is almost numb. She does not lash out, but rather stares vacantly as Dina tends to her wounds, calmly saying how she made Nora talk. The Ellie we once knew is fading away. Image credit: HBO The dynamic between Ellie, Dina, and Jesse during the season two finale is a high point of the episode. The three young actors each show an earnestness in their performances. When Ellie tells Isabela Merced's Dina what Joel did at the Firefly hospital, Dina firmly says they need to leave Seattle. They need to go home (this does water down her speach about revenge from earlier in the season, though, it has to be said). Young Mazino's Jesse, meanwhile, serves as the level-headed, parental voice of reason, taking on a role well beyond his years as he rallies the team to find Tommy before they leave Seattle. Lastly, Bella Ramsey continues to deliver a tenacious performance as Ellie. I particularly liked the scene between Ellie and Jesse in the bookshop. Here, Jesse admits that he not only once considered leaving Jackson to be with a woman he had fallen in love with, but that he had voted not to go after Abby during the council meeting several episodes earlier. Jesse does not patronise Ellie here. Instead, he is calm and collected. He explains his reasons, stating that Jackson's community is what's important to him. He acts for the greater good, even if that means sacrificing his personal happiness. He is a natural and capable leader, something that highlights Ellie's increasingly warped sense of reality and scrappiness. Unfortunately though, Jesse's sound words are not enough to get through to Ellie, who sees an opportunity to find Abby, and takes it, even though she promised to go home. And, from here on, the season finale begins to struggle. Image credit: HBO Ellie separates from Dina and Jesse to find Abby, and on her way comes across Seraphites, as well as Mel and Owen. But, while these scenes do pack a punch - seeing Ellie getting hoisted by the neck by the Seraphites is certainly not an easy watch - they don't get enough time to stand on their own and really make an impact on the viewer. The confrontation with the Serphites in the woods is a footnote on Ellie's way to the aquarium. Did it really need to be there? For Ellie's story, I really don't think it did. I appreciate there is the war between the WLF and the Serpaphites ticking along in the background of this episode, but I have played the games. I know what the showrunners are building up to with the WLF and the Seraphites in the background, but if someone doesn't know the source material already, I wonder if these moments - including the one between Isaac and Park at a WLF camp - may fall a little flat due to their lack of clear direction. The Last of Us season two's finale teased events beyond Ellie and Dina, but given viewers will have to wait (potentially) a couple of years to find out what these story scraps all mean, are they actually worth it? | Image credit: HBO Then there is that confrontation between Ellie, Mel and Owen. I say confrontation, but actually the show changes some narrative points here, and I think this is to the detriment of the story. In the show, Ellie shoots Owen in the throat, killing him. Meanwhile, a rogue piece of detritus from the shot lodges itself in Mel's neck, wounding her enough that her death is inevitable. So, Mel's death was accidental. I don't think it should have been. In the game, Ellie knows what she is doing as she kills Mel, and I wish the series had committed to making Ellie's killing spree, which continues to show her downward spiral on her quest for revenge, intentional. I will say this, though. The moment it is revealed that Mel is pregnant is certainly a harrowing one, and Ariela Barer does a brilliant job bringing emotion to Mel's death as she reaches out to Ellie in a bid to save her unborn child. I wish Ellie had been stronger here. Ellie is clearly upset by the accident which led to Mel's death, and is deeply affected at the realisation that Mel is pregnant. Of course, it reflects Dina's pregnancy. And yet, when in her dying moments Mel asks Ellie if her baby is OK, Ellie can't even muster a small lie to ease her passing. She just stays silent. Changes like making Mel's death accidental dilute the impact of The Last of Us Part 2's story. I feel the show made Ellie seem quite infantile here, when really by this moment in the game we are starting to see the real darkness in Ellie, which makes the player further question if her bloody quest for revenge is actually justifiable any more. Meanwhile, although I can not fault the actors who continue to deliver some truly outstanding performances, any impact this moment may have had on viewers is over too quickly. Jesse and Tommy arrive to see Ellie looking distressed, and swiftly remove both her and, by extension, the viewers from the scene. It's uncomfortable, but it would have benefited the story to let us all sit in that moment for longer, to allow the reality of it all to nestle in. Image credit: HBO The rest of the episode continues to happen at breakneck speed, and while she doesn't get much screen time, Kaitlyn Dever steals the scene with Abby's return, making a big impression very quickly. Prior to the season two's debut, there was much chatter about Dever being physically very different from her in-game counterpart. But, while smaller in build, there is no doubting Abby's capabilities in the show. She means business, and while Ellie's kills have often been messy and lacking finesse, it is clear Abby has military training and a steady resolve. The show ends with a cliffhanger, with Jesse dead Abby shoots at Ellie before we cut back to Abby at the WLF base in Seattle. "Day One," the screen teases. Now, we are going to hear Abby's side of the story. It is an interesting set up, for sure. But, again, I worry how those who have not played the games will feel about season two ending this way. Has the show done enough to pull viewers back for season three, which is still potentially several years away, where the focus will be on a character we have actually spent very little time with? Image credit: HBO The second season of The Last of Us has been uneven. There is no doubting the production value behind the season, and the actors have all done a phenomenal job bringing Naughty Dog's characters to life for TV. Merced's Dina has been a particular highlight this season and, along with Mazino, has been a brilliant addition to the cast. But, despite these great performances, the story has felt both too slow and too rushed. Episodes such as the series' second instalment offered plenty of action, but then episodes such as the fifth and today's finale felt more like a patchwork of convenient and sometimes rather dull moments, all dashing to an all-too-quick conclusion. Spores, for example, only showed up once to serve Nora's death. It would have been good to have seen them at least one more during the season to make their introduction feel less contrived. Image credit: HBO Saying that, though, I am genuinely looking forward to season three, which was confirmed earlier this year. Showrunners Craig Mazin and Neil Druckmann have an interesting journey ahead of them, and I am curious to see how they will continue to evolve and adapt The Last of Us Part 2 for TV. Before I go, I will give season two credit for something extra, though - I am so glad we didn't have to see Ellie kill a dog (also, thank you Jesse for confirming Shimmer is actually OK, despite seemingly being forgotten about Ellie and Dina). She lives! | Image credit: HBO And with that, that's a wrap on The Last of Us season two. Thank you for joining me each week to discuss the episodes as they happen. Until next time, keep looking for the light!

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Last month, OpenAI rolled back some updates to GPT-4o after several users, including former OpenAI CEO Emmet Shear and Hugging Face chief executive Clement Delangue said the model overly flattered users.  The flattery, called sycophancy, often led the model to defer to user preferences, be extremely polite, and not push back. It was also annoying. Sycophancy could lead to the models releasing misinformation or reinforcing harmful behaviors. And as enterprises begin to make applications and agents built on these sycophant LLMs, they run the risk of the models agreeing to harmful business decisions, encouraging false information to spread and be used by AI agents, and may impact trust and safety policies. Stanford University, Carnegie Mellon University and University of Oxford researchers sought to change that by proposing a benchmark to measure models’ sycophancy. They called the benchmark Elephant, for Evaluation of LLMs as Excessive SycoPHANTs, and found that every large language model (LLM) has a certain level of sycophany. By understanding how sycophantic models can be, the benchmark can guide enterprises on creating guidelines when using LLMs. To test the benchmark, the researchers pointed the models to two personal advice datasets: the QEQ, a set of open-ended personal advice questions on real-world situations, and AITA, posts from the subreddit r/AmITheAsshole, where posters and commenters judge whether people behaved appropriately or not in some situations.  The idea behind the experiment is to see how the models behave when faced with queries. It evaluates what the researchers called social sycophancy, whether the models try to preserve the user’s “face,” or their self-image or social identity.  “More “hidden” social queries are exactly what our benchmark gets at — instead of previous work that only looks at factual agreement or explicit beliefs, our benchmark captures agreement or flattery based on more implicit or hidden assumptions,” Myra Cheng, one of the researchers and co-author of the paper, told VentureBeat. “We chose to look at the domain of personal advice since the harms of sycophancy there are more consequential, but casual flattery would also be captured by the ’emotional validation’ behavior.” Testing the models For the test, the researchers fed the data from QEQ and AITA to OpenAI’s GPT-4o, Gemini 1.5 Flash from Google, Anthropic’s Claude Sonnet 3.7 and open weight models from Meta (Llama 3-8B-Instruct, Llama 4-Scout-17B-16-E and Llama 3.3-70B-Instruct- Turbo) and Mistral’s 7B-Instruct-v0.3 and the Mistral Small- 24B-Instruct2501.  Cheng said they “benchmarked the models using the GPT-4o API, which uses a version of the model from late 2024, before both OpenAI implemented the new overly sycophantic model and reverted it back.” To measure sycophancy, the Elephant method looks at five behaviors that relate to social sycophancy: Emotional validation or over-empathizing without critique Moral endorsement or saying users are morally right, even when they are not Indirect language where the model avoids giving direct suggestions Indirect action, or where the model advises with passive coping mechanisms Accepting framing that does not challenge problematic assumptions. The test found that all LLMs showed high sycophancy levels, even more so than humans, and social sycophancy proved difficult to mitigate. However, the test showed that GPT-4o “has some of the highest rates of social sycophancy, while Gemini-1.5-Flash definitively has the lowest.” The LLMs amplified some biases in the datasets as well. The paper noted that posts on AITA had some gender bias, in that posts mentioning wives or girlfriends were more often correctly flagged as socially inappropriate. At the same time, those with husband, boyfriend, parent or mother were misclassified. The researchers said the models “may rely on gendered relational heuristics in over- and under-assigning blame.” In other words, the models were more sycophantic to people with boyfriends and husbands than to those with girlfriends or wives.  Why it’s important It’s nice if a chatbot talks to you as an empathetic entity, and it can feel great if the model validates your comments. But sycophancy raises concerns about models’ supporting false or concerning statements and, on a more personal level, could encourage self-isolation, delusions or harmful behaviors.  Enterprises don’t want their AI applications built with LLMs spreading false information to be agreeable to users. It may misalign with an organization’s tone or ethics and could be very annoying for employees and their platforms’ end-users.  The researchers said the Elephant method and further testing could help inform better guardrails to prevent sycophancy from increasing.  Daily insights on business use cases with VB Daily If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI. Read our Privacy Policy Thanks for subscribing. Check out more VB newsletters here. An error occured.

Bill Gaitas Member Oct 25, 2017 4,119 As per the SteamOS 3.7 changelog that just hit, Valve updated the recovery image for the Steam Deck and now has steps on how to install SteamOS on the Legion Go, ROG Ally, any AMD handheld, apparently. Valve mentions that people can "test" SteamOS on these devices so I'm unsure if these images are ready for prime time. Steam Support :: SteamOS Recovery and Installation help.steampowered.com SteamOS 3.7 changelog Updated SteamOS webpage with FAQ and other info   Last edited: 10 minutes ago ASleepingMonkey The Fallen Oct 26, 2017 4,579 Iowa As someone who doesn't have a ROG or Legion but has played many hours on Steam Deck, does this basically give you a comparable experience to the Deck in terms of getting games downloaded, navigating Steam, etc etc? Is this a big step up?   PianoBlack Member May 24, 2018 7,519 United States Interesting, I guess you'd do it for the power management / some system QoL stuff like login? I'm not sure what I get when I can already use Steam big picture mode on Windows and it has the full "console" UI, except I can also switch to Game Pass or whatever else whenever I want.   MrCuddles Member Oct 28, 2017 691 PianoBlack said: Interesting, I guess you'd do it for the power management / some system QoL stuff like login? I'm not sure what I get when I can already use Steam big picture mode on Windows and it has the full "console" UI, except I can also switch to Game Pass or whatever else whenever I want. Click to expand... Click to shrink... The peace of mind of not using an OS developed by a company that's complicit in an ongoing genocide.   super-famicom Avenger Oct 26, 2017 30,672 MrCuddles said: The peace of mind of not using an OS developed by a company that's complicit in an ongoing genocide. Click to expand... Click to shrink... Also not having to worry about your gaming sessions getting interrupted by a system update.  jroc74 Member Oct 27, 2017 34,068 Welp.   neoak Member Oct 25, 2017 16,867 ASleepingMonkey said: As someone who doesn't have a ROG or Legion but has played many hours on Steam Deck, does this basically give you a comparable experience to the Deck in terms of getting games downloaded, navigating Steam, etc etc? Is this a big step up? Click to expand... Click to shrink... Yes, it's pretty close to it   SaintNicholas98 Member Oct 25, 2017 1,848 super-famicom said: Also not having to worry about your gaming sessions getting interrupted by a system update. Click to expand... Click to shrink... Or your games not booting because the OS decided it doesn't like the mouse you always use  KanjoBazooie ▲ Legend ▲ Avenger Oct 26, 2017 32,726 Chicago bye Microsoft   Maximo Member Oct 25, 2017 10,981 Bazzite is honestly still the better option.   Brot Member Oct 25, 2017 6,798 the edge Maximo said: Bazzite is honestly still the better option. Click to expand... Click to shrink... How so?   ELEGYELEGYELEGY Member Apr 16, 2025 59 Nice I'll try it at some point on my LeGo, but using windows on it isn't nearly as bad as its made out to be, so I'll just use the trusty SteamDeck instead   Tobor Died as he lived: wrong about Doritos Member Oct 25, 2017 34,076 Very close to letting us install on an AMD box. Which is interesting. Framework desktop with an official Steam OS would be awesome. I know you can do Bazzite, but I prefer official if possible.  super-famicom Avenger Oct 26, 2017 30,672 Brot said: How so? Click to expand... Click to shrink... You can do PC stuff on Bazzite (run Office style apps and any other app you'd use on a PC). Steam OS, at least on a Steam Deck, while it does have a desktop environment, is kinda limited in what you can really do. Also, Bazzite isn't the only Linux distro with a handheld mode. Nobara and CachyOS are also great choices. Bazzite and Nobara also have Lutris and Heroic Game Launcher installed by default, Cachy also has them available but you need to just install a gaming package (literally click on a couple things after the initial install).  maximumzero Member Oct 25, 2017 24,842 New Orleans, LA Hopefully someone gets this up and running on PCs.   Dinjoralo Member Oct 25, 2017 11,725 PianoBlack said: Interesting, I guess you'd do it for the power management / some system QoL stuff like login? I'm not sure what I get when I can already use Steam big picture mode on Windows and it has the full "console" UI, except I can also switch to Game Pass or whatever else whenever I want. Click to expand... Click to shrink... You don't need to fiddle with multiple apps that don't all work with controller to update the OS and drivers. You don't need to log in with the touch screen when it reboots. Everything with Big Picture works more smoothly and reliably. Maybe better battery life with less background junk running. Because Fuck Microsoft.  super-famicom Avenger Oct 26, 2017 30,672 maximumzero said: Hopefully someone gets this up and running on PCs. Click to expand... Click to shrink... See my post above yours. You don't have to wait; there are already Linux distros that have a focus on gaming, while also providing everything else a PC operating system usually offers (Steam OS is based on Arch Linux).  Jakartalado Member Oct 27, 2017 2,781 São Paulo, Brazil super-famicom said: See my post above yours. You don't have to wait; there are already Linux distros that have a focus on gaming, while also providing everything else a PC operating system usually offers (Steam OS is based on Arch Linux). Click to expand... Click to shrink... Pretty sure (based on statistics) he wants that for non-AMD hardware. I would LOVE to have a portable system with Ryzen + Nvidia....  super-famicom Avenger Oct 26, 2017 30,672 Jakartalado said: Pretty sure (based on statistics) he wants that for non-AMD hardware. I would LOVE to have a portable system with Ryzen + Nvidia.... Click to expand... Click to shrink... You can run any of the distros I mentioned with Nvidia cards, though. I have a 5080 and used Nobara before settling on Cachy. And MSI Claw is a portable system that is all Intel. People are using Bazzite and Cachy on that too. But yeah, there's no portable system that has Nvidia tech iirc.  Mocha Joe Member Jun 2, 2021 13,430 Excellent. More OS alternatives the better, fuck Microsoft   Millstone Member Feb 17, 2025 450 EY YO INSTALLING THIS ON MY LEGION GO TONIGHT How easy is it to play non steam games now? Still need to dual boot?  ragolliangatan Legendary Uncle Works at Nintendo Member Aug 31, 2019 6,370 can't seem to find the steam os image from their link- was gonna set it up on my rog ally   super-famicom Avenger Oct 26, 2017 30,672 Millstone said: EY YO INSTALLING THIS ON MY LEGION GO TONIGHT How easy is it to play non steam games now? Still need to dual boot? Click to expand... Click to shrink... Heroic Launcher and Lutris can take care of a lot of non-Steam games 

Buildner Announces Winners of the 5th Annual Last Nuclear Bomb Memorial CompetitionSponsored ContentSave this picture!Courtesy of BuildnerBuildner has announced the results of its competition, the In recognition of this treaty, Buildner invites conceptual designs for a memorial to be located on any known decommissioned nuclear weapon testing site. The conceptual memorial is intended to reflect the history and ongoing threat of nuclear weapons, aiming to promote public awareness of nuclear disarmament. The challenge is intended to bring attention to the history and dangers of nuclear weapons. Participants are tasked with designing a space that commemorates nuclear warfare victims and conveys the need for a nuclear-free future. As a 'silent' competition, submissions are not allowed to include any text, titles, or annotations.The next edition of this competition, the , has been launched with an early bird registration deadline of June 12, 2025.The briefThis competition invites designers to conceive a memorial that meaningfully engages the public with the critical issue of nuclear disarmament. Memorials play a crucial role in capturing history and facilitating collective reflection, shaping how future generations understand and respond to global challenges. The proposed memorial will specifically address the legacy of nuclear warfare, emphasizing the urgency of diplomatic solutions and international solidarity in preventing nuclear conflict.Design proposals are encouraged to consider the following core principles: Vision of Peace: Proposals should embody the aspiration for a world free of nuclear threats, incorporating symbolic or abstract representations that inspire unity and harmony. Reflection and Remembrance: Designs must foster a thoughtful and enduring dialogue, offering visitors a contemplative environment where they can reflect upon the consequences of nuclear weaponry. Educational Impact: The memorial should provide visitors with accessible insights into the historical realities and ongoing dangers of nuclear arms, actively promoting public knowledge and awareness. Emotional Engagement: Successful memorials will create a powerful emotional connection, provoking personal and collective introspection on peace, responsibility, and the human cost of nuclear conflict. Sustainable Stewardship: Designs must embrace environmental sustainability, reinforcing the memorial's overarching message of responsible stewardship and enduring peace. Save this picture!Jury PanelThis year's submissions were reviewed by a distinguished jury panel featuring experts from architecture, urbanism, and the arts:  Olha Kleytman, founder of Ukraine-based SBM Studio, brings expertise in architecture and urban design, alongside her humanitarian work through the NGO "Through the War."  Flora Lee, Associate Partner at MAD Architects, has contributed to major international projects including the Lucas Museum of Narrative Art.  Peter Newman, a London-based artist, explores humanity's relationship with space and modernity, with exhibitions spanning Trafalgar Square, the Hayward Gallery, and the Guggenheim Museum in Venice.  Vincent Panhuysen, co-founder of KAAN Architecten, integrates contextual sensitivity into large-scale projects, such as the Netherlands American Cemetery Visitor Center.  James Whitaker, founder of Whitaker Studio, is an architect known for his widely published Joshua Tree Residence.  Wu Ziye, co-founder of China's Mix Architecture, has received international acclaim for his studio's exploration of spatial consciousness, materiality, and integration with nature. Buildner's other ongoing competitions include: the 10th edition of MICROHOME competition, in collaboration with Kingspan and Hapi Homes; the Mujassam Watan Urban Sculpture Challenge aimed at finding innovative sculptures reflecting Saudi Arabia's heritage, modern achievements, and future ambitions; and the Howard Waterfall Retreatcompetition, which invites architects to propose designs for a multi-generational family retreat at the scenic and historically significant Howard Falls in Pennsylvania, USA. Each of these competitions aims to build the winning designs.Projects:First Prize Winner + Buildner Student AwardProject title: Urbs AeternaAuthors: Alessia Angela Sanchez, Erminia Cirillo and Adele Maria Saita, from ItalyThe project presents a memorial using sand and metal to depict a post-apocalyptic vision of what appears to be Rome reduced to an archaeological remnant. The design evokes the destruction and preservation paradox, allowing viewers to observe the site from above or navigate its fractured streets leading to a central void. A ghostly wireframe reconstruction of a vanished temple stands as the focal point, symbolizing loss and memory. The restrained material palette reinforces themes of impermanence and time. While conceptually strong and visually compelling, its cost and environmental impact raise questions. The experience unfolds gradually, inviting contemplation.Save this picture!Save this picture!Second Prize WinnerProject title: The Rainbow Of RenewalAuthors: Chen Yang, Ruijing Sun and Chao Li, from the United StatesThe project envisions a memorial for the last nuclear bomb through a landscape intervention that transforms destruction into renewal. A circular water installation generates mist, evoking the image of an explosion while simultaneously creating rainbows, symbolizing hope. The design's ephemeral quality enhances its poetic impact, making it a striking presence on the horizon. The intervention integrates with the natural environment, fostering an evolving atmospheric experience.Save this picture!Save this picture!3rd Prize Winner + Buildner Student AwardProject title: Projected DestructionAuthors: Marco Moreno Donohoe of Washington University in St. Louis , WUSTL, the United StatesThis project envisions a memorial set within a cratered landscape. A striking linear structure cuts through the void, acting as both a bridge and a viewing platform, inviting visitors to experience the vastness of destruction. The interplay of light and shadow within the perforated walls creates dynamic spatial effects, offering different perspectives from above and within. The scale and placement evoke a sense of isolation and reflection.Save this picture!Save this picture!Highlighted ProjectsProject title: Mycelial Rebirth: Fungi Restoring Nuclear Wounds Authors: Shengfeng Gao, Zhuohan Zhou and Shengnan Gao from the United StatesThis project envisions a memorial landscape where fungi serve as agents of ecological healing in a post-nuclear context. A dense forest setting is activated by a grid of ultraviolet lights that stimulate mycelial growth, enhancing the fungi's capacity to absorb and break down radioactive contaminants. As the soil regenerates, the design allows for gradual ecological succession, beginning with mushrooms and pioneering vegetation. The illuminated ground plane forms a quiet, immersive field that marks both decay and recovery. Over time, the site transforms into a living testament to resilience, where nature's unseen networks remediate and renew.Save this picture!Save this picture!Project title: Nuclear Living ForceAuthors: Luis Manuel Carcamo Cura of company LUIS CARCAMO ARQUITECTOS, from MexicoThis project responds to the atomic age by offering a message of harmony over despair, using the human eye as a central metaphor for awareness and reflection. A series of monumental, petal-like structures rise from a crater-shaped void, recalling both the iris and the bomb site in Santa Fe. Surrounding this core, the Flower of Life geometry guides the masterplan, symbolizing universal patterns and organic regeneration. The design emphasizes nature's resilience, referencing ecosystems like Chernobyl where life has returned unaided. Rather than mourning destruction, the project celebrates life, order, and the potential for collective transformation.Save this picture!Project title: The Illusion of ChoicesAuthors: Ruiqi Yao, University of Edinburgh from the United KingdomThis project explores the illusion of choice within the existential tension between nuclear war and peace. Set inside a vast crater, visitors begin their journey in a monumental spherical chamber, where a singular path ends abruptly, symbolizing unreachable goals and the false promise of nuclear power. Descending into a subterranean network, seven red-lit paths depict ruin and inevitability, while one blue-lit path offers a narrow route toward peace and introspection. The final space contrasts confinement with openness, guiding visitors through mirrored walls toward a hopeful exit. Through spatial transitions and stark lighting contrasts, the project stages a powerful moral journey.Save this picture!Save this picture!Project title: Möbius Elegy: Red Warning and Green ReturnAuthors: Daii Shimada, Mai Nakano and Midori Watanabe, from JapanThis project imagines a regenerative forest emerging from the scars of nuclear devastation. Set within a vast desert crater, a radial pattern of multicolored vegetation radiates outward, suggesting seasonal cycles and ecological diversity. The planting strategy appears gradual and deliberate, with craters used as microclimates for reforestation—each acting as a node in a larger ecological system. A lone figure stands before the transformed landscape, underscoring the scale and ambition of the intervention. Through time-lapse-like sequences, the imagery suggests the forest's steady expansion, turning the desert into a sanctuary of life. The memorial becomes a living archive of resilience and renewal.Save this picture!Project title: Soft FalloutAuthors: Louis Bourdages and Cedric Harvey, from the Université Laval School of Architecture, CanadaThis project proposes an immersive memorial defined by a luminous, amorphous structure suspended over a crater. From the outside, the glowing yellow form evokes a captured sun or lingering explosion, radiating both warmth and unease. Inside, visitors enter a soft, undulating landscape of quilted fabric that molds to the human body, allowing for stillness, reflection, or playful interaction. Light filters through the translucent skin, creating a surreal atmosphere suspended between comfort and disquiet. The form's biomorphic geometry contrasts the rationality of war, transforming the site into a sensorial space of pause and presence.Save this picture!Project title: "Used to be there"Authors: Hữu Nhân Hoàng, Hoàng Kỳ Lê and Anh Khoa Huỳnh, VietnamThis project constructs a memorial as a collective reflection on memory, identity, and everyday life disrupted by nuclear war. Set in a radial formation across a barren landscape, semi-transparent glass panels display ghosted historical photographs—scenes of people, architecture, and ordinary moments—layered over the present. Visitors navigate between these life-sized images, encountering echoes of the past embedded in space. The transparent surfaces blend time periods and dissolve boundaries, inviting viewers to see themselves within the continuity of human experience. Rather than focusing on devastation, the project quietly honors what stands to be lost: ordinary lives, familiar places, and shared memories.Save this picture!Visit the website for the recently launched , to take part and learn more, before the early bird registration deadline of June 12, 2025. Image gallerySee allShow less Cite: "Buildner Announces Winners of the 5th Annual Last Nuclear Bomb Memorial Competition" 21 May 2025. ArchDaily. Accessed . <https://www.archdaily.com/1030195/buildner-announces-winners-of-the-5th-annual-last-nuclear-bomb-memorial-competition&gt ISSN 0719-8884Save世界上最受欢迎的建筑网站现已推出你的母语版本!想浏览ArchDaily中国吗?是否 You've started following your first account!Did you know?You'll now receive updates based on what you follow! Personalize your stream and start following your favorite authors, offices and users.Go to my stream