David Reger, founder and CEO of Munich-based Neura Robotics, is building humanoid robots — and a reputation with a touch of déjà vu. In the German press, he’s sometimes dubbed the “Young Elon Musk.”  It’s a nickname Reger embraces, despite all of the controversy surrounding the world’s richest man. “For me, it’s a positive, not a negative,” he told TNW in an interview. “I respect how Musk builds companies, how successful he is, how fearless he is to drive things further.” Musk’s politics, Reger continues, aren’t the focus of his admiration. “I’m just thinking about technological advancement and how to move that further and faster, and I admire Musk for that.” Like Musk, Reger has speed on his mind. Founded in 2019, Neura has quickly grown into one of Europe’s best-funded robotics startups, with over 600 employees. It’s already commercialised multiple robots, including a robotic arm for manufacturing and a load-carrying robot. And next month, the company will unveil the third generation of the 4NE-1 robot, which it claims will be the world’s most advanced humanoid.  The 💜 of EU techThe latest rumblings from the EU tech scene, a story from our wise ol' founder Boris, and some questionable AI art. It's free, every week, in your inbox. Sign up now!4NE-1 — as the name implies — is a robot built for anyone. The human-like bot is designed to be equally capable of folding your washing at home as it is stacking boxes in a warehouse. The current version of 4NE-1 is 180cm tall, tips the scales at about 80kg, and can carry items weighing up to 15kg. With a top speed of 3km/h, though, it’s a bit of a slowcoach. Its performance is set to improve in the third generation — we’ll have to wait to find out. What sets the humanoid apart, according to Reger, is its cognitive abilities. “It can touch, think, and react in much the same way humans do,” he said.  That’s thanks to a network of sensors and cameras embedded throughout its body. These feed real-time data to an AI system that interprets the environment and makes split-second decisions. The third generation of 4NE-1 will have more of these sensors than other humanoids, Reger said, allowing better data collection and closing the loop between virtual and physical worlds.  While Reger is confident that Neura is building the best humanoid, competition will be fierce. There are hundreds of companies developing human-like robots globally — including Musk’s car firm Tesla. The company is currently developing Optimus, also known as the “Tesla bot.”  Optimus is not dissimilar to Neura’s 4NE-1. Measuring 173cm and weighing 57kg, it’s also designed to be multi-purpose. It can fold washing, water plants, and vacuum, according to a recent demo video. Tesla aims to produce between 5,000 to 12,000 Optimus units this year.  “I see Musk as my only competitor in the segment,” said Reger.  Although Reger admires Musk, he’s wary of the impact his recent antics could have on robotics. He fears the political controversies could set the industry back.  “For humanoids to be accepted in people’s homes and work lives, trust is everything,” said Reger. “So he should be careful with what he is doing.” Story by Siôn Geschwindt Siôn is a freelance science and technology reporter, specialising in climate and energy. From nuclear fusion breakthroughs to electric vehic (show all) Siôn is a freelance science and technology reporter, specialising in climate and energy. From nuclear fusion breakthroughs to electric vehicles, he's happiest sourcing a scoop, investigating the impact of emerging technologies, and even putting them to the test. He has five years of journalism experience and holds a dual degree in media and environmental science from the University of Cape Town, South Africa. When he's not writing, you can probably find Siôn out hiking, surfing, playing the drums or catering to his moderate caffeine addiction. You can contact him at: sion.geschwindt [at] protonmail [dot] com Get the TNW newsletter Get the most important tech news in your inbox each week. Also tagged with

While large reasoning models (LRMs) have shown impressive capabilities in short-context reasoning through reinforcement learning (RL), these gains do not generalize well to long-context scenarios. Applications such as multi-document QA, research synthesis, and legal or financial analysis require models to process and reason over sequences exceeding 100K tokens. However, RL optimization in such regimes is plagued by slower reward convergence, unstable policy updates due to KL divergence fluctuations, and reduced exploration resulting from entropy collapse. These bottlenecks reveal a fundamental gap in transitioning LRMs from short-context proficiency to long-context generalization. QwenLong-L1: A Structured RL Framework for Long-Context Adaptation To address these limitations, the Qwen Research team introduces QwenLong-L1, a novel RL framework designed to adapt LRMs to long-context reasoning tasks. The framework is structured into three key stages: Warm-up Supervised Fine-Tuning (SFT): Provides a stable initialization for the policy model by training on curated question-context-answer triplets, ensuring basic competence in contextual comprehension and answer extraction. Curriculum-Guided Phased Reinforcement Learning: Introduces a staged training process with gradually increasing context lengths. This progression enables the model to incrementally acquire long-context reasoning behaviors without destabilizing policy updates. Difficulty-Aware Retrospective Sampling: Enhances exploration by maintaining and reusing hard examples from previous phases, weighted by their difficulty, to encourage deeper reasoning and robustness across diverse inputs. These stages are complemented by hybrid reward mechanisms—combining rule-based exact match verification with semantic evaluation by a lightweight LLM—ensuring both precision and recall during policy training. Technical Design and Methodological Advantages QwenLong-L1 integrates recent advances in group-relative RL optimization, specifically GRPO and DAPO, to mitigate the computational overhead associated with long-context value estimation: GRPO estimates advantage by normalizing rewards within sampled groups, eliminating the need for a separate value network and encouraging diverse generation patterns. DAPO incorporates mechanisms such as dynamic sampling, overlength penalty shaping, and asymmetric clipping thresholds to prevent entropy collapse and mitigate length biases during training. The reward function is defined as the maximum of two signals: a deterministic rule-based match and a semantic judgment from a compact evaluator model (e.g., Qwen2.5-1.5B). This hybrid approach avoids overfitting to rigid formats while maintaining answer correctness across varied notations and phrasings. Moreover, the framework is optimized via progressive context scaling, where the RL process transitions from 20K-token to 60K-token input lengths in controlled phases, stabilizing training dynamics and facilitating policy generalization. Experimental Results and Benchmark Performance QwenLong-L1 was evaluated on seven long-context document QA benchmarks, including DocMath, Frames, 2WikiMultihopQA, HotpotQA, Musique, NarrativeQA, and Qasper. The 32B variant, QwenLong-L1-32B, demonstrated strong empirical performance: It outperformed baseline models such as R1-Distill-Qwen-32B by 5.1 points and exceeded leading proprietary systems like OpenAI-o3-mini and Qwen3-235B-A22B. Its performance was comparable to Claude-3.7-Sonnet-Thinking, indicating competitive reasoning capabilities under extreme context lengths. Pass@K analysis revealed consistent improvements with increased sampling, achieving a Pass@2 average of 73.7, surpassing DeepSeek-R1 and OpenAI-o1-preview, even at low sampling rates. Ablation studies further validated the individual contributions of SFT, phased RL, and retrospective sampling. Notably, RL played a decisive role in enabling emergent reasoning behaviors such as grounding, subgoal setting, verification, and backtracking—traits not effectively induced by supervised fine-tuning alone. Conclusion QwenLong-L1 represents a systematic approach to equipping LRMs with robust long-context reasoning capabilities through reinforcement learning. Its design effectively bridges the gap between short-context expertise and the demands of information-dense environments by combining supervised initialization, curriculum-driven context scaling, and hybrid evaluation strategies. The framework not only achieves state-of-the-art results across long-context benchmarks but also demonstrates the emergence of interpretable reasoning patterns during training. Check out the Paper, Model on Hugging Face and GitHub Page. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 95k+ ML SubReddit and Subscribe to our Newsletter. Asif RazzaqWebsite |  + postsBioAsif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.Asif Razzaqhttps://www.marktechpost.com/author/6flvq/NVIDIA Releases Llama Nemotron Nano 4B: An Efficient Open Reasoning Model Optimized for Edge AI and Scientific TasksAsif Razzaqhttps://www.marktechpost.com/author/6flvq/A Coding Implementation to Build an AI Agent with Live Python Execution and Automated ValidationAsif Razzaqhttps://www.marktechpost.com/author/6flvq/Step-by-Step Guide to Build a Customizable Multi-Tool AI Agent with LangGraph and Claude for Dynamic Agent CreationAsif Razzaqhttps://www.marktechpost.com/author/6flvq/A Comprehensive Coding Guide to Crafting Advanced Round-Robin Multi-Agent Workflows with Microsoft AutoGen

For nearly 10 years I have written about science and technology and I’ve been an early adopter of new tech for much longer. As a teenager in the mid-1990s I annoyed the hell out of my family by jamming up the phone line for hours with a dial-up modem; connecting to bulletin board communities all over the country.When I started writing professionally about technology in 2016 I was all for our seemingly inevitable transhumanist future. When the chip is ready I want it immediately stuck in my head, I remember saying proudly in our busy office. Why not improve ourselves where we can?Since then, my general view on technology has dramatically shifted. Watching a growing class of super-billionaires erode the democratizing nature of technology by maintaining corporate controls over what we use and how we use it has fundamentally changed my personal relationship with technology. Seeing deeply disturbing philosophical stances like longtermism, effective altruism, and singulartarianism envelop the minds of those rich, powerful men controlling the world has only further entrenched inequality.A recent Black Mirror episode really rammed home the perils we face by having technology so controlled by capitalist interests. A sick woman is given a brain implant connected to a cloud server to keep her alive. The system is managed through a subscription service where the user pays for monthly access to the cognitive abilities managed by the implant. As time passes, that subscription cost gets more and more expensive - and well, it’s Black Mirror, so you can imagine where things end up. Titled 'Common People', the episode is from series 7 of Black MirrorNetflix The enshittification of our digital world has been impossible to ignore. You’re not imagining things, Google Search is getting worse.But until the emergence of AI (or, as we’ll discuss later, language learning models that pretend to look and sound like an artificial intelligence) I’ve never been truly concerned about a technological innovation, in and of itself.A recent article looked at how generative AI tech such as ChatGPT is being used by university students. The piece was authored by a tech admin at New York University and it’s filled with striking insights into how AI is shaking the foundations of educational institutions.Not unsurprisingly, students are using ChatGPT for everything from summarizing complex texts to completely writing essays from scratch. But one of the reflections quoted in the article immediately jumped out at me.When a student was asked why they relied on generative AI so much when putting work together they responded, “You’re asking me to go from point A to point B, why wouldn’t I use a car to get there?”My first response was, of course, why wouldn’t you? It made complete sense.For a second.And then I thought, hang on, what is being lost by speeding from point A to point B in a car? What if the quickest way from point A to point B wasn't the best way to get there?Depositphotos Let’s further the analogy. You need to go to the grocery store. It’s a 10-minute walk away but a three-minute drive. Why wouldn’t you drive?Well, the only benefit of driving is saving time. That’s inarguable. You’ll be back home and cooking up your dinner before the person on foot even gets to the grocery store.Congratulations. You saved yourself about 20 minutes. In a world where efficiency trumps everything this is the best choice. Use that extra 20 minutes in your day wisely.But what are the benefits of not driving, taking the extra time, and walking?First, you have environmental benefits. Not using a car unnecessarily; spewing emissions into the air, either directly from combustion or indirectly for those with electric cars.Secondly, you have health benefits from the little bit of exercise you get by walking. Our stationary lives are quite literally killing us so a 20-minute walk a day is likely to be incredibly positive for your health.But there are also more abstract benefits to be gained by walking this short trip from A to B.Walking connects us to our neighborhood. It slows things down. Helps us better understand the community and environment we are living in. A recent study summarized the benefits of walking around your neighborhood, suggesting the practice leads to greater social connectedness and reduced feelings of isolation.So what are we losing when we use a car to get from point A to point B? Potentially a great deal.But let’s move out of abstraction and into the real world.An article in the Columbia Journalism Review asked nearly 20 news media professionals how they were integrating AI into their personal workflow. The responses were wildly varied. Some journalists refused to use AI for anything more than superficial interview transcription, while others use it broadly, to edit text, answer research questions, summarize large bodies of science text, or search massive troves of data for salient bits of information.In general, the line almost all those media professionals shared was they would never explicitly use AI to write their articles. But for some, almost every other stage of the creative process in developing a story was fair game for AI assistance.I found this a little horrifying. Farming out certain creative development processes to AI felt not only ethically wrong but also like key cognitive stages were being lost, skipped over, considered unimportant.I’ve never considered myself to be an extraordinarily creative person. I don’t feel like I come up with new or original ideas when I work. Instead, I see myself more as a compiler. I enjoy finding connections between seemingly disparate things. Linking ideas and using those pieces as building blocks to create my own work. As a writer and journalist I see this process as the whole point.A good example of this is a story I published in late 2023 investigating the relationship between long Covid and psychedelics. The story began earlier in the year when I read an intriguing study linking long Covid with serotonin abnormalities in the gut. Being interested in the science of psychedelics, and knowing that psychedelics very much influence serotonin receptors, I wondered if there could be some kind of link between these two seemingly disparate topics.The idea sat in the back of my mind for several months, until I came across a person who told me they had been actively treating their own long Covid symptoms with a variety of psychedelic remedies. After an expansive and fascinating interview I started diving into different studies looking to understand how certain psychedelics affect the body, and whether there could be any associations with long Covid treatments.Eventually I stumbled across a few compelling associations. It took weeks of reading different scientific studies, speaking to various researchers, and thinking about how several discordant threads could be somehow linked.Could AI have assisted me in the process of developing this story?No. Because ultimately, the story comprised an assortment of novel associations that I drew between disparate ideas all encapsulated within the frame of a person’s subjective experience.And it is this idea of novelty that is key to understanding why modern AI technology is not actually intelligence but a simulation of intelligence. LLMs are a sophisticated language imitator, delivering responses that resemble what they think a response would look likeDepositphotos ChatGPT, and all the assorted clones that have emerged over the last couple of years, are a form of technology called LLMs (large language models). At the risk of enraging those who actually work in this mind-bendingly complex field, I’m going to dangerously over-simplify how these things work.It’s important to know that when you ask a system like ChatGPT a question it doesn’t understand what you are asking it. The response these systems generate to any prompt is simply a simulation of what it computes a response would look like based on a massive dataset.So if I were to ask the system a random question like, “What color are cats?”, the system would scrape the world’s trove of information on cats and colors to create a response that mirrors the way most pre-existing text talks about cats and colors. The system builds its response word by word, creating something that reads coherently to us, by establishing a probability for what word should follow each prior word. It’s not thinking, it’s imitating.What these generative AI systems are spitting out are word salad amalgams of what it thinks the response to your prompt should look like, based on training from millions of books and webpages that have been previously published.Setting aside for a moment the accuracy of the responses these systems deliver, I am more interested (or concerned) with the cognitive stages that this technology allows us to skip past.For thousands of years we have used technology to improve our ability to manage highly complex tasks. The idea is called cognitive offloading, and it’s as simple as writing something down on a notepad or saving a contact number on your smartphone. There are pros and cons to cognitive offloading, and scientists have been digging into the phenomenon for years.As long as we have been doing it, there have been people criticizing the practice. The legendary Greek philosopher Socrates was notorious for his skepticism around the written word. He believed knowledge emerged through a dialectical process so writing itself was reductive. He even went so far as to suggest (according to his student Plato, who did write things down) that writing makes us dumber. “For this invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them. You have invented an elixir not of memory, but of reminding; and you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise.” Wrote Plato, quoting Socrates Almost every technological advancement in human history can be seen to be accompanied by someone suggesting it will be damaging. Calculators have destroyed our ability to properly do math. GPS has corrupted our spatial memory. Typewriters killed handwriting. Computer word processors killed typewriters. Video killed the radio star.And what have we lost? Well, zooming in on writing, for example, a 2020 study claimed brain activity is greater when a note is handwritten as opposed to being typed on a keyboard. And then a 2021 study suggested memory retention is better when using a pen and paper versus a stylus and tablet. So there are certainly trade-offs whenever we choose to use a technological tool to offload a cognitive task.There’s an oft-told story about gonzo journalist Hunter S. Thompson. It may be apocryphal but it certainly is meaningful. He once said he sat down and typed out the entirety of The Great Gatsby, word for word. According to Thompson, he wanted to know what it felt like to write a great novel. Thompson was infamous for writing everything on typewriters, even when computers emerged in the 1990sPublic Domain I don’t want to get all wishy-washy here, but these are the brass tacks we are ultimately falling on. What does it feel like to think? What does it feel like to be creative? What does it feel like to understand something?A recent interview with Satya Nadella, CEO of Microsoft, reveals how deeply AI has infiltrated his life and work. Not only does Nadella utilize nearly a dozen different custom-designed AI agents to manage every part of his workflow – from summarizing emails to managing his schedule – but he also uses AI to get through podcasts quickly on his way to work. Instead of actually listening to the podcasts he has transcripts uploaded to an AI assistant who he then chats to about the information while commuting.Why listen to the podcast when you can get the gist through a summary? Why read a book when you can listen to the audio version at X2 speed? Or better yet, watch the movie? Or just read a Wikipedia entry. Or get AI to summarize the wikipedia entry.I’m not here to judge anyone on the way they choose to use technology. Do what you want with ChatGPT. But for a moment consider what you may be skipping over by racing from point A to point B.Sure, you can give ChatGPT a set of increasingly detailed prompts; adding complexity to its summary of a scientific journal or a podcast, but at what point do the prompts get so granular that you may as well read the journal entry itself? If you get generative AI to skim and summarize something, what is it missing? If something was worth being written then surely it is worth being read?If there is a more succinct way to say something then maybe we should say it more succinctly.In a magnificent article for The New Yorker, Ted Chiang perfectly summed up the deep contradiction at the heart of modern generative AI systems. He argues language, and writing, is fundamentally about communication. If we write an email to someone we can expect the person at the other end to receive those words and consider them with some kind of thought or attention. But modern AI systems (or these simulations of intelligence) are erasing our ability to think, consider, and write. Where does it all end? For Chiang it's pretty dystopian feedback loop of dialectical slop. “We are entering an era where someone might use a large language model to generate a document out of a bulleted list, and send it to a person who will use a large language model to condense that document into a bulleted list. Can anyone seriously argue that this is an improvement?” Ted Chiang

Apple's AirPods 4 with active noise cancellation (ANC) just became an even more enticing proposition for those who have been on the fence about picking up a pair. They have dropped to $149, which is $30 off the regular price. That's only about $10 more than the record low and the lowest price we've seen for the AirPods 4 with ANC so far this year. If ANC isn't such a big deal for you (perhaps, like me, you tend to only wear one earbud at a time), you can snap up a set of AirPods 4 without ANC instead. Those will currently run you $119, a discount of $10. We gave the AirPods 4 with ANC a score of 86 in our review. Apple improved the audio quality compared with the previous version, and the earbuds have a better fit than the AirPods 3. We felt that the ANC was pretty effective too. However, the lack of onboard volume controls remains a disappointment. The AirPods 4 use the same H2 chip as the AirPods Pro 2, meaning they share some features with the higher-end model. They support Voice Isolation, Personalized Spatial Audio with dynamic head tracking, Personalized Volume and Adaptive EQ. The ANC-enabled model also has Conversation Awareness, Adaptive Audio and Transparency mode. In addition, the charging case that comes with the ANC version has Qi-compatible wireless charging, as well as a built-in speaker for Find My. However, the AirPods Pro 2's advanced hearing health features aren't present here. Check out our coverage of the best Apple deals for more discounts, and follow @EngadgetDeals on X for the latest tech deals and buying advice.This article originally appeared on Engadget at https://www.engadget.com/deals/apples-airpods-4-with-anc-drop-to-149-for-memorial-day-161120128.html?src=rss

The first observance of what came to be known as Memorial Day was on May 30, 1868, when a Civil War general called on Americans to commemorate the sacrifices of Union soldiers. It was initially called Decoration Day, for the practice of decorating graves with wreaths and flags. And there were so many graves — more than 300,000 men had died on the Union side, and nearly as many for the Confederacy. In total, more died on both sides of the Civil War than in every other US conflict through the Korean War, combined. It wasn’t long, though, before remembrance began to be overshadowed by celebration. Within a year, the New York Times opined the holiday would no longer be “sacred” if parades and speeches became more central than the act of memorializing the dead. Which is precisely what happened, especially after Congress in 1971 fixed Memorial Day as the last Monday in May, making it the perfect launchpad for summer, with an increasingly perfunctory nod to the holiday’s original purpose.The gap between those for whom Memorial Day is a moment of remembrance versus three days of hot dogs and hamburgers will likely only grow in the future, as veterans of previous wars pass away and the divide between America’s all-volunteer military and its civilians deepens. Fewer than 1 percent of the US adult population serves in the military, and those still signing up increasingly come from a small handful of regions and families with a history of military service. (You can include my own family in that ever rarer number: My brother is a retired Army captain who served in Iraq.)With ever-inflating military spending — now nearing $1 trillion, according to one estimate — the footprint of the US military is hardly shrinking, but the number of those who will potentially be called on to give what Abraham Lincoln called the “last full measure of devotion” is.Yet there’s a greater gap embedded in Memorial Day: It’s between those who died as warfighters (to use one of the Pentagon’s terms), and the far greater number around the world who have died not as war’s participants, but as its victims. When civilians die in warThe past is not just a foreign country to us, but a bloody one. From the interpersonal to the international, conflict was a constant throughout much of human history. Between 1500 and 1800, there was hardly a year when great powers weren’t enmeshed in some kind of war. Though war became somewhat less common as we entered the 1900s, it did not become less deadly. Far from it — while the death toll of war in the past was more chiefly concentrated among combatants, the 20th century saw the awful blossoming of total war, where little to no distinction was made between those fighting the war and the civilians on the sidelines, and new weapons enabled mass, indiscriminate killing.Go back to the Civil War, which sits at the junction between battle as it had long been practiced and the greater horror it would become. Over 600,000 soldiers were killed in the conflict, against at least 50,000 civilians, ranging from those killed directly to the many who died in the wake of war, from starvation and disease. That number was terrible, yet in the wars to come, it would only grow.In the First World War, a roughly equal number of combatants and civilians were killed globally — approximately 10 million on each side. In the Second World War, more combatants were killed than in any other conflict in human history, a toll nearing 15 million. Yet for every soldier, sailor, or airman who was killed, nearly one and a half civilians would die, totaling, by one count, almost 40 million. The last of the dead would come in Hiroshima and Nagasaki, when as many as 210,000 people — nearly all of them Japanese civilians — died in the first and so far only atomic bombings. Not only were these new weapons capable of murdering at a vastly larger scale than ever before, but they existed chiefly to threaten the lives of noncombatants. Thankfully, given the weapons militaries now had at their disposal, World War II was the high mark for war deaths. In the decades that followed, deaths in battle for both combatants and civilians sharply declined, minus the occasional spike in conflicts like the Korean and Vietnam Wars. Even with the recent resurgence of conflict, people around the world today are much less likely to die in war than their ancestors, which is one of the most undeniable — if tenuous — markers of our species’ under-appreciated progress.Yet even in this era of comparative peace, civilians still bear the brunt of war when it comes, including when it is fought by the United States. According to Brown University’s Costs of War project, more civilians were likely directly killed in post-9/11 conflicts than fighters on either side — and when the number of indirect deaths from starvation and destruction are included, that gulf only widens. In Ukraine, at least 12,910 civilians have been killed in the war as of March 31, including nearly 700 children, while nearly 31,000 civilians have been injured. In a single large-scale Russian missile attack on April 24, at least nine civilians were killed and 90 were injured, including 12 children.In Gaza, accurately counting the civilian death toll has been all but impossible, but the most recent UN estimates put the number of dead children, women, and elderly people at north of 27,000, with thousands of dead bodies still unidentified. Even those civilians who have escaped death face the real risk of starvation, with Israel only now allowing trickled of aid in after a blockade that has lasted more than two months. And of course, Israel itself lost nearly 700 civilians in the October 7 attacks, while many noncombatants are still held hostage by Hamas and other militant groups.And the ongoing war in Sudan — which has received only a fraction of the global attention of Ukraine and Gaza — has led to horrifying levels of civilian death. Last year Tom Perriello, then the US envoy for Sudan, estimated that at least 150,000 people had died of war-related causes, while 13 million people have been forced to flee their homes.A new kind of Memorial DayThe US has its Memorial Day to honor fallen soldiers, while other countries have their Remembrance Day, their Victory Day. Yet there are only a handful of monuments to honor the countlessly greater number of civilians killed in war.It’s not hard to imagine why. As the shift in perception around the Vietnam Veterans Memorial has shown — from unpatriotic atrocity to a celebrated work of national mourning — we can honor the sacrifice of service members who died in a war, even if we don’t believe in the war. But the death of those who died without a rifle in hand, who died in childhood and infancy, who died because they could not fight and could not be protected, shows war for what it ultimately is: a waste. And we can’t begin to know how to mark the unmarked.America has been a historical exception in many ways, but perhaps no more so than that its civilian citizens have largely escaped the scourge of war. (Though the same, of course, can hardly be said for its Indigenous populations, so long treated as enemy combatants in their own land.) Americans have fought and Americans have died, but at an ever-increasing remove, a distance that grows with each Memorial Day. The general decline of war is one of our great accomplishments as humans, something to be unequivocally celebrated. Perhaps we would feel that more if we gave the deaths of civilians the same honor as that of soldiers — a new kind of Memorial Day that can begin here. A version of this story was initially published in the Future Perfect newsletter. Sign up here to subscribe!Update, May 26, 2025, 8 am ET: This story was first published on May 31, 2023, has been updated to include new data on civilian deaths in Gaza, Israel, Sudan, and Ukraine.You’ve read 1 article in the last monthHere at Vox, we're unwavering in our commitment to covering the issues that matter most to you — threats to democracy, immigration, reproductive rights, the environment, and the rising polarization across this country.Our mission is to provide clear, accessible journalism that empowers you to stay informed and engaged in shaping our world. By becoming a Vox Member, you directly strengthen our ability to deliver in-depth, independent reporting that drives meaningful change.We rely on readers like you — join us.Swati SharmaVox Editor-in-ChiefSee More: