标签：#zed

This is a fascinating explotation of how LLMs fall for prompt injection attacks. It turns out that they learn to recognize the style of text in different role/instruction blocks, and not just the tags. Their conclusion: Role tags were a formatting trick that became the security architecture and the cognitive scaffolding of modern LLMs. We’ve shown that this architecture doesn’t survive into the model’s actual representations, and that such role confusion is linked to prompt injection. Unless LLMs achieve genuine role perception, we think injection defense will remain a perpetual whack-a-mole game. And the continuous nature of role boundaries opens the threat of injections designed to subtly shift LLM states through seemingly innocuous text, legally and at scale...

One universal AI agent sounds convenient. One agent to read tickets, write code, generate tests,...

On April 29, 2026, Nathan Sobo published the Zed 1.0 announcement post on Zed's blog. The post landed on Hacker News at 2,047 points and 663 comments — the highest-engagement HN story in the present cache by a substantial margin. The launch announcement is a milestone marker after five years of development, roughly a million lines of Rust, and a custom GPU-accelerated UI framework called GPUI that the Zed team built from scratch rather than building atop Electron, Chromium, or any other browser engine. The structural argument Zed has been making for the last several years is condensed in one sentence from Sobo's post: "Instead of building Zed like a web page, we built it like a video game, organizing the entire application around feeding data to shaders running on the GPU." The video-game framing is not metaphorical. Zed's editor surface is composited by feeding glyph atlases, syntax-tree-derived color spans, and pane-layout geometry into GPU shaders the way a video-game engine composites its frames. The reason this matters is the reason the Zed team gave for starting over from the Atom era: Atom was built as a fork of Chromium, and the same team that built Atom is the team that spawned Electron. The Atom-Electron-VSCode lineage is, in the historical-causal sense, Zed's own. Sobo's post is unusually direct about the inherited limitation: "Electron eventually became the foundation of VS Code (which today seems to be forked into a new AI code editor every other week). Web technology offered an easy path to shipping flexible software, but it also imposed a ceiling. No matter how hard we worked, we couldn't make Atom better than the platform it was built on." The 1.0 announcement is, in part, a statement that the rebuild from scratch has finally cleared that ceiling. Who built it Zed's three co-founders all worked on Atom at GitHub before founding Zed Industries in 2021. Nathan Sobo led the Atom team from 2011 to 2018; he also co-led Teletype for Atom, one of the first

At least one malware developer is adding text about nuclear and biological weapons to their spyware, in an effort to stop automatic AI analysis. Details : The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The real malware begins after the comment with a try{eval(…)} wrapper around a large character-code array and a ROT-style substitution function. This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware...

With a test being developed at MIT, diagnosing pneumonia and other lung conditions could someday be as easy as breathing into a tube. The test, dubbed PlasmoSniff, is a portable, chip-scale sensor that traps and detects biomarkers, synthetic compounds indicating disease. The idea is that a person would first breathe in nanoparticles that are specially…

MIT engineers have found the first direct evidence that plant seeds can sense sounds in nature: Rice submerged in shallow water germinated 30% to 40% more quickly when exposed to vibrations from water dripping on the surface. They think other types of seeds may respond similarly. When a raindrop hits a puddle’s surface or the…

A technology developed by Professor Sangeeta Bhatia, SM ’93, PhD ’97, and colleagues could offer new hope to the thousands of Americans with chronic liver disease who are waiting for an organ transplant or not strong enough to tolerate one. The liver is involved in regulating blood clotting, removing bacteria from the bloodstream, metabolizing drugs,…

With an adaptable fastener designed at CSAIL, pitching a tent or adjusting the cast for a broken bone could be almost as easy as zipping your coat. The researchers, led by associate professor Stefanie Mueller, were inspired by an abandoned prototype for a three-sided zipper that William Freeman, PhD ’92 (now an MIT professor), patented…

Our hands are the nimblest parts of our bodies, coordinating 34 muscles, 27 joints, and over 100 tendons and ligaments to perform countless nuanced movements and gestures. So far, robots have been notoriously bad at mimicking that dexterity, in part because researchers struggle to capture what is actually going on under our skin in order…

Right now, MIT alumni and friends are voicing their support for: America’s scientific and technological leadership Merit-based admissions and affordable education Advances that increase US health, security, and prosperity Our community is standing up for MIT and its mission to serve the nation and the world. And we need you to join us at this…

The national conversation about the value of education is currently dominated by speculation about the risks and positive potential of AI. Whatever your own perspective on that debate, I hope you’ll be glad to know that MIT is also working on a deeply important but comparatively old-fashioned challenge: American high school students’ startlingly uneven access…

Brian Sietsema has a favorite word. It’s somewhat surprising that he can choose just one. He’s the person spellers rely on to confirm pronunciations and answer questions about the roots of the words they’re given at the Scripps National Spelling Bee—arguably the world’s most prestigious competition of its kind. The story of how the word…

Here’s a problem you probably didn’t solve in school: You’re an ambitious young plumber from Brooklyn in a world inhabited by violent human-size mushrooms called Goombas. The love of your life has been kidnapped, so you embark on a quest to rescue her, venturing through stretches of pipe-filled and monster-­ridden terrain where your only means…

The Argentina v. France final of the 2022 Men’s World Cup in Qatar was shaping up to be one of the most epic games in soccer history. With just 12 minutes remaining in the extra time added to the game to break a tie, the referee had a critical decision to make—and fast. Lionel Messi,…

Fable 5 is the supposed safe version of Anthropic’s Mythos Preview, with guardrails to ensure that it can’t be used to create cyberattacks. Well, that restriction was bypassed within days.

I haven’t thought about the privacy issues surrounding professional athletes and wearables. Wearables present serious privacy issues for “Average Joe” consumers, who are entrusting tech companies to safely store and protect their biometric data. Imagine the stakes for a professional athlete, whose entire livelihood could be affected by a single biometric data point. To give one of many realistic hypotheticals: a basketball player has a terrible game, and the coach wonders if they showed up to the gym hungover. The coach has access to the player’s wearable data, and checks to see when they went to sleep, as well as what their heart rate looked like during the night. Should the player have been out partying before a game? No. Should the coach be able to surveil them? Definitely not...

Dolphins, sharks, turtles, and human workers are all victims of unregulated squid fishing fleets. Another news article . As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered. Blog moderation policy.

On June 9th, Anthropic released its Fable generative AI model. Three days later, the US government classified it as a dangerous munition, and used its export-control authority to prohibit any foreign nationals from accessing it. Unable to differentiate between Americans and foreigners, the company shut off access for everyone. The government’s actions won’t help . The problem isn’t any one particular model; it’s the general trend of increasing AI capabilities. And any real solution requires the sort of collective action that just isn’t possible right now...

At least one malware developer is adding text about nuclear and biological weapons to their spyware, in an effort to stop automatic AI analysis. Details : The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The real malware begins after the comment with a try{eval(…)} wrapper around a large character-code array and a ROT-style substitution function. This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware...

On 14 April, the Trump administration quietly acknowledged the widespread use of AI to automate government processes. The office of management and budget (OMB) disclosed a staggering 3,611 active or planned use cases for AI across the federal government. The list has ballooned by 70% from the one published in the final year of the Biden administration, and includes many disturbing-seeming plans to hand over sensitive governmental functions to AI. Scanning this list, many readers may find many causes for alarm. It represents a transfer of decision processes from human to machine on a massive scale over matters of individual freedom, public health and well-being, nuclear reactor safety and more...