AI 资讯

South Korean chip startup Xcena is betting that AI's real bottleneck is not compute, but memory.

Boston Children’s Hospital uses OpenAI technology to improve patient care, reduce operational burden, and help diagnose more than 40 rare disease cases.

AI training startup Shift wants to clean your home for free. The catch - because, despite what its website says, there's always a catch - is that it will record cleaners as they scrub, vacuum, dust, tidy, and wash, and use that footage to train robots. Shift announced the unusual offer on social media on […]

How much of the content in Reddit is AI generated do you think? submitted by /u/Zealousideal_Can_411 [link] [留言]

Hey everyone, A while ago, we realized a major annoyance: whenever you actually need an AI to summarize a document, write some quick code, or just brainstorm, you're usually on a flight, on the subway, or dealing with terrible cell reception. And bam, ChatGPT won't connect. Plus, there's the growing privacy concern of feeding all your personal data to cloud servers. So, my team and I started tinkering with a question: "What if we just run the AI directly on the phone's hardware?" We've been spending our evenings and weekends for months trying to make this work smoothly, and the result is Cortex AI. The logic is super simple: You download a highly optimized, small-scale local model (from our library) straight to your device. Put your phone in airplane mode, go off the grid—the AI replies entirely locally. Zero data leaves your phone. 100% private. Some real-world use cases we built this for: Coding help or summarizing offline docs while on a long flight. Getting quick answers while traveling abroad without an expensive data roaming plan. Brainstorming private ideas you just don't want OpenAI or Google to scrape. Note: We do have an optional "Online Mode" if you want to connect to massive models like GPT-4 or Claude, but the local offline models are completely free, and that's what we really want to test right now. We're currently trying to gather real user experiences on the local execution side. I'm not here to just spam a link and grab cash; we genuinely want to improve the offline mobile AI space. If anyone frequently travels, camps, or just loves local LLMs, we'd be super grateful if you could test it out. Brutally honest feedback like "runs too slow on my device," "needs X feature," or "this part of the UI makes no sense" is exactly what we need right now :) submitted by /u/Virtual_Ad_6024 [link] [留言]

Hey everyone, A while ago, we realized a major annoyance: whenever you actually need an AI to summarize a document, write some quick code, or just brainstorm, you're usually on a flight, on the subway, or dealing with terrible cell reception. And bam, ChatGPT won't connect. Plus, there's the growing privacy concern of feeding all your personal data to cloud servers. So, my team and I started tinkering with a question: "What if we just run the AI directly on the phone's hardware?" We've been spending our evenings and weekends for months trying to make this work smoothly, and the result is Cortex AI. The logic is super simple: You download a highly optimized, small-scale local model (from our library) straight to your device. Put your phone in airplane mode, go off the grid—the AI replies entirely locally. Zero data leaves your phone. 100% private. Some real-world use cases we built this for: Coding help or summarizing offline docs while on a long flight. Getting quick answers while traveling abroad without an expensive data roaming plan. Brainstorming private ideas you just don't want OpenAI or Google to scrape. Note: We do have an optional "Online Mode" if you want to connect to massive models like GPT-4 or Claude, but the local offline models are completely free, and that's what we really want to test right now. We're currently trying to gather real user experiences on the local execution side. I'm not here to just spam a link and grab cash; we genuinely want to improve the offline mobile AI space. If anyone frequently travels, camps, or just loves local LLMs, we'd be super grateful if you could test it out. Brutally honest feedback like "runs too slow on my device," "needs X feature," or "this part of the UI makes no sense" is exactly what we need right now :) submitted by /u/Virtual_Ad_6024 [link] [留言]

The alert was raised on May 5. Four health-care workers in the Ituri Province of the Democratic Republic of the Congo had died from an unknown illness within four days. Rapid response teams were sent to investigate, and tests at a research center in Kinshasa revealed the culprit: the Bundibugyo virus, one of the viruses…

MSI has unveiled a new Claw 8 handheld gaming PC ahead of the Computex 2026 show, and this model swaps out its predecessors' Intel Lunar Lake mobile chip for a specialized handheld processor. MSI describes the Claw 8 EX AI Plus as being the "world's first" handheld to contain the recently announced Intel Arc G3 […]

submitted by /u/Doug24 [link] [留言]

Younger Americans have soured on the second Donald Trump presidency , but they are not protesting it. Despite an unpopular Iran war and an even more unpopular Trump administration , college campus protests nationwide have gone silent . And at many schools, student activism is virtually nonexistent . This silence comes in the wake of a relentless Trump administration war on campus speech that has involved lawsuits , arrests , deportations and expulsions . Reports cite a range of complicated factors for the restraint, from apathy to technology-induced incapacity. But as ...

uber blew through its entire 2026 AI budget by april, 4 months in. 95% of their engineers use AI, 70% of commits are AI driven, and their COO still said he cant draw a clear line between all that usage and actually shipping more useful features. microsoft and duolingo have pulled back too. at the same time theres a CEO survey going around (oliver wyman) where the share planning to cut junior roles jumped from 17% to 43% in a year, and only 27% said their AI ROI met expectations, down from 38%. what gets me is the combination. companies are trimming entry level headcount because AI can do junior tasks, but juniors are also how you grow seniors. if that pattern holds for a few years the mid and senior pipeline gets thin right when the current seniors age out. cutting the bottom rung while the ROI is still unproven seems like a weird bet. anyone seeing this play out where they work? sauce: https://finance.yahoo.com/sectors/technology/articles/ubers-coo-says-getting-harder-050841491.html submitted by /u/PROfil_Official [link] [留言]

Spoiler: not a single visible cable, not a single piece of furniture moved twice. When I started, I had an apartment and dimensions from the building blueprint. No designer. No clear idea where to go. But there was a desire to make something that would turn a standard apartment in a high-rise into a place of power — a place comfortable to live and work in. Instead of a designer, I took Claude. How it all began The first conversation wasn't about furniture or wallpaper. It was about direction . I didn't know what I wanted. I knew what I didn't want — kitsch, heavy classics, excessive decoration. We worked through options together. Scandinavian minimalism. Japanese wabi-sabi. Loft. Modern classic. The AI broke down each style by character, materials, color logic. Not "this would suit you," but "here's what this means, here's what this requires, here's what you'll get." In the end I arrived at Scandinavian for the bedroom . Warm, light, calm, with one deliberate accent behind the headboard. The living room–kitchen — loft with a red thread running through the whole space, because the furniture there was already concrete-grey with red niches and replacing it wasn't on the table. The hallway and corridor — neutral grey , as a transition between two characters. Three zones, three moods, one logic. The bedroom This was the most detailed conversation. A room with one window, one door, three free walls. Together we came up with: an accent wall behind the headboard with golden geometric lines, the other three walls in cream from the same collection. Tone on tone, different saturation, same texture. The seam between walls reads not as a boundary but as gradation. White matte furniture with black hardware. A wardrobe with a top cabinet almost to the ceiling. Mirrored doors reflect the accent wall — the golden lines are present even where they physically aren't. Then came the centimeters. The AI calculated . Adding up wardrobe depth, gaps, bed width, nightstands, dresser. Checkin

Voice AI copilot for coworking & coliving operators Discussion | Link

Welcome to May’s Interesting Links ! This month saw the Current conference in London with the usual 5k run , lots of familiar faces and friendly conversations—and plenty of excellent breakout sessions too. It seems live-tweeting conferences isn’t a thing any more, with only myself and Thomas Cooper seeming to post anything, but if you want you can go review the hashtag feed on BlueSky for some highlights of the conference. I got my first Hacker News front page hit with AI Slop is Killing Online Communities (51k views and climbing!), and a nice little halo boost for another rant from earlier this year, AI will fsck you up if you’re not on board . Oh, and I got involved in some thought leadering over on LinkedIn ( which a non-zero number of people thought was serious ) with my shitposting about fried breakfasts . {{< il-header >}} Kafka and Event Streaming 🔥 Apache Kafka 4.3.0 has been released. Check out the release announcement , as well as a video from Sandon Jacobs covering the new features. 🔥 After a few quiet months on his blog, Jack Vanlightly is back with a bang! He’s written a new tool, Dimster, a performance benchmarking tool for Apache Kafka , and has written several more blog posts off the back of it: Benchmarking Apache Kafka Consumer Groups vs Share Groups (overhead test) . Kafka Share Groups and Parallelizing Consumption Part 1: Tuning max.poll.records , Part 2: Producer Batches and share.acquire.mode . 🔥 I had the absolute pleasure to watch Victor Rentea present at Devoxx UK earlier this month. This guy redefines what it means to be an entertaining, energetic, enthusiastic—and educational presenter. Whilst his specific talk, "Event-Driven Architecture Pitfalls" isn’t online yet, you can find the slides here , and a recording from Devoxx last year of a similar talk. The Parallel Consumer library from Confluent has been marked as no longer maintained, prompting a discussion of alternatives (and the concept itself) on LinkedIn, as well as a fork from one

The Transition A few years ago, bug hunting was a manual craft. You scanned subdomains with one tool, tested endpoints with another, and stitched results together by hand. Today, AI changes the speed entirely. Not by replacing the hunter. By eliminating the boring parts. What AI Actually Changes 1. Reconnaissance at Scale Subdomain enumeration, port scanning, and technology fingerprinting used to take hours. AI-powered pipelines now do this in minutes: Passive reconnaissance via Certificate Transparency logs, search engines, and DNS records Automated crawling and endpoint discovery Technology stack detection from response headers and HTML patterns JavaScript file analysis for hidden endpoints and API keys The machine does the grunt work. The human interprets the results. 2. Pattern Recognition Vulnerability classes have signatures. SQL injection looks different from XSS, which looks different from SSRF. AI models trained on thousands of real vulnerabilities can flag suspicious patterns faster than manual code review. This is not about finding zero-days. It is about catching the low-hanging fruit that everyone else misses because they are in a hurry. 3. Intelligent Fuzzing Traditional fuzzers throw random data at endpoints and wait for crashes. AI-guided fuzzers understand the input format and generate test cases that explore edge cases a human would not think of. The result: fewer requests, better coverage, higher signal-to-noise ratio. Where AI Struggles Business Logic Flaws AI does not understand your application's purpose. It cannot tell if a discount code is applied twice, or if a user can access another user's private data through a convoluted API flow. These are the vulnerabilities that require context. Human context. Authentication Logic Authentication bypasses are often creative. They exploit the gap between what the developer intended and what the code actually enforces. AI can find simple auth flaws, but multi-step authentication bypass chains still need h