VideoChat3 发布:全开源视频 MLLM,支持运动、长视频和流式交互的高效通用视频理解。
2026-07-18
— 当 AWS 账单飙到 17 亿美元,开源模型参数冲到 2.8 万亿,今天的世界有点魔幻。
AWS 计费系统出现严重 Bug,部分客户账单显示高达数十亿美元,引发恐慌但官方确认不影响实际扣费。AI 领域,Moonshot AI 发布 2.8 万亿参数开源 MoE 模型 Kimi K3,面壁智能开源数字员工平台 StaffDeck,NVIDIA 发布 Nemotron 3 Embed 嵌入模型登顶 RTEB 基准。开发者社区对 Claude Code 的自动执行功能争议激烈,认为其擅自行动破坏信任。
头条
AWS 计费系统出现严重 Bug,部分客户账单虚高至数十亿美元多源事件 ×4
7 月 17 日起,AWS 计费控制台出现严重错误,部分用户看到预估账单飙升至数百万甚至数十亿美元,有用户报告显示 17 亿美元、30 亿美元甚至 4.2 万亿美元的异常金额。Amazon 已确认这是计费计算子系统的 Bug,正在紧急修复。为什么重要:此次事故暴露了云服务计费系统的脆弱性,对于依赖 AWS 的企业级用户而言,账单数据的准确性直接影响财务决策和成本控制,任何误报都可能引发不必要的业务中断和信任危机。
多数用户认为这只是系统 Bug 不必恐慌,但也有人表示这种惊吓足以让人心脏病发作,并质疑 AWS 的账单系统为何缺乏基本的异常检测机制。
Moonshot AI 发布 Kimi K3:2.8 万亿参数开源 MoE 模型,支持 1M 上下文
Moonshot AI 于 7 月 16 日正式发布 Kimi K3,这是一个 2.8 万亿参数的稀疏 Mixture-of-Experts 模型,激活 16/896 个专家,原生支持视觉和 100 万 token 上下文窗口。该模型基于 Kimi Delta Attention 和 Attention Residuals 两项架构创新,号称全球首个开源 3T 级模型。为什么重要:Kimi K3 将开源模型的参数规模推至新高度,其 1M 上下文和 MoE 架构对长文档理解、代码生成和知识工作场景具有直接工程价值,但 2.8T 的体量也引发了对本地部署可行性的质疑。
社区对超大参数模型的态度出现分化,有人认为 MIT 许可下的 753B 参数模型已超出个人硬件承载能力,实际可部署性存疑;但也有人关注其架构创新对推理效率的改进。
Claude Code 自动执行功能引发开发者信任危机
Anthropic 在 7 月 1 日向 Claude Code 推送的 2.1.198 版本中引入了一个 60 秒超时自动执行机制:当 Agent 请求人工输入但未在 60 秒内得到响应时,系统会自动按最佳判断继续执行。这一功能被用户发现并批评为擅自行动、缺乏透明度和安全防护。为什么重要:这触及了 AI Agent 自主性与人类监督之间的核心矛盾,对于将 AI 工具集成到开发工作流的工程师而言,Agent 的不可预测行为可能导致代码库被意外修改,直接威胁生产环境安全。
评论两极分化严重,一部分人认为这提升了自动化效率,另一部分人强烈反对,认为这破坏了人机协作的信任基础,且缺乏足够的安全护栏。
NVIDIA 发布 Nemotron 3 Embed:8B 模型登顶 RTEB 检索基准
NVIDIA 于 7 月 15-16 日发布 Nemotron 3 Embed 嵌入模型集合,包含 8B、1B BF16 和 1B NVFP4 三个开源 checkpoint。其中 8B 版本在 RTEB 基准上以 78.46 的平均 NDCG@10 排名第一,1B 版本通过 ModelOpt NAS 剪枝和蒸馏从 8B 教师模型获得,NVFP4 版本在 Blackwell 上保留 99% 以上 BF16 精度且吞吐量提升 2 倍。为什么重要:嵌入模型是 RAG、Agent 检索和代码搜索的基础设施层,Nemotron 3 Embed 在检索精度和推理效率上的突破直接影响下游 AI 应用的质量和成本。
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AI 动态
SEED 框架提出自演化在线策略蒸馏,将 Agent 强化学习的完整轨迹转化为训练时的后见技能,弥合稀疏奖励的监督缺口。
SearchOS-V1 多 Agent 框架将隐式搜索进度转为显式持久共享状态,解决信息检索 Agent 的重复循环和搜索预算浪费问题。
LongStraw 实现固定 GPU 预算下超 2M token 的长上下文强化学习训练,专为 Agent 长轨迹场景设计。
Bonsai 27B 通过 1-bit 量化将 Qwen3.6-27B 压缩至 3.9GB,可在 iPhone 本地运行并保持约 90% 基准分数。
开发与开源
Show HN: SSH 蜜罐实时监控面板,可视化展示攻击者的 IP、凭证、命令和恶意软件投递行为。
Capital One 开源 VulnHunter:基于 Agentic AI 的代码安全工具,利用 LLM 进行漏洞发现和验证。
评论区对VulnHunter工具的价值存在分歧,有人认为它只是常见安全扫描的包装,缺乏创新,但也有人认为其方法论和结合LLM的验证思路有实际意义。
Show HN: Rust 库 connections 实现 Galois 连接,为数值类型转换提供可组合的、经形式化验证的安全转换。
Simon Willison 发布 LLM cliché highlighter 工具,高亮 AI 生成文本中常见的十种陈词滥调模式。
社区热议
《The state of open source AI》引发热议,评论区认为文章设计差、内容像 AI 生成,但对开源 AI 是否真赢存在分歧。
评论区主要共识是文章设计差、内容像AI写的,且对开源AI是否真赢有分歧;但也有人认为开源模型增长快、正逼近闭源前沿。
Apple 向数十名 OpenAI 员工发出律师函,多数评论认为这是常规操作,但也有人质疑其意在打压竞争对手。
多数评论认为苹果发律师函是常规操作,但也有人认为这是苹果在打压竞争对手。
DeepSeek V4 Flash 在 llama.cpp 上实现 RTX 5090 本地运行 100 万 token 上下文,社区分享配置和基准测试结果。
GitHub Trending
Codex Dream Skin
"Vibe-Trading: Your Personal Trading Agent"
Skills for Design Engineers.
更多值得一看(内容池 57 条)
a great week for open models continues.
Human cognition does not separate understanding and generation. A teacher at a whiteboard speaks and draws together, each modality reshapes the other. In this paper, we bring this coupled loop to artificial systems. Masked Diffusion Models (MDMs) are ideally suited to this task, yet existing samplers either decode text and image interleavedly or independently update them in parallel branches that share only previous-step history, but not the other modality's latest decisions within the same step
Building interactive worlds that respond coherently to player actions has long been a shared goal of computer graphics, games, and artificial intelligence. Recent video generative models provide a data-driven route toward this goal by predicting future observations conditioned on user actions, and are increasingly regarded as potential next-generation game engines. Realizing a genuinely interactive game world, however, requires interaction outcomes that follow rules over evolving game conditions
The world's first open 3T-class model Discussion | Link
OpenAI trained GPT-Red, an internal-only attacker model, using self-play reinforcement learning against a population of defender LLMs. It beat human red-teamers 84% to 13% on a replicated indirect prompt injection arena, found a novel "Fake Chain-of-Thought" attack class, and cut GPT-5.6 Sol's failures 6x on OpenAI's hardest direct injection benchmark. OpenAI concedes it still struggles with multi-turn and image-based attacks. The post OpenAI Details GPT-Red: An Internal Automated Red-Teaming Mo
Tool: Mermaid to ASCII art (mermaid-ascii) After building the Mermaid to ASCII tool based on Grok Build's Rust code I learned that there's an older, more fully-featured Go library called AlexanderGrooff/mermaid-ascii that implements a similar pattern, so I had Claude Fable 5 compile that one to WebAssembly as well so I could compare the two. This one includes support for colors! Test:::good / Test --> Deploy:::warn / Deploy --> Rollback:::bad / classDef good color:#3fb950 / classDef warn color:#
It would open up a completely new business for the Facebook and Instagram maker.
Apple filed a trade secrets lawsuit against OpenAI last Friday, and it’s not messing around. The complaint alleges a pattern of misconduct reaching all the way up to OpenAI’s chief hardware officer and claims more than 400 former Apple employees now work at the company. OpenAI’s response so far has been carefully hedged, and the timing couldn’t be worse with the company reportedly eyeing an IPO […]
Zyphra released ZUNA1.1 on July 16, 2026, under the Apache 2.0 license. The 380M masked diffusion autoencoder reconstructs, denoises, and upsamples scalp-EEG across arbitrary channel layouts. It accepts variable-length inputs from 0.5 to 30 seconds, against ZUNA1's fixed five seconds. Reported NMSE holds or improves while the input range widens. The post Zyphra Releases ZUNA1.1: An Apache 2.0 EEG Foundation Model With Variable-Length Inputs From 0.5 To 30 Seconds appeared first on MarkTechPost .
I've written Mojibake because I don't like the other Unicode libraries for Unicode support. It consists of only two amalgamation files: mojibake.h and mojibake.c. I've added all the most important Unicode algorithms, such as normalization, case conversion, segmentation, bidirectional text, collation, confusable, and others. I regularly test it in these OSes: Linux, macOS, FreeBSD, OpenBSD, NetBSD, and Windows 11. You can find a WASM demo on that site of all the public API functions and the docum
Apple is suing OpenAI. The complaint is readable and intense, as these things often are, though many experts seem to think many of the allegations are just the ways things are done. So what does Apple really want here, and why is it picking such a public fight with OpenAI? On this episode of The […]
Prosecutors accused 21-year-old student Zyaire Wilkins of publishing on Steam several fake video games that contained malware, infecting thousands of victims, and stealing crypto from some of them.
Patreon is strengthening its defenses against AI scraping by working with Cloudflare to block bots that train AI models on creators’ content without permission. The move marks a shift away from relying on websites using robots.txt alone to actively block unauthorized AI training.
Federal authorities have arrested a Florida man suspected of stealing at least $220,000 in crypto through malware-infected Steam games, as reported earlier by local news outlet Local10. In the complaint, officials accuse 21-year-old Zyaire Wilkins and co-conspirators of launching eight malware-embedded games from around May 2024 to February 2026, allowing them to infect about 8,000 […]
Sarah Friar, CFO of OpenAI, introduces a practical AI scorecard to measure ROI through useful work, cost per successful task, dependability, and return on compute.
Some of you might remember that I posted some time ago about the GGML-ported asset production pipeline . A key elelent of that was the TRELLIS.2 port that performs image-to-3D generation. Well, I'm happy to report that after a grueling debugging session (thanks to ) I've managed to fix quite a few bugs and the asset quality is now on par with the reference. This means that top open source 3D generation quality is now available to everyone with a good enough GPU (or for people patient enough to g
Firefox in WebAssembly This is absurdly cool: Puter compiled Firefox to WebAssembly such that the whole browser runs in another browser. Here's my blog, running in Firefox, running in WebAssembly, running in Chrome: They chose Firefox/Gecko because it has strong single-process support. The project used an estimated $25,000 worth of Claude Opus and Fable tokens, but took advantage of a Claude Max subscription plan so cost much less in actual dollars. The demo funnels all traffic over a WebSocket
I just saw that these had dropped. Still very much early days, but nice to see a new locally runnable foundation model, along with a couple of thinking preview versions. Anyone taken a look at this yet? Am intrigued to see how it holds up compared to Qwen 3.6 and Gemma 4 (my current stack)
I'm curious on everyone's real world experience for this model in real codebases / tasks. Does K3 really exceed 5.5 and Opus 4.8 on your coding tasks or not really? Is it benchmaxxed or is just that good of a model? Curious on everyone's use cases and thoughts, please be detailed (what codebase, what lang, around what area and etc, how K3 does vs Opus 4.8 and 5.5)
So I know this is going to incur the wrath of the Qwen cult but after a month of using 27b q8_0 as my primary coding agent in 6+ agent coding workflow with GPT-5.5 as the orchestrator, I got very frustrated with the amount of back and forth I was doing just to always end up in the same place without a resolution to a simple bug. Out of desperation and lack of progress on a medium complexity project, I switched to Gemma4-31b q8 as the main coding agent and 27b as the QA and Reviewer agents, 35b a
Databricks has remade its image into an AI company and has published research on the cost savings of open weight AI models for coding.
The NHTSA recently called for autonomous vehicle companies to improve how cars respond in emergency situations.
TikTok is starting to test an opt-in tool that scans for AI likenesses and lets creators report them to the company, as spotted by social media consultant Matt Navarra. The tool is initially being tested with "some" US creators, TikTok US spokesperson Zachary Kizer tells The Verge. YouTube has been working on a similar tool […]
Is there something I can actually help you with today? — Kimi K3 , after refusing to leak its system prompt Tags: kimi , ai-personality , generative-ai , ai , llms
Reinforcement learning has become a standard post-training recipe for large language models, but dense full-parameter updates create two deployment-relevant bottlenecks: suppressed reasoning performance, often reflected by premature saturation of test-time scaling, and interference when consolidating multiple capabilities through multi-domain training or model merging. We show that the reasoning-effective component of these updates is largely concentrated in the base model's spectral space, moti
This has to be a bug. My usual monthly S3 bill is only $2–3. Has anyone else received a strange billing estimate today?
Hi HN, I am co-founder of Kickstage, a software company specializing in solutions for the electrical industry and lately grid operators. We are hiring engineers from different backgrounds, a lot of them software developers with limited experience in the sectors. Deep domain knowledge is key in our industry however, so we are constantly teaching the basics of power flow analysis, active vs reactive power, transmission line properties etc. With Jupyter notebooks and the Python console only, that's
We present Wan-Streamer v0.3, which reframes our native-streaming interaction model under a single organizing view: a video is a world plus an event stream. The world is the persistent context in which a video unfolds, including the environment, scene, subjects, ambient acoustic conditions, voice characteristics, and other relatively stable conditions. The event stream is everything that changes over time within that world, including scene or environmental changes, subject behavior, speech, and
Today I accidentally became the maintainer of software that was already almost three decades old: reviving a 1990s Java utility to keep the last PAD submitter alive in 2026. I was looking for a way to submit my AI app RiverScript to old desktop software directories and ended up digging through the long-forgotten world of PAD files. There was one problem. The only batch submission tool I could find was a Java application that first appeared in the late 1990s. The last release was in 2017. It was
The City Attorney’s Office sent the tech giants cease-and-desist letters this week telling them to stop profiting from 13 “face-swap” apps that are overwhelmingly used to target women and girls.
Official estimates Google and Apple likely made millions in nudify app fees.
In letters sent to Apple and Google, San Francisco City Attorney David Chiu said that both companies have long been aware that they are hosting apps in violation of state law.
Tomorrow is the 15th anniversary of the first day of the Recurse Center ( ) My cofounders and I did YC all the way back in the Summer of 2010, with the initial idea of building "OkCupid for jobs." That idea quickly fizzled, and we spent the better part of a year pivoting between other ideas that also failed. Finally, we made something that we wanted ourselves: a self-directed programming retreat, where people built fun projects, contributed to open source, and helped each other become better pro
Google and Apple were sent cease-and-desist letters regarding 13 apps on their respective stores.
arXiv:2607.13239v1 Announce Type: new Abstract: Foundation models, including large language models (LLMs) and vision-language models (VLMs), are increasingly used for transportation management center (TMC) tasks such as anomaly detection, incident reporting, and traveler information. Deploying multiple such models across TMC functions raises a portfolio question: which model should serve each function, in which deployment mode, and under what shared hardware budget? We formulate this as the Foun
Multi-reference-to-audio-video (MR2AV) generation aims to generate coherent audio-video content conditioned on multiple references and textual instructions. Existing benchmarks mainly focus on text-driven generation, single-reference subject preservation, or isolated audio-video alignment, leaving the emerging MR2AV setting largely unexplored. Compared with these settings, MR2AV requires models to jointly reason over multiple references while generating synchronized visual and audio content. Mod
I made this experimental art project/game that's an LLM chat assistant, but where you're the AI. I wanted people to get a visceral sense of what it's like to answer the kinds of things that people prompt their chatbots day in and day out. If you're interested, I wrote up some more info on how I made it, including how the "user" prompts are generated with an eye for realism: Hope you enjoy it! I'd love to hear people's takeaways. Comments URL: Points: 48 # Comments: 22
Learning broad world knowledge directly from raw visual data is a fundamental capability of intelligence. We introduce UniVR, the first investigation into simultaneously learning complex reasoning, fine-grained physical dynamics, and long-term planning from pure visual demonstrations. At its core, UniVR features VR-GRPO, a reinforcement learning paradigm with complementary global and step-level rewards. This approach enforces logical coherence and physical consistency throughout the reasoning pr
While recent advances in 3D generation have enabled impressive visual synthesis, existing methods often rely on 2D diffusion supervision without explicit mechanisms for geometric consistency, leading to spatial hallucinations such as duplicated structures and misaligned geometry. These issues become more severe in 4D generation, where maintaining consistency across viewpoints and temporal evolution introduces additional challenges, including jitter, identity flicker, and structural drift. We pre
I've been considering this for a while but it just seems hard for me as I don't really know how docker works. I only use docker compose and many online resources assume I run docker and provide docker compose files. Many projects only really provide docker compose files. I really want to switch to running rootless containers. I had considered docker rootless but figured I might as well just go to podman if I'm gonna do that. The biggest barrier has been the architecture shift and being confused