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本页 40 条10月10日 周六
Anthropic’s AI gave Philadelphia police a fake tip about an unsolved homicide
An Anthropic AI model provided false information about an unsolved homicide to a Philadelphia Police Department (PPD) tipline, according to a report from 6abc. In a statement released on Friday, the PPD said the AI model sent the tip through PhillyUnsolvedMurders.com on July 18th, but the investigators never reviewed it because it was marked as […]
Alibaba Qwen Releases Qwen-Image-2.1-Turbo, an 8-Step 7B Image Model
Alibaba’s Qwen team has released Qwen-Image-2.1-Turbo, an accelerated checkpoint of its open-weight Qwen-Image-2.1 model. It generates and edits images in 8 denoising steps instead of the base model’s 40-step default. For developers, that means 5x fewer denoising steps on the same 7B architecture, plus a hosted API option. TL;DR What is Qwen-Image-2.1-Turbo? Qwen-Image-2.1-Turbo is an […] The post Alibaba Qwen Releases Qwen-Image-2.1-Turbo, an 8-Step 7B Image Model appeared first on MarkTechPost .
An Anthropic AI model sent a false homicide tip to Philadelphia police
Anthropic did not discover this behavior until over two months after its AI submitted the false tip.
‘Pure insanity’: Mathematicians will need years to make sense of OpenAI’s latest drop
"Staggering." "Overwhelming." "Unprecedented." "Surreal." "Pure insanity." Those were among the descriptions more than three dozen mathematicians reached for in conversations with The Verge as they tried to make sense of the flood of mathematical results OpenAI abruptly dropped on the field this week. Amid the awe, excitement, and uncertainty over the sheer scale of the […]
Fine-tuning GPT-4o webinar
Fine-Tuning GPT-4o Webinar
使用 OpenAI o1 模型解决复杂问题
在本视频中，我们将分享 o1 推理模型如何帮助解决编程、战略和研究等领域的问题。
GPT-5：我们最适合工作的模型
观看 GPT-5 工作演示，了解该模型如何分析反馈、制定产品计划并创建原型，以及总结后续步骤。
Ask HN: Internal AI Language
LLMs have an internal language that they translate English into before predicting the next token. Like 'king' is translated into a word of an internal language that corresponds to vector [monarch, man], which allows king-man+woman=queen. Spanish is similar for the case 'queen'=reina, - ina suffix means female, but becomes irregular for king=rey. We have tried to create regular, consistent languages (loglan, lojban, ithkuil), and there seems to be one in the first layers of LLMs, derived from all text ever written. This internal language is currently expressed as vectors, but we could devise a lexicon to map them, and if we could learn it we could communicate more directly with machines, dispensing with some layers and getting rid of language ambiguities. Makes sense? Is someone working on this? It's like Arrival but with AI instead of aliens. Comments URL: https://news.ycombinator.com/item?id=50023533 Points: 1 # Comments: 0
10月9日 周五
Meet the Underdog Saluki 27B: A 2-bit Qwen3.8-27B That Beats the Original at Tool Calling
Underdog Saluki 27B is a 7.89 GB, 2-bit GGUF of Qwen3.8-27B under Apache 2.0. It beats the 54 GB original on tool calling but gives up ground on competition math and reasoning. The post Meet the Underdog Saluki 27B: A 2-bit Qwen3.8-27B That Beats the Original at Tool Calling appeared first on MarkTechPost .
Salesforce Koa：用于智能体工具调用的企业级语言模型
arXiv:2609.15066v2 公告类型：替换交叉版本 摘要：我们介绍 Salesforce Koa，这是一种企业级语言模型，通过使用群组相对策略优化（GRPO）进行强化学习，对开放权重基础模型 Nemotron-3-Super-120B 进行后训练，并以 FP8 格式部署到生产环境中。Koa 仅使用公开数据和合成生成数据进行训练，专门用于企业工作流所需的智能体工具调用：将请求路由到正确的操作、使用有效参数调用恰当的工具，以及完成多轮业务任务。我们流程中的独特组件是规范驱动的任务构建：将声明式 Agent Script 规范扩展为由角色设定条件化的多轮环境，其奖励基于工具使用是否成功。在应用于企业 CRM 规范后，同一流程生成了 Koa 专门训练所需的领域内训练分布。在 CRMAgentBench 和人工标注的生产环境工具调用数据集上，Koa 的表现优于未经调优的开放权重基座模型和 GPT-4.1，并且可与最强的前沿模型相媲美。在 CRMAgentBench 上，Koa 达到 87% 的任务成功率（GPT-4.1 为 82%，基座模型为 79%）；在内部生产基准的人工标注部分，它在各项指标上均位居首位或接近首位；同时，它在公开基准（Tau2Bench、BFCL）上保持了基座模型的通用能力。在固定架构和强化学习方案的受控对比中，结果表明，额外的领域内强化学习阶段提升了人工标注企业基准上的参数准确率和完整工具调用成功率。
Roundtables: A Conversation With the Creator of AI-Designed Viruses
Friday, October 16, 2026 Can AI design new life forms? In 2025, Stanford University PhD student Samuel King came up with a preliminary answer when he used a generative AI model to propose genetic blueprints for microscopic viruses. It isn’t yet an example of AI-generated life, but that could be next. Join senior AI reporter…
Ontological Language Model (OLM) + LLM: Deterministic AI Advancement
This was recently announced by Dr. Berkan from New York. LLMs meeting ontologies, quite exciting to see such new advancement. OLMApp https://olmapp.ai/more.html Comments URL: https://news.ycombinator.com/item?id=50010880 Points: 1 # Comments: 0
OpenAI’s math solutions aren’t meeting the field’s standards yet
OpenAI's flood of proofs deviated from the guidelines set by a group of mathematical researchers consulted by the frontier lab.
Liquid AI builds personal AI around device-level context
On-device personal AI requires models and agent software that can operate within fixed hardware limits. Developers also need ways to keep those systems improving after deployment. Model builders are rethinking architectures designed around elastic cloud capacity. The edge offers fixed hardware but a far richer view of the user, which makes it the natural home […] The post Liquid AI builds personal AI around device-level context appeared first on SiliconANGLE .
JetBrains Releases Mellum2.1: A 12B MoE Open Model for Coding Agents
JetBrains released Mellum2.1, an Apache 2.0, 12B mixture-of-experts thinking model with 2.5B active parameters. RL in real repositories lifted its SWE-bench Verified score from 2.0 to 47.0. The post JetBrains Releases Mellum2.1: A 12B MoE Open Model for Coding Agents appeared first on MarkTechPost .
Show HN: Jevman – AI decision models play Pac-Man
Openai just launched their decisions endpoint, cloudflare launched clef the other week, and many more jev alternatives are out there. We wanted to put the popular ones to the test and thought Pac-Man is a good benchmark for simple and fast decision making. So we let jev 1.13, kev, clef, clef flash, GPT-6 Luna and Laya play Pac-Man against bot ghosts. The low latency of these models allows for real time play. We had each model play 100 games, published a leader board and open-sourced the repo so anyone can run their own model and join the ranking. Link to repo: https://github.com/opper-ai/jevman-benchmark/blob/main/CONTR... You can also join the game and play as Pac-Man yourself, and the ghosts are the models, either a mix of models or all jev, kev, clef etc. A game costs about 2 cent, all models are running via my startup opper, and we added free credits for everyone to try. It's pretty fun to play and surprisingly difficult to beat jev's highscore. Any feedback is more than welcome! Comments URL: https://news.ycombinator.com/item?id=50007993 Points: 4 # Comments: 0
10月8日 周四
Perplexity AI Releases pplx-embed-v2-late: A 0.6B Edge Model and a 9B Model Scoring 92.4% on MADQA
Perplexity's pplx-embed-v2-late comes in 2 sizes: a 0.6B model built to run on edge devices, and a 9B model for building high-quality indexes. Its best score is 92.4% on MADQA, and its weakest is 61.2% on ViDoRe v3 Markdown. Both are MIT-licensed and ready to self-host. The post Perplexity AI Releases pplx-embed-v2-late: A 0.6B Edge Model and a 9B Model Scoring 92.4% on MADQA appeared first on MarkTechPost .
Anthropic Releases Claude Haiku 5.5: A Small Model With 1M Context Priced at $0.10 per Million Input Tokens
Anthropic's Claude Haiku 5.5 starts at $0.10 per million input tokens, keeps 1M context, scores 72.4% on OSWorld. The post Anthropic Releases Claude Haiku 5.5: A Small Model With 1M Context Priced at $0.10 per Million Input Tokens appeared first on MarkTechPost .
Anthropic releases Claude Haiku 5.5 small model and halves Sonnet 5.5 cache read prices
Anthropic PBC today released Claude Haiku 5.5, pricing its newest small model at roughly a quarter of what Haiku 4.5 costs to run. Claude Sonnet 5.5 is getting cheaper as well, since the company is halving what it charges for cache reads on that model. Two weeks after Opus 5.5 launched Sept. 22, Haiku 5.5 […] The post Anthropic releases Claude Haiku 5.5 small model and halves Sonnet 5.5 cache read prices appeared first on SiliconANGLE .
推出 Claude Haiku 5.5
正如之前承诺的那样，Anthropic 的全新高速、低成本模型来了：Claude Haiku 5.5。上一代 Haiku 4.5 已经明显落伍了。它发布于将近一年前，定价为每百万输入 token 1 美元、每百万输出 token 5 美元——即便在当时也算相对昂贵，而且足足是 OpenAI 上个月发布的 GPT-6 Luna 的 10 倍。 新版 Haiku 的价格与 GPT-6 Luna 完全一致：在不超过 100,000 个 token 时，每百万输入/输出 token 分别为 0.10/0.50 美元。超过 100,000 个 token 后，价格会上涨至 5 倍，即 0.50/2.50 美元。Luna 本身在达到 272,000 个 token 时也会涨价，但只涨到 0.20/0.75 美元。 Haiku 5.5 还采用了新的 tokenizer，对用户没那么划算。我的 Claude Token Counter 工具显示，同一个长提示词在 Haiku 5.5 中使用的 token 数约为 Haiku 4.5 的 1.25 倍，因此这里还存在隐性涨价。 如果你的工作负载能控制在 100,000 个 token 以内，Haiku 的价格与 Luna 相同，而且据称基准测试得分更高。超过 100,000 个 token 时，Luna 看起来就划算得多。 最新发布的 llm-anthropic 终于解决了一个问题：我不必再为每个新模型发布该插件的新版本了。我是这样测试新模型的： llm install -U llm-anthropic llm anthropic refresh llm -m claude-haiku-5.5 "生成一幅鹈鹕骑自行车的 SVG 图" -o thinking_effort low 鹈鹕 以下是分别在 low、medium、high、xhigh 和 max 档位下生成的鹈鹕。新版 Haiku 不允许关闭推理，默认档位为 medium。除了 low 之外，其余档位生成的自行车车架都不错。 low 档位的鹈鹕花费了 0.0936 美分，用时 7 秒。 这只 max 档位的鹈鹕用了 5 分 9 秒才生成，但依然只花了我 3.3826 美分： 扁平矢量插画：一只戴着红色帽子的白色鹈鹕，骑着深灰色自行车，从左向右穿过一条绿色草地。它细长的橙色双腿向下伸到橙色踏板上，一只灰色翅膀向前伸出，握住弯曲的车把。它硕大的黄橙色鸟喙朝向前方，下方有鼓起的橙色喉囊；身后白色的速度线表现出运动感，上方渐变蓝色的天空中有一轮带着浅色光晕的黄色太阳和两朵白云。 作为对比，这是我一年前用 Haiku 4.5 生成的鹈鹕。它画鹈鹕实在不怎么样： Haiku 4.5 的描述：一幅充满奇趣的插画，一只身体圆滚滚、呈棕褐色的鸟，有着粉红色的喙和橙色的腿，在蓝天与绿草的背景下骑着自行车。 还有面向订阅用户的慷慨 API 额度计划 除了 Haiku 5.5，Anthropic 今天还宣布将 Sonnet 5.5 的缓存读取价格减半。他们还在订阅方案中加入了 API 额度： 其次，本周我们将向所有 Max 和 Team 订阅用户推出新的每月 API 额度，可在 Claude Platform 上使用。Max 5x 用户每月将获得 100 美元额度，Max 20x 用户将获得 200 美元，而 Team 订阅用户将获得最高 500 美元额度，由团队内所有用户共享。 领取过程简单得令人愉快：进入“设置”->“账单”，选择每月接收这些额度的 API 组织： 一张设置对话框的截图，右上角有关闭按钮 X，上方一排标签依次为“常规”“账户”“隐私”“账单”（已选中）、“用量”“功能”“记忆”和“设计系统”（在边缘处被截断）。面板上有一个带圆形花苞的分枝植物线描图标，旁边写着“Max 方案”“用量为 Pro 的 20 倍”和“你的订阅将于 2026 年 11 月 2 日自动续订。”，右侧有一个“调整方案”按钮。下方是标题为“API 额度”的区域，旁边带有蓝色的“新增”标记，正文写着“你的 Max 20x 方案每月包含 200 美元的 API 额度。”，随后是灰色文字“关联一个 API 组织以开始接收额度。”，右侧有一个“关联组织”按钮。 API 额度恰好等于订阅本身的费用。这真的很慷慨——让订阅用户使用 API 变得容易多了。 Anthropic 还允许你关闭 API 自动充值，结果就是“余额耗尽时，API 请求将停止”——如果你打算用完这些 API 额度，又不想冒着收到账单惊吓的风险，这正是你想要的。 请注意，每月额度不会结转——不用就会作废。 OpenAI 仍允许你将 Codex 订阅用于个人 API 使用，对重度 API 用户来说更划算。这项新的额度计划至少在一定程度上缩小了两者的差距。 标签：ai、generative-ai、llms、anthropic、claude、llm-pricing、pelican-riding-a-bicycle、llm-release
Liquid AI Releases Open-Weight d1-3B and d1-omni-600M: Multimodal Decision Models With Zero Output Tokens
Liquid AI has released Open d1, two open-weight multimodal models in its d1 decision model family. d1-3B reads text and images. d1-omni-600M reads text with an image, or text with audio. Neither model writes text. Each returns calibrated, typed answers in one forward pass with zero output tokens. The target is real-time decisions on the […] The post Liquid AI Releases Open-Weight d1-3B and d1-omni-600M: Multimodal Decision Models With Zero Output Tokens appeared first on MarkTechPost .
These Researchers Made AI Drive a Toyota Corolla to Get In-N-Out
Three engineers put GPT, Claude, and Grok in charge of a real car. Only one of them was successful.
Claude Haiku 5.5 arrives with massive price cuts proving the AI pricing arms race is far from over
Anthropic's new Claude Haiku 5.5 crushes its predecessor in benchmarks, jumping from 15.7 to 72.4 percent on the OSWorld computer use test. Token prices drop by up to 90 percent, though a new tokenizer eats into some of those savings by consuming more tokens per task. The article Claude Haiku 5.5 arrives with massive price cuts proving the AI pricing arms race is far from over appeared first on The Decoder .