https://t.me/AI_News_CN
📈主流AI服务状态页通知 | 🆕汇集全网ChatGPT/AI新闻 #AI #ChatGPT
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📈主流AI服务状态页通知 | 🆕汇集全网ChatGPT/AI新闻 #AI #ChatGPT
🆓免费AI聊天 https://free.netfly.top
✨BEST AI中转 https://api.oaibest.com 2.8-4.2折 支持OpenAI, Claude, Gemini,Grok, Deepseek, Midjourney, 文件上传分析
Buy ads: https://telega.io/c/AI_News_CN
OpenAI宣布推出开源模型GPT-OSS系列
OpenAI CEO 山姆·奥尔特曼周二宣布，公司将在未来几天里带来许多新东西，其中周二会迎来一项“小而重磅”的更新——预热已久的开源模型GPT-OSS。简单而言，OpenAI周二共发布两款开放权重AI推理模型。其中参数量达到1170亿的gpt-oss-120b能力更强，可以由单个英伟达专业数据中心GPU驱动；参数量210亿的gpt-oss-20b模型，则能够在配备16GB内存的消费级笔记本电脑上运行。两款模型都以Apache 2.0许可证发布，企业在商用前无需付费或获得许可。就该模型性能而言，GPT-OSS大致位于开源模型的第一梯队，但整体略逊于GPT-o3和o4-mini。
—— 财联社、彭博社、OpenAI
via 风向旗参考快讯 - Telegram Channel
OpenAI CEO 山姆·奥尔特曼周二宣布，公司将在未来几天里带来许多新东西，其中周二会迎来一项“小而重磅”的更新——预热已久的开源模型GPT-OSS。简单而言，OpenAI周二共发布两款开放权重AI推理模型。其中参数量达到1170亿的gpt-oss-120b能力更强，可以由单个英伟达专业数据中心GPU驱动；参数量210亿的gpt-oss-20b模型，则能够在配备16GB内存的消费级笔记本电脑上运行。两款模型都以Apache 2.0许可证发布，企业在商用前无需付费或获得许可。就该模型性能而言，GPT-OSS大致位于开源模型的第一梯队，但整体略逊于GPT-o3和o4-mini。
—— 财联社、彭博社、OpenAI
via 风向旗参考快讯 - Telegram Channel
Elevated errors for requests to Claude 4 Sonnet
Aug 5, 20:08 UTC
Investigating - We are currently investigating elevated errors on requests to Claude 4 Sonnet on the API, Claude.ai, and the Anthropic Console.
via Anthropic Status - Incident History
Aug 5, 20:08 UTC
Investigating - We are currently investigating elevated errors on requests to Claude 4 Sonnet on the API, Claude.ai, and the Anthropic Console.
via Anthropic Status - Incident History
#BestAI update
https://api.oaibest.com
2025/8/6更新
✅ 新增模型：claude-opus-4-1-all，gpt-oss-120b，gpt-oss-20b
2025/7/22更新
✅ 新增模型：moonshotai/kimi-k2-instruct, qwen3-coder
2025/7/18更新
✅ 已支持claude code，请使用claude code分组，低至官方2.8折
https://api.oaibest.com
2025/8/6更新
✅ 新增模型：claude-opus-4-1-all，gpt-oss-120b，gpt-oss-20b
2025/7/22更新
✅ 新增模型：moonshotai/kimi-k2-instruct, qwen3-coder
2025/7/18更新
✅ 已支持claude code，请使用claude code分组，低至官方2.8折
🤖 Eric Wallace 团队发布 gpt-oss-120b 和 gpt-oss-20b 开源大模型，强调性能与安全
Eric Wallace 团队今日发布了两款开源大语言模型（LLMs）：gpt-oss-120b 和 gpt-oss-20b。这两款模型在性能和智能体工具使用方面表现出色。在发布前，团队进行了一项开创性的安全分析，通过有意微调模型以最大化其生物和网络能力，从而评估并确保其安全性。
(@OpenAI)
via 茶馆 - Telegram Channel
Eric Wallace 团队今日发布了两款开源大语言模型（LLMs）：gpt-oss-120b 和 gpt-oss-20b。这两款模型在性能和智能体工具使用方面表现出色。在发布前，团队进行了一项开创性的安全分析，通过有意微调模型以最大化其生物和网络能力，从而评估并确保其安全性。
(@OpenAI)
via 茶馆 - Telegram Channel
🤖 OpenAI发布两款“开放权重”AI模型，时隔五年再推开放模型
OpenAI近日在Hugging Face平台发布了两款“开放权重”AI模型：GPT-oss-120b和GPT-oss-20b。这些模型具备文本生成、编码和在线研究等复杂任务能力，允许开发者自定义参数。这是OpenAI自2019年GPT-2以来首次发布开放模型，但由于未披露训练数据，它们并非完全开源。OpenAI首席执行官萨姆·奥特曼强调了安全担忧及修订开源策略的必要性。此次发布旨在服务包括企业和政府在内的多元用户，并被视为对中国DeepSeek R1成功的回应，也与特朗普的AI行动计划中推广开放标准的理念相符。
(财经快讯)
via 茶馆 - Telegram Channel
OpenAI近日在Hugging Face平台发布了两款“开放权重”AI模型：GPT-oss-120b和GPT-oss-20b。这些模型具备文本生成、编码和在线研究等复杂任务能力，允许开发者自定义参数。这是OpenAI自2019年GPT-2以来首次发布开放模型，但由于未披露训练数据，它们并非完全开源。OpenAI首席执行官萨姆·奥特曼强调了安全担忧及修订开源策略的必要性。此次发布旨在服务包括企业和政府在内的多元用户，并被视为对中国DeepSeek R1成功的回应，也与特朗普的AI行动计划中推广开放标准的理念相符。
(财经快讯)
via 茶馆 - Telegram Channel
Estimating worst case frontier risks of open weight LLMs
摘要
本文研究了发布gpt-oss模型时的最坏情况前沿风险。我们引入了恶意微调（MFT）方法，旨在通过微调gpt-oss，使其在生物学和网络安全两个领域的能力达到最大化。为了最大化生物风险（biorisk），我们策划了与威胁制造相关的任务，并在具备网页浏览功能的强化学习环境中训练gpt-oss。为了最大化网络安全风险，我们在一个具备代理编码能力的环境中训练gpt-oss，以解决夺旗赛（CTF）挑战。我们将这些经过恶意微调的模型与开放权重和封闭权重的大型语言模型（LLM）在前沿风险评估中进行了比较。与封闭权重的前沿模型相比，经过恶意微调的gpt-oss表现不及OpenAI的o3模型，后者在生物风险和网络安全方面的能力低于“高准备度”水平。与开放权重模型相比，gpt-oss可能略微提升了生物学能力，但并未显著推动前沿发展。综合来看，这些结果促成了我们发布该模型的决定，我们希望恶意微调方法能为评估未来开放权重模型发布可能带来的危害提供有益指导。
----------------------
Abstract
In this paper, we study the worst-case frontier risks of releasing gpt-oss. We introduce malicious fine-tuning (MFT), where we attempt to elicit maximum capabilities by fine-tuning gpt-oss to be as capable as possible in two domains: biology and cybersecurity. To maximize biological risk (biorisk), we curate tasks related to threat creation and train gpt-oss in an RL environment with web browsing. To maximize cybersecurity risk, we train gpt-oss in an agentic coding environment to solve capture-the-flag (CTF) challenges. We compare these MFT models against open- and closed-weight LLMs on frontier risk evaluations. Compared to frontier closed-weight models, MFT gpt-oss underperforms OpenAI o3, a model that is below Preparedness High capability level for biorisk and cybersecurity. Compared to open-weight models, gpt-oss may marginally increase biological capabilities but does not substantially advance the frontier. Taken together, these results contributed to our decision to release the model, and we hope that our MFT approach can serve as useful guidance for estimating harm from future open-weight releases.
via OpenAI News
摘要
本文研究了发布gpt-oss模型时的最坏情况前沿风险。我们引入了恶意微调（MFT）方法，旨在通过微调gpt-oss，使其在生物学和网络安全两个领域的能力达到最大化。为了最大化生物风险（biorisk），我们策划了与威胁制造相关的任务，并在具备网页浏览功能的强化学习环境中训练gpt-oss。为了最大化网络安全风险，我们在一个具备代理编码能力的环境中训练gpt-oss，以解决夺旗赛（CTF）挑战。我们将这些经过恶意微调的模型与开放权重和封闭权重的大型语言模型（LLM）在前沿风险评估中进行了比较。与封闭权重的前沿模型相比，经过恶意微调的gpt-oss表现不及OpenAI的o3模型，后者在生物风险和网络安全方面的能力低于“高准备度”水平。与开放权重模型相比，gpt-oss可能略微提升了生物学能力，但并未显著推动前沿发展。综合来看，这些结果促成了我们发布该模型的决定，我们希望恶意微调方法能为评估未来开放权重模型发布可能带来的危害提供有益指导。
----------------------
Abstract
In this paper, we study the worst-case frontier risks of releasing gpt-oss. We introduce malicious fine-tuning (MFT), where we attempt to elicit maximum capabilities by fine-tuning gpt-oss to be as capable as possible in two domains: biology and cybersecurity. To maximize biological risk (biorisk), we curate tasks related to threat creation and train gpt-oss in an RL environment with web browsing. To maximize cybersecurity risk, we train gpt-oss in an agentic coding environment to solve capture-the-flag (CTF) challenges. We compare these MFT models against open- and closed-weight LLMs on frontier risk evaluations. Compared to frontier closed-weight models, MFT gpt-oss underperforms OpenAI o3, a model that is below Preparedness High capability level for biorisk and cybersecurity. Compared to open-weight models, gpt-oss may marginally increase biological capabilities but does not substantially advance the frontier. Taken together, these results contributed to our decision to release the model, and we hope that our MFT approach can serve as useful guidance for estimating harm from future open-weight releases.
via OpenAI News
gpt-oss-120b & gpt-oss-20b Model Card
介绍
我们推出了 gpt-oss-120b 和 gpt-oss-20b 两款开放权重推理模型，这些模型在 Apache 2.0 许可证和我们的 gpt-oss 使用政策下提供。它们是在开源社区反馈的基础上开发的，仅支持文本输入，兼容我们的 Responses API，设计用于具备强指令遵循能力的代理工作流，支持工具使用（如网页搜索和 Python 代码执行）及推理能力——包括能够根据任务复杂度调整推理力度。模型可定制，支持完整的链式思维（CoT）和结构化输出。
安全性是我们开放模型方法的基础。这些模型与专有模型存在不同的风险特征：一旦发布，决心坚定的攻击者可能会对其进行微调，以绕过安全拒绝机制或直接优化有害行为，而 OpenAI 无法实施额外的缓解措施或撤销访问权限。
在某些情况下，开发者和企业需要实施额外的安全保障措施，以复制通过我们的 API 和产品提供的模型所内置的系统级保护。我们将此文档称为模型卡，而非系统卡，因为 gpt-oss 模型将作为各种系统的一部分被广泛使用，这些系统由不同的利益相关者创建和维护。虽然模型默认设计遵循 OpenAI 的安全政策，但其他利益相关者也会做出并实施自己的决策，以确保这些系统的安全。
我们对 gpt-oss-120b 进行了可扩展能力评估，确认该默认模型在我们准备框架的三个跟踪类别（生物与化学能力、网络能力和 AI 自我改进）中均未达到高能力的指示阈值。我们还调查了两个额外问题：
● 对抗性行为者是否能通过微调 gpt-oss-120b，使其在生物与化学或网络领域达到高能力？模拟攻击者的潜在行为，我们对 gpt-oss-120b 进行了针对这两个类别的对抗性微调。OpenAI 安全咨询组（SAG）审查了该测试，结论是即使利用 OpenAI 领先的训练技术进行强力微调，gpt-oss-120b 仍未达到生物与化学风险或网络风险的高能力水平。
● 发布 gpt-oss-120b 是否会显著推动开放基础模型在生物能力领域的前沿？我们的发现是否定的：在大多数评估中，一个或多个现有开源模型的默认表现已接近 gpt-oss-120b 对抗性微调后的表现。
作为此次发布的一部分，OpenAI 重申其致力于推动有益 AI 发展并提升整个生态系统安全标准的承诺。
----------------------
Introduction
We introduce gpt-oss-120b and gpt-oss-20b, two open-weight reasoning models available under the Apache 2.0 license and our gpt-oss usage policy. Developed with feedback from the open-source community, these text-only models are compatible with our Responses API and are designed to be used within agentic workflows with strong instruction following, tool use like web search and Python code execution, and reasoning capabilities—including the ability to adjust the reasoning effort for tasks that don’t require complex reasoning. The models are customizable, provide full chain-of-thought (CoT), and support Structured Outputs.
Safety is foundational to our approach to open models. They present a different risk profile than proprietary models: Once they are released, determined attackers could fine-tune them to bypass safety refusals or directly optimize for harm without the possibility for OpenAI to implement additional mitigations or to revoke access.
In some contexts, developers and enterprises will need to implement extra safeguards in order to replicate the system-level protections built into models served through our API and products. We’re terming this document a model card, rather than a system card, because the gpt-oss models will be used as part of a wide range of systems, created and maintained by a wide range of stakeholders. While the models are designed to follow OpenAI’s safety policies by default, other stakeholders will also make and implement their own decisions about how to keep those systems safe.
We ran scalable capability evaluations on gpt-oss-120b, and confirmed that the default model does not reach our indicative thresholds for High capability in any of the three Tracked Categories of our Preparedness Framework (Biological and Chemical capability, Cyber capability, and AI Self-Improvement). We also investigated two additional questions:
● Could adversarial actors fine-tune gpt-oss-120b to reach High capability in the Biological and Chemical or Cyber domains? Simulating the potential actions of an attacker, we adversarially fine-tuned the gpt-oss-120b model for these two categories. OpenAI’s Safety Advisory Group (“SAG”) reviewed this testing and concluded that, even with robust fine-tuning that leveraged OpenAI’s field-leading training stack, gpt-oss-120b did not reach High capability in Biological and Chemical Risk or Cyber risk.
● Would releasing gpt-oss-120b significantly advance the frontier of biological capabilities in open foundation models? We found that the answer is no: For most of the evaluations, the default performance of one or more existing open models comes near to matching the adversarially fine-tuned performance of gpt-oss-120b.
As part of this launch, OpenAI is reaffirming its commitment to advancing beneficial AI and raising safety standards across the ecosystem.
via OpenAI News
介绍
我们推出了 gpt-oss-120b 和 gpt-oss-20b 两款开放权重推理模型，这些模型在 Apache 2.0 许可证和我们的 gpt-oss 使用政策下提供。它们是在开源社区反馈的基础上开发的，仅支持文本输入，兼容我们的 Responses API，设计用于具备强指令遵循能力的代理工作流，支持工具使用（如网页搜索和 Python 代码执行）及推理能力——包括能够根据任务复杂度调整推理力度。模型可定制，支持完整的链式思维（CoT）和结构化输出。
安全性是我们开放模型方法的基础。这些模型与专有模型存在不同的风险特征：一旦发布，决心坚定的攻击者可能会对其进行微调，以绕过安全拒绝机制或直接优化有害行为，而 OpenAI 无法实施额外的缓解措施或撤销访问权限。
在某些情况下，开发者和企业需要实施额外的安全保障措施，以复制通过我们的 API 和产品提供的模型所内置的系统级保护。我们将此文档称为模型卡，而非系统卡，因为 gpt-oss 模型将作为各种系统的一部分被广泛使用，这些系统由不同的利益相关者创建和维护。虽然模型默认设计遵循 OpenAI 的安全政策，但其他利益相关者也会做出并实施自己的决策，以确保这些系统的安全。
我们对 gpt-oss-120b 进行了可扩展能力评估，确认该默认模型在我们准备框架的三个跟踪类别（生物与化学能力、网络能力和 AI 自我改进）中均未达到高能力的指示阈值。我们还调查了两个额外问题：
● 对抗性行为者是否能通过微调 gpt-oss-120b，使其在生物与化学或网络领域达到高能力？模拟攻击者的潜在行为，我们对 gpt-oss-120b 进行了针对这两个类别的对抗性微调。OpenAI 安全咨询组（SAG）审查了该测试，结论是即使利用 OpenAI 领先的训练技术进行强力微调，gpt-oss-120b 仍未达到生物与化学风险或网络风险的高能力水平。
● 发布 gpt-oss-120b 是否会显著推动开放基础模型在生物能力领域的前沿？我们的发现是否定的：在大多数评估中，一个或多个现有开源模型的默认表现已接近 gpt-oss-120b 对抗性微调后的表现。
作为此次发布的一部分，OpenAI 重申其致力于推动有益 AI 发展并提升整个生态系统安全标准的承诺。
----------------------
Introduction
We introduce gpt-oss-120b and gpt-oss-20b, two open-weight reasoning models available under the Apache 2.0 license and our gpt-oss usage policy. Developed with feedback from the open-source community, these text-only models are compatible with our Responses API and are designed to be used within agentic workflows with strong instruction following, tool use like web search and Python code execution, and reasoning capabilities—including the ability to adjust the reasoning effort for tasks that don’t require complex reasoning. The models are customizable, provide full chain-of-thought (CoT), and support Structured Outputs.
Safety is foundational to our approach to open models. They present a different risk profile than proprietary models: Once they are released, determined attackers could fine-tune them to bypass safety refusals or directly optimize for harm without the possibility for OpenAI to implement additional mitigations or to revoke access.
In some contexts, developers and enterprises will need to implement extra safeguards in order to replicate the system-level protections built into models served through our API and products. We’re terming this document a model card, rather than a system card, because the gpt-oss models will be used as part of a wide range of systems, created and maintained by a wide range of stakeholders. While the models are designed to follow OpenAI’s safety policies by default, other stakeholders will also make and implement their own decisions about how to keep those systems safe.
We ran scalable capability evaluations on gpt-oss-120b, and confirmed that the default model does not reach our indicative thresholds for High capability in any of the three Tracked Categories of our Preparedness Framework (Biological and Chemical capability, Cyber capability, and AI Self-Improvement). We also investigated two additional questions:
● Could adversarial actors fine-tune gpt-oss-120b to reach High capability in the Biological and Chemical or Cyber domains? Simulating the potential actions of an attacker, we adversarially fine-tuned the gpt-oss-120b model for these two categories. OpenAI’s Safety Advisory Group (“SAG”) reviewed this testing and concluded that, even with robust fine-tuning that leveraged OpenAI’s field-leading training stack, gpt-oss-120b did not reach High capability in Biological and Chemical Risk or Cyber risk.
● Would releasing gpt-oss-120b significantly advance the frontier of biological capabilities in open foundation models? We found that the answer is no: For most of the evaluations, the default performance of one or more existing open models comes near to matching the adversarially fine-tuned performance of gpt-oss-120b.
As part of this launch, OpenAI is reaffirming its commitment to advancing beneficial AI and raising safety standards across the ecosystem.
via OpenAI News
#Announcement #OpenAI
OpenAI 现已开源两款模型：
- gpt-oss-120b
- gpt-oss-20b
120b 宣称性能略弱于 o4-mini。
https://openai.com/open-models/
via AI Copilot - Telegram Channel
OpenAI 现已开源两款模型：
- gpt-oss-120b
- gpt-oss-20b
120b 宣称性能略弱于 o4-mini。
https://openai.com/open-models/
via AI Copilot - Telegram Channel
Openai
Open models by OpenAI
Advanced open-weight reasoning models to customize for any use case and run anywhere.
via LoopDNS资讯播报 - Telegram Channel
同时所有受支持语言的补全都更加智能，现在具有对 SQL、YAML、JSON、Markdown 等语言的支持
via LoopDNS资讯播报 - Telegram Channel
#Update #Claude
Claude Opus 4.1 现已发布，小幅改进了编程、研究和数据分析能力。
现已通过 API 和 Claude App 提供（需要订阅）。
via AI Copilot - Telegram Channel
Claude Opus 4.1 现已发布，小幅改进了编程、研究和数据分析能力。
现已通过 API 和 Claude App 提供（需要订阅）。
via AI Copilot - Telegram Channel
Anthropic发布功能更加强大的AI模型Opus 4.1
抢在ChatGPT-5之前，Anthropic发布功能更加强大的AI模型Opus 4.1，编程、研究、数据分析能力都更加强大。(格隆汇)
via LoopDNS资讯播报 - Telegram Channel
抢在ChatGPT-5之前，Anthropic发布功能更加强大的AI模型Opus 4.1，编程、研究、数据分析能力都更加强大。(格隆汇)
via LoopDNS资讯播报 - Telegram Channel
BugBot Service Degradation due to GitHub Outage
Aug 5, 15:45 UTC
Monitoring - Due to a GitHub service outage, some BugBot functionality may be temporarily unavailable.
Once the outage is resolved, all services should resume normal operations shortly after.
https://www.githubstatus.com/
Aug 5, 15:40 UTC
Investigating - We are investigating an internal alert regarding BugBot errors.
via Cursor Status - Incident History
Aug 5, 15:45 UTC
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🤖 美国政府将OpenAI、Google和Anthropic列入联邦机构AI供应商名单
美国政府已将OpenAI、Google和Anthropic三家公司列入获准向民间联邦机构提供人工智能服务的供应商名单。这些公司将通过新的联邦承包平台“多重奖励计划”（MSA）提供AI工具，该平台允许政府机构通过预先协商的合同获取AI服务，从而避免单独谈判。负责MSA的美国总务管理局（GSA）表示，对这些科技公司的评估基于安全性和性能。此举是在特朗普总统发布一项侧重于人工智能发展的行政命令之后进行的，该命令包括调整环境标准以增加数据中心能源供应，并指示联邦机构仅使用“不受意识形态偏见”的人工智能。
(IT业界资讯)
via 茶馆 - Telegram Channel
美国政府已将OpenAI、Google和Anthropic三家公司列入获准向民间联邦机构提供人工智能服务的供应商名单。这些公司将通过新的联邦承包平台“多重奖励计划”（MSA）提供AI工具，该平台允许政府机构通过预先协商的合同获取AI服务，从而避免单独谈判。负责MSA的美国总务管理局（GSA）表示，对这些科技公司的评估基于安全性和性能。此举是在特朗普总统发布一项侧重于人工智能发展的行政命令之后进行的，该命令包括调整环境标准以增加数据中心能源供应，并指示联邦机构仅使用“不受意识形态偏见”的人工智能。
(IT业界资讯)
via 茶馆 - Telegram Channel
