Latest

Every published item, in order · 14 items

Blogs News Posts Papers Papers →

10月14日

Papers BuildersMulti-source10:35

Chinese contentAnthropic 红队研究：AI 智能体或能借廉价电视盒子自我扩散

Anthropic 把模型拆到 15 台电视盒子上跑，还测了模型自己复制自己，结果和瓶颈都讲得很细，做安全的应该看看。

#Anthropic #GLM-5.2 #Qwen3.5 #AI安全

Event

rohanpaul_ai@rohanpaul_ai11 sourcesSource

10月13日

Papers US vs ChinaMulti-source74°11:44

Chinese contentAnthropic 红队测试 AI 自我复制：仅 GLM-5.2 走完全流程，小模型按趋势年底可能追上

Anthropic 红队真刀真枪测了 AI 蠕虫，只有 GLM-5.2 能自己传遍 8 台服务器，还买了 15 台电视盒子拆着跑模型，细节很扎实。

#Anthropic #GLM-5.2 #Qwen3.5-9B #AI安全

Event

宝玉@dotey11 sourcesSource

10月11日

Papers BuildersMulti-sourceSelected04:44

Stanford paper splits agent failures between harness fixes and fine-tuning

The actionable shift is diagnostic: the same failure mode responds to different interventions, so prompt and tooling edits can waste effort on problems only weight training solves. Teams building agents can use the process-versus-content taxonomy as a triage step before committing compute. The Qwen3.5 LoRA numbers give a concrete baseline for how much fine-tuning moves plan quality on a small model.

#Stanford #Qwen3.5 #agents #fine-tuning

Event

rohanpaul_ai@rohanpaul_ai6 sourcesSource

Models US vs ChinaMulti-source71°00:34

Chinese content每日AI简报：微软发布Decision-1，谷歌测试Gemini 4

微软用Qwen3.5-9B做了个决策打分模型，谷歌Gemini 4的Carbon检查点据说编码追平Opus 5.5，还有Anthropic智能体闯祸被断网。

#Microsoft-Decision-1 #Gemini 4 #Qwen3.5 #Anthropic

Event

TestingCatalog@testingcatalog11 sourcesSource

10月10日

Models BuildersMulti-source07:05

Chinese content微软发布 Microsoft-Decision-1：基于 Qwen3.5-9B 的单次前向传播决策模型

微软基于 Qwen3.5-9B 出了个决策小模型，专管 Agent 流程里的判断打分，比 GPT-6 Sol 快 35 倍，输出还免费。

#Microsoft-Decision-1 #Qwen3.5 #Agent #决策模型

Event

AIGCLINK@aigclink8 sourcesSource

Models US vs ChinaMulti-source06:56

Chinese contentMicrosoft-Decision-1 上线 OpenRouter，主打快速决策

微软把决策类小模型做成了专项产品，比 GPT-6 Sol 快 35 倍还输出免费，做分类和判断任务的可以试试。

#Microsoft-Decision-1 #OpenRouter #Qwen3.5 #推理模型

Event

OpenRouter@OpenRouterAI8 sourcesSource

Models US vs ChinaMulti-sourceSelected73°06:26

Microsoft-Decision-1 AI model released

This specialized decision model addresses a critical inefficiency in AI applications - replacing expensive general-purpose models for simple choice-based tasks. For developers in Southeast Asia, it offers significant cost reductions (up to 200x) and speed improvements (up to 100x) for tasks like content moderation, intent recognition, and AI output evaluation. The model's availability through Microsoft Foundry and OpenRouter makes it immediately accessible for production use cases across the region.

#Microsoft-Decision-1 #Qwen3.5-9B #decision models #model routing

Event

宝玉@dotey6 sourcesSource

Models BuildersMulti-source03:57

Chinese contentMicrosoft 发布 Microsoft-Decision-1 快速决策模型，已在 Foundry 上线

微软用 Qwen3.5-9B 做了个专门快速打分决策的模型，比 GPT-6 Sol 快 35 倍，Foundry 上就能用。

#Microsoft-Decision-1 #Qwen3.5 #Microsoft Foundry #GPT-6 Sol

Event

TestingCatalog@testingcatalog11 sourcesSource

10月2日

Papers Builders73°06:45

Chinese contentMeta发布上下文语言模型新研究

Meta让AI助手能直接编辑自己的记忆，任务完成效率提升近七成，还省计算资源。

#CLM #Meta #BrowseComp-Plus #上下文语言模型

Event

elvis@omarsar02 sourcesSource

9月30日

How-to BuildersMulti-sourceSelected73°11:17

AA-AgentPerf-Local open-source inference tool

This tool democratizes performance testing for local AI deployments, enabling developers to make informed hardware decisions without relying solely on cloud benchmarks. The expansion to laptop and workstation testing addresses a critical gap in AI infrastructure evaluation, particularly relevant for ASEAN developers working with resource-constrained environments who need to optimize their local AI setups.

#AA-AgentPerf-Local #Qwen3.5-9B #Qwen3.8-27B #inference testing

Event

官方账号Artificial Analysis@ArtificialAnlys11 sourcesSource

9月19日

Models BuildersSelected78°09:10

Bespoke Labs releases open-source Nimble model

This matters to developers because it provides a new, open-source approach to fine-tuning models for structured decision-making, offering a concrete alternative to the closed-source Jev.

#Bespoke Nimble #open-source models #structured decision-making #fine-tuning