#Gemini 4 Argon

118 stories · 3 in 7 days · 22 in 30 days
Stories, products and papers tagged "Gemini 4 Argon", newest first.
Nov 14
PapersBuildersMulti-source00:53
Chinese contentGoogle DeepMind 论文:多智能体攻击可突破 Gemini 4 Argon 的提示注入防御

DeepMind 用 8 组攻击智能体互相学习迭代,结果 Gemini 4 Argon 也被攻破 34% 的任务,开源模型更是几乎全败。做智能体工具调用的开发者都得看看,别以为人测不出漏洞就安全了。

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rohanpaul_ai@rohanpaul_aiSource
Nov 11
ModelsUS vs ChinaMulti-source79°01:12
Chinese contentClaude Fable 5.2 登顶 AA-3D 3D 构建基准

Anthropic 新的 Claude Fable 5.2 在 3D 交互构建基准上比自家上代高出 132 分,也压过 GPT-6 Astra 和 Gemini 4 Argon 一大截。做 3D 内容生成、交互原型的开发者可以换它试试,Elo 分差说明优势不是测试波动。

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Official accountArtificial Analysis@ArtificialAnlysSource
Chinese contentApple 论文:Claude Opus 5.5 直接控制机械臂,零样本成绩超 VLA 专用模型

苹果没训练任何机器人模型,只把 Claude Opus 5.5 接上摄像头和机械臂,RoboLab-120 上零样本就拿到 85.6%,比专门训过的 VLA 高了近一倍。做机器人或具身智能的值得看看这个思路,缺点是实时性还跟不上。

rohanpaul_ai@rohanpaul_aiSource
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How-toBuildersSelected14:31
Code Mode: Agents Collapse Tool Calls into Typed Code Sandboxes

The shift from listing dozens of MCP tools to writing code against them changes how agents scale with large toolsets, cutting token overhead and improving reliability. Developers building agent workflows can try the Gemini 4 Argon example or the pi framework directly. Schmid's bet that MCP remains the underlying protocol, just invoked through code, is a useful planning signal for anyone wiring up tool infrastructure.

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Philipp Schmid@_philschmidSource
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Oct 15
ModelsUS vs ChinaMulti-sourceSelected19:29
Gemini 4 Argon scores 165 on Epoch Capabilities Index

The gap between Google and the ECI frontier has narrowed to 2 points, putting Gemini back in competitive range after months of lag. Teams choosing models for hard reasoning or agentic workloads now have a four-way race to benchmark on their own tasks rather than defaulting to a single leader. Comparable scores across Opus 5.5, GPT-6 Astra and Argon suggest provider switching costs are lower than vendor benchmarks imply.

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Official accountEpoch AI@EpochAIResearchSource