搜索“Google DeepMind”

Google DeepMind 发布 Gemini 3.5 Live Translate，可自动识别 70 多种语言并持续生成近实时译音，同时保留说话者的语调、节奏和音高。该模型仅落后说话者数秒，支持嘈杂环境和多语言输入。它正向 Android、iOS 版 Google Translate 全球推送，Google Meet 将于本月面向部分企业 Workspace 客户开启私密预览。 · Google DeepMind has released Gemini 3.5 Live Translate, which automatically detects more than 70 languages and continuously produces near-real-time translated speech while preserving the speaker’s intonation, pacing, and pitch. The model stays only a few seconds behind the speaker and supports noisy env

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Google DeepMind 的多智能体系统 Co-Scientist 帮助 Gary Peltz 加快寻找肝纤维化疗法，筛选出此前被忽视的药物再利用候选方案。其中一个候选药物在实验室测试中成功阻断了 91% 与瘢痕形成相关的反应，相关成果已发表于 Advanced Science。 · Google DeepMind’s multi-agent system Co-Scientist helped Gary Peltz accelerate the search for liver fibrosis treatments by identifying overlooked drug-repurposing candidates. One candidate successfully blocked 91% of a scarring-linked response in laboratory tests, with the results published in Advanced Science.

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Google DeepMind 为实验性原型 Project Genie 推出 Street View 地图影像接地能力，使其生成的交互式世界能够以现实地点为起点。用户可在美国选择地点、视觉风格和角色，探索或重新构想现实场景；该功能现已可用，并计划逐步扩展到更多地区。 · Google DeepMind has launched Street View imagery grounding for its experimental Project Genie prototype, allowing its generated interactive worlds to begin from real-world locations. Users can select a place in the U.S., a visual style and a character to explore or reimagine real settings; the capability is available now, with plans to expand to more places ove

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Google DeepMind 推出面向复杂智能体工作流的 Gemini 3.5 系列，率先发布 3.5 Flash，并计划下月推出 3.5 Pro。3.5 Flash 在 Terminal-Bench 2.1 获得 76.2%，输出速度为其他前沿模型的 4 倍。该模型已全面开放，并成为 Gemini 应用和全球搜索 AI Mode 的默认模型。 · Google DeepMind introduced the Gemini 3.5 family for complex agentic workflows, beginning with 3.5 Flash, while 3.5 Pro is planned for next month. Gemini 3.5 Flash scores 76.2% on Terminal-Bench 2.1 and produces output tokens four times faster than other frontier models. It is generally available and is now the default mo

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Google DeepMind 使用由 Gemini 驱动的编码智能体 AlphaEvolve 改进 DNA 测序纠错模型 DeepConsensus，使变异检测错误减少 30%。这些改进正帮助 PacBio 科学家以更低成本、更准确地分析遗传数据，并可能发现此前隐藏的致病突变。 · Google DeepMind used its Gemini-powered coding agent AlphaEvolve to improve DeepConsensus, a DNA sequencing error-correction model, reducing variant detection errors by 30%. The improvements are helping PacBio scientists analyze genetic data more accurately and at lower cost, potentially enabling the discovery of previously hidden disease-causing mutation

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Google DeepMind 推出 Decoupled DiLoCo，通过异步连接相互解耦的计算“岛”，以较低带宽跨远程数据中心训练大语言模型，并隔离硬件故障。团队使用 2-5 Gbps 广域网络，在美国四个地区完成 120 亿参数模型的预训练，速度较传统同步方法快 20 倍以上。Gemma 4 测试显示，该架构在故障下保持更高可用性，并达到与传统训练相同的基准性能。 · Google DeepMind introduced Decoupled DiLoCo, which asynchronously connects decoupled compute “islands” to train LLMs across distant data centers with lower bandwidth while isolating hardware failures. The team pretrained a 12-billion-parameter model across four U.S. regions using 2-5 Gbps wide-area networking,

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