🚨 AI News | TestingCatalog@testingcatalog · 6月4日46

GOOGLE 🔥: A new Dreambeans experiment is now available in Google Labs for US-based Google AI Ultra users on the waitlist. This experiment uses Personal Intelligence to deliver daily stories based on the user's data context. Not a testing time for the most 👀

译GOOGLE 🔥: 一项新的 Dreambeans 实验现已于 Google Labs 上线，面向美国地区的 Google AI Ultra 用户（需加入候补名单）。 该实验利用个人智能，根据用户的数据上下文提供每日故事。 对大多数人来说，这并非测试时间👀

🚨 AI News | TestingCatalog@testingcatalog · 6月4日65

GOOGLE 🔥: A new Gemma 4 12B is now available on Huggingface under Apache 2.0 license! > Built with the same multimodal functionality as Gemma 4 E2B and E4B (text, audio, image, and video inputs), it brings native audio and vision understanding directly to local environments without the need for separate encoders. > This unified approach to multimodality makes the model encoder-free, offering a deployment size that is perfect for consumer devices and streamlined local execution.

译Google 最新的 Gemma 4 12B 模型已上线 Hugging Face，采用 Apache 2.0 许可证。该模型与 Gemma 4 E2B/E4B 共享相同多模态能力，支持文本、音频、图像和视频输入，无需单独编码器即可实现原生音频和视觉理解。这种无编码器统一设计方案使其部署体积更小，非常适合消费级设备和本地执行环境。官方称其旨在弥合边缘效率与高级推理之间的差距。

Google AI Developers@googleaidevs · 6月4日77

We’re launching Gemma 4 12B: Our unified, encoder-free model that brings powerful multimodal intelligence straight to your laptop 🚀 The model bridges the gap between our mobile E4B model and larger 26B MoE models, packaging frontier-class reasoning and native audio into a highly optimized footprint, all under a permissive Apache 2.0 license. Here’s what makes it unique: + Encoder-Less Architecture: We removed the multimodal encoders. The vision and audio inputs flow directly into the LLM backbone. + Agentic Performance (16GB VRAM): Run complex, multi-step workflows locally, with performance nearing our 26B model.

译Google发布Gemma 4 12B，一款无编码器的统一多模态模型，可直接将视觉和音频输入送入LLM主干，无需传统多模态编码器。该模型填补了移动端E4B模型与26B MoE模型之间的空白，封装前沿推理与原生音频能力，采用Apache 2.0许可。在16GB VRAM下即可本地运行复杂多步骤智能体工作流，性能接近26B模型。

Sundar Pichai@sundarpichai · 6月4日70

On Monday we announced an equity offering for Alphabet - part of our multi-year investment strategy to meet the AI opportunity ahead and support the demand we’re seeing from enterprises and consumers. Pleased to share the offering was well over-subscribed. We raised a total of ~$45B, with an additional $40B to come as part of an “at the market” program starting in Q3 (for a total of ~ $85B). A huge thank you to our investors, including Berkshire Hathaway who invested $10B.

译周一我们宣布了Alphabet的股权融资——这是我们多年投资策略的一部分，旨在抓住未来的AI机遇并支持我们看到的来自企业和消费者的需求。很高兴告诉大家，此次融资已大幅超额认购。我们共募集了约450亿美元，另将通过Q3启动的“按市价发行”计划再募集400亿美元（总计约850亿美元）。非常感谢我们的投资者，包括投资了100亿美元的伯克希尔·哈撒韦。

Google Gemini@GeminiApp · 6月3日67

Join @GoogleDeepMind Principal Engineer @__apf__ to walk through how Gemini Spark helps simplify your daily workflows. Powered by Gemini 3.5 Flash, Spark builds upon Gemini's ability to connect with @GoogleWorkspace apps like Docs and Gmail to execute complex tasks.

译参加 @GoogleDeepMind 首席工程师 @__apf__ 的演示，了解 Gemini Spark 如何帮助简化您的日常工作流程。由 Gemini 3.5 Flash 驱动，Spark 建立在 Gemini 与 @GoogleWorkspace 应用（如 Docs 和 Gmail）连接的能力之上，以执行复杂任务。

elvis@omarsar0 · 6月3日72

New research from Google. Just shows the impressive results you can get from custom agent harnesses. LEAP wraps a general-purpose LLM in an agentic scaffold that grounds every step in the Lean compiler and iterates against verifier feedback. The same general model solves all 12 Putnam 2025 problems and lifts Lean-IMO-Bench one-shot solve rate from under 10% to 70%, beating a specialized gold-medal system that scores 48%. Paper: https://arxiv.org/abs/2606.03303 Learn to build effective AI agents in our academy: https://academy.dair.ai/

译Google 新研究 LEAP 将通用大语言模型封装在智能体框架中，每个步骤基于 Lean 编译器，并依赖验证器反馈进行迭代。同一通用模型解决了全部 12 道 Putnam 2025 问题，并将 Lean-IMO-Bench 一次性解决率从不到 10% 提升至 70%，击败了得分 48% 的专业金牌系统。论文链接：https://arxiv.org/abs/2606.03303。

Josh Woodward@joshwoodward · 6月3日53

✅ Papercut fixed: Thinking Levels are now available on Gemini across Web, iOS, and Android.

译✅ 已修复：思考级别功能现已在 Gemini 的 Web、iOS 和 Android 平台上线。

Berryxia.AI@berryxia · 6月3日76

兄弟们，Google DeepMind 团队又来整活儿！ Google DeepMind的最新发布，直接把“AI能帮科学家干嘛”这个老问题彻底翻篇了。 他们把Gemini做成了一个叫Co-Scientist的多Agent系统。 不是简单问答工具，是完整复制了科学家从idea到验证的整个循环：生成上千个假设、举办“idea锦标赛”、让多个Agent展开科学辩论、互相批判精炼，最后用文献、数据和搜索工具把每个主张落地验证。 以前科研最卡的环节，就是一个人脑力有限，生成好假设、反复辩论、跨领域拉新知识都要靠自己。 现在Co-Scientist把这个过程变成可规模化的流水线。 过去一年他们和全球顶尖科学家一起测，在肝纤维化新靶点、肌萎缩侧索硬化（ALS）新疗法、逆转衰老的遗传线索这些超级复杂的问题上，都拿出了真正有潜力的新方向。 最反直觉的一点是：它不是来取代科学家的，只是真正成了“专职研究伙伴”。 科学家终于可以把脑力从“反复想假设、反复查文献”里解放出来，专注在最有创造力的判断和实验设计上。 AI把以前只有顶尖团队才玩得起的“高强度idea迭代”变成了人人可用的基础设施。 现在他们已经把Hypothesis Generation功能开放给个人研究者，直接通过Gemini for Science就能用。 普通研究员也能拥有一个24小时不睡觉、能辩论、能验证、还能不断进化的AI合作者。 这其实戳破了当前最主流的误解：很多人以为AI会让科学家失业，结果真实路径是AI把科学发现的速度和广度直接拉高一个数量级，让更多人能真正参与到突破性研究里。

译Google DeepMind发布了基于Gemini的多Agent系统Co-Scientist，旨在实现科研流程自动化。该系统能够生成、辩论和验证假设，帮助科学家从高强度脑力劳动中解放出来。过去一年，它已在肝纤维化新靶点、ALS新疗法等复杂问题上与科学家合作探索出新方向。其定位并非取代科学家，而是作为“专职研究伙伴”。目前，其假设生成功能已通过Gemini for Science向个人研究者开放。

🚨 AI News | TestingCatalog@testingcatalog · 6月3日44

GOOGLE 🔥: NotebookLM will get a new "Planning Mode" for Video Overviews. This also likely signals that Google is upgrading Video Overviews to rely on recently released Gemini Omni!

译GOOGLE 🔥: NotebookLM 将为视频概述新增一个“规划模式”。 这也可能意味着 Google 正在升级视频概述功能，使其依赖于近期发布的 Gemini Omni！

NotebookLM@NotebookLM · 6月3日58

Notice anything different about the NotebookLM mobile app recently? 😉 Well, we’re excited to REPORT that you can now create briefing docs, study guides, and blog posts on-the-go! 📱✨ Are there any other report formats you'd want specifically for mobile? Let us know!

译注意到 NotebookLM 移动应用最近有什么不同了吗？😉 我们很高兴地宣布，你现在可以在移动端创建简报文档、学习指南和博客文章了！📱✨ 还有其他你希望在移动端特别支持的报告格式吗？请告诉我们！

fofr@fofrAI · 6月3日57

This is 🔥

译这是🔥 [引用 @DavidMaliglowka]：Gemini Omni 🏕️ 提示词在 🧵

Ethan Mollick@emollick · 6月3日47

Law professors wrote questions they were asked during office hours. Gemini 2.5 & humans answered them then other law professors blindly judged the results: -Gemini had a 75% win rate vs. professors -Gemini's answers were rated LESS harmful than humans -Newer models do even better

译法学教授们写下了他们在办公时间被学生问到的问题。Gemini 2.5 和人类分别作答，然后其他法学教授在不知道答案作者的情况下对结果进行了评判： - Gemini 的胜率为 75%，击败了教授们 - Gemini 的答案被评为比人类的答案危害更小 - 更新的模型表现甚至更好

Google DeepMind@GoogleDeepMind · 6月3日61

We believe AI can be a dedicated research partner to help discover the next breakthrough. Enter Co-Scientist: our latest Gemini-based multi-agent system that can generate, debate and evolve novel hypotheses for complex scientific problems 🧵

译我们相信 AI 可以成为专属研究伙伴，帮助发现下一个突破。 隆重推出 Co-Scientist：我们最新的基于 Gemini 的多智能体系统，能够为复杂科学问题生成、辩论和演进新颖的假设 🧵

Google Gemini@GeminiApp · 6月3日41

See Gemini Omni in action with a live demo from one of the team members who helped build it. Join us on Discord as Product Manager Chloe shares how to use Gemini Omni’s multimodal inputs, real-world knowledge, and easy conversational editing to create videos like never before. 👉Join the Discord to watch live: http://discord.gg/gemini 📅 Wednesday, June 3 at 11:30am PT

译通过一位参与构建的团队成员的现场演示，了解 Gemini Omni 的实际效果。 加入我们的 Discord，产品经理 Chloe 将分享如何使用 Gemini Omni 的多模态输入、现实世界知识和便捷的对话式编辑，以前所未有的方式创建视频。 👉加入 Discord 观看直播：http://discord.gg/gemini 📅 太平洋时间 6 月 3 日星期三上午 11:30

Chubby♨️@kimmonismus · 6月2日50

At @Google I/O, I sat down with @osanseviero and @DynamicWebPaige from Google DeepMind to talk about Gemma, open models, AI Studio, on-device AI, sovereign AI and the future of AI development. A great conversation on how building with AI is becoming more open, local and accessible.

译在 Google I/O 上，我与 Google DeepMind 的 @osanseviero 和 @DynamicWebPaige 坐下来，聊了聊 Gemma、开源模型、AI Studio、端侧 AI、主权 AI 以及 AI 开发的未来。 一场关于 AI 构建如何变得更开放、更本地化、更易获取的精彩对话。

Rohan Paul@rohanpaul_ai · 6月2日82

In roughly 28 years, Google/Alphabet has tapped primary equity capital only seven times; the 2026 announced $80B raise is more than 10x all prior identified primary raises combined.

译Alphabet宣布计划通过多种方式筹集约800亿美元资金，以支持其AI算力扩张支出。该融资规模超过其过去28年间七次主要股权融资总和的10倍。融资结构包括承销股票、强制性可转换优先股、伯克希尔100亿美元的私募配售以及400亿美元的ATM计划（其中约300亿与员工股权税务相关）。市场将此举视为看涨信号，表明AI发展瓶颈已从需求和模型转向算力供应，Alphabet正通过融资投资于类似铁路、电网和晶圆厂的关键基础设施。

Rohan Paul@rohanpaul_ai · 6月2日86

Alphabet to raise $80B from share sales to fund AI spending splurge, Berkshire to invest $10B Very bullish news, as it shows again the limiting factor is no longer demand, models, or products, but compute supply. For years, the cleanest story was excess cash, buybacks, and software-like returns; now the story is closer to railroads, power grids, and fabs, where whoever can finance the bottleneck may own the toll road. Berkshire’s $10B placement gives the raise a stamp of patient capital. Alphabet is not simply selling $80B of common stock straight into the market tomorrow for AI capex. It is using a mix of underwritten stock, mandatory convertible preferred, Berkshire private placement, and a $40B ATM program, with about $30B of that ATM tied to employee equity tax mechanics. --- s206.q4cdn .com/479360582/files/doc_news/2026/Jun/01/attachments/2026-June-Alphabet-Equity-Capital-Raise-Press-Release-PDF.pdf

译Alphabet计划通过包括承销股票、可转换优先股、Berkshire的100亿美元私募配售以及一个400亿美元的市场发售计划在内的多种方式，募集高达800亿美元资金，主要用于AI基础设施投资。市场将此举视为强烈看涨信号，表明AI发展的关键瓶颈已从需求侧转向计算供给。Berkshire的投资被视为对“耐心资本”的背书，此事件也标志着行业投资逻辑正从追求软件式回报转向对铁路、电网和晶圆厂等瓶颈基础设施的重资产竞争。

Jeff Dean@JeffDean · 6月2日31

Thanks for a great @twominutepapers conversation, Károly!

译感谢与 @twominutepapers 的精彩对话，Károly！

🚨 AI News | TestingCatalog@testingcatalog · 6月2日66

Google AI Studio Build now supports many new integrations with Google services such as Gmail, Calendar, and Sheets, enabling users to vibe code apps that dynamically fetch relevant context.

译Google AI Studio Build 现在支持与 Gmail、日历和表格等 Google 服务进行多项新集成，使用户能够通过 vibe code 构建动态获取相关上下文的应用程序。

Logan Kilpatrick@OfficialLoganK · 6月2日79

We just shipped the ability to build apps that connect to Gmail, Drive, Sheets, and more directly inside of @GoogleAIStudio, no navigating to other sites, you can add testers right inside of AI Studio, with full public sharing coming soon!!

译我们刚刚上线了在 @GoogleAIStudio 内直接构建连接 Gmail、Drive、Sheets 等应用的功能，无需跳转其他网站，你可以直接在 AI Studio 内添加测试人员，完整的公开分享功能即将推出！！

Logan Kilpatrick@OfficialLoganK · 6月2日53

We just shipped the first iteration of API Key breakdown of your Gemini API usage 🗝️, you can now filter your request chart via API key! More granular controls in other areas coming soon : )

译我们刚刚发布了 Gemini API 用量按 API Key 分类的首个版本 🗝️，你现在可以通过 API Key 来筛选请求图表了！其他领域更精细的控制功能也将很快推出 : )

Google AI Developers@googleaidevs · 6月2日68

From clutter to clarity. Watch parallel subagents in @Antigravity sort and rename hundreds of marketing assets, eliminating manual file management.

译从杂乱到清晰。观看 @Antigravity 中的并行子智能体对数百个营销资产进行分类和重命名，消除手动文件管理。

Berryxia.AI@berryxia · 6月2日77

卧槽！Gemink Omini 可以直接制作数字人了啊！ 三步搞定、赶紧试试呢！ 今天Gemini官方账号发了这条制作自己的数字人的教程！ 该功能已经上线：用Gemini Omni创建属于你自己的数字头像（Digital Avatar），它不光外貌像你，连声音都克隆了。 做好后，在视频创作工具里直接选中，就能把自己“放进去”。 具体操作三步走（直接抄作业）： 1. 打开Gemini App或网页 http://gemini.google.com 2. 设置菜单里点“Avatar” 3. 跟着提示拍几张照片+录几句语音，系统自动生成你的数字分身 生成完后，在工具栏选你的Avatar，就能直接用在视频里。整个过程对普通用户几分钟搞定，完全不需要专业设备。 最关键的一点：所有用Gemini Omni生成的视频，都会自动嵌入不可见SynthID数字水印。 你随时可以在Gemini App里验证一段视频到底是不是AI生成的、谁生成的。 这一步直接把“深假风险”按死在源头，比很多竞品只喊口号强太多。 为什么这个功能现在特别狠？ • 以前AI视频是你指挥AI，现在是你自己变成主角。想做个人vlog、教学视频、品牌 内容，直接把自己塞进去，真实感拉满。 • 对教育、营销、内容创作者来说，这是降维打击：以前要请真人出镜、剪辑，现在自己克隆一个分身24小时待命。

译Gemini Omni现已上线数字头像（Avatar）创建功能。用户可通过Gemini App或网页，按三步流程（拍照、录语音、系统自动生成）创建外观和声音都像自己的数字分身。该功能可直接应用于视频创作，显著降低了制作个人视频内容的门槛。所有由Gemini Omni生成的视频均自动嵌入SynthID数字水印，可用于验证视频是否为AI生成及出处，以技术手段防范深假风险。

Google Gemini@GeminiApp · 6月2日71

Easily add yourself to your video creations in Gemini. Here’s how to create your own digital avatar that looks and sounds like you with Gemini Omni. 🧵

译轻松将自己添加到Gemini的视频创作中。 以下是如何使用Gemini Omni创建一个外观和声音都像你的数字分身。🧵

Chubby♨️@kimmonismus · 5月31日75

Interesting updates on Apple AI: As Apple's WWDC lands next month, and the long-delayed Siri and on-device AI upgrades are expected to be the centerpiece: a smaller, distilled version of Google's Gemini running locally on iPhone silicon, pitched on privacy and lower token costs. Most of that stack is sourced from elsewhere. The local model is distilled from Gemini. Queries too heavy for the device route to Google Cloud (!), where Apple has now signed off on Nvidia's confidential-compute tech to process them. Apple is also reportedly hunting for small on-device-AI startups to speed up the model-shrinking work, having looked at Liquid AI among others. One quiet shift from the 2024 rollout: Apple promised then that anything leaving your iPhone would run on Apple silicon inside Private Cloud Compute. It couldn't get the full Gemini running there, so those queries now sit in Google Cloud. The Private Cloud Compute name is staying anyway. Via The Information

译苹果下月WWDC将重点展示延迟已久的Siri及设备端AI升级，核心是在iPhone芯片本地运行从Google Gemini蒸馏而来的更小模型，以强调隐私与降低token成本。但该技术栈大部分源自外部：本地模型由Gemini蒸馏，设备无法处理的复杂查询将路由至Google Cloud处理，并采用了Nvidia的机密计算技术。苹果据称正在寻觅小型设备端AI初创公司以加速模型缩减工作。此外，苹果2024年承诺的Private Cloud Compute方案原计划使用苹果芯片，因无法承载完整Gemini模型，现已部分转向谷歌云，但该名称仍将保留。

🚨 AI News | TestingCatalog@testingcatalog · 5月31日40

ICYMI 👀: Top 3 things to expect from NotebookLM soon. 1. A new Canvas artifact, allowing users to visualize information from their sources as a web artifact. 2. Personal Preferences, grounding across past conversations, artifacts, and customization instructions 3. Connectors, with other Google services and potentially external apps as well. * All these features have been spotted earlier, just testing a recap format.

译ICYMI 👀：NotebookLM 即将推出的三大功能。 1. 全新的 Canvas 作品，允许用户将来源中的信息可视化为网页作品。 2. 个人偏好，基于过往对话、作品和自定义指令进行关联。 3. 连接器，与其他 Google 服务以及可能的外部应用相连。 * 所有这些功能此前已被发现，只是测试一种回顾格式。

Google AI Developers@googleaidevs · 5月30日71

ICYMI: Nano Banana Pro [gemini-3-pro-image] and Nano Banana 2 [gemini-3.1-flash-image] are now GA and ready for production via the Gemini API. Check out these great community examples to see the capabilities of both models in action 🧵

译ICYMI：Nano Banana Pro [gemini-3-pro-image] 和 Nano Banana 2 [gemini-3.1-flash-image] 现已正式发布，可通过 Gemini API 投入生产使用。 查看这些优秀的社区示例，了解两个模型的实际能力 🧵

Jeff Dean@JeffDean · 5月30日76

I enjoyed this chat immensely with @OfficialLoganK and my fellow Gemini leads @OriolVinyalsML and @NoamShazeer and @koraykv.

译我非常享受与@OfficialLoganK以及我的Gemini联合负责人@OriolVinyalsML、@NoamShazeer和@koraykv的这次对话。

Google AI Developers@googleaidevs · 5月30日42

Good implementation of Managed Agents in the Gemini API by our friends at @Eigent_AI! Root causing CI failures at lightning speed. ⚡

译Eigent平台展示了集成Gemini Managed Agents API的实际效果。其开源协作工具Eigent使用Gemini 3.5 Flash和该API，快速定位了一个真实的megatron-lm CI故障，在几分钟内找到了根本原因。工作流程中，协调员智能体规划审计，开发员智能体加载`ml-failure-audit`技能并收集证据，随后Gemini智能体作为远程子智能体接手进行深度推理。这体现了Managed Agents在自动化复杂任务中的效率。

Google Gemini@GeminiApp · 5月30日69

From the screen to reality in a single prompt. Check out these incredible examples of how Gemini Omni can understand your video input, apply physics, and generate seamless new motion. Try it out for yourself and share how you're experimenting with Gemini Omni in the replies 👇

译从屏幕到现实，只需一个提示词。 看看这些令人惊叹的例子，了解 Gemini Omni 如何理解你的视频输入，应用物理规律，并生成无缝的新动作。 亲自试试看，并在回复中分享你如何实验 Gemini Omni 👇

Google AI Developers@googleaidevs · 5月30日63

The team at @llama_index built an awesome template using LlamaParse and the new Managed Agents in the Gemini API. See how they built an agent that can tackle unstructured documents. 📄↓

译LlamaIndex 团队基于 Google 新发布的 Agents API 构建了一个模板，使智能体能够访问 LlamaParse 和 LiteParse，从而自动处理非结构化文档。其工作流程为：配置数据与输出的 Git 仓库，将仓库克隆至智能体沙箱，安装 LiteParse CLI 与 LlamaParse SDK 及相关技能，最后通过提示词驱动智能体自主执行任务。该模板最终形成一个可直接使用 LlamaParse 和 LiteParse 处理真实世界文档的智能体。

Josh Woodward@joshwoodward · 5月30日47

Editing video with our Omni model 🤯 Here are 10 creative examples that caught my eye in the last 24 hours… Try it in @GeminiApp and @FlowbyGoogle

译用我们的 Omni 模型编辑视频 🤯 以下是过去 24 小时里吸引我注意的 10 个创意示例…… 在 @GeminiApp 和 @FlowbyGoogle 中试试看

Google Gemini@GeminiApp · 5月30日74

Gemini Omni can transform even a basic sketch into a new reality. Try for yourself in the Gemini app. Upload a video of someone drawing a circle and then enter this prompt: When I finish drawing the circle, it becomes ___.

译Gemini Omni甚至能将简单的草图变为新的现实。 在Gemini应用中亲自尝试。上传一段有人画圆的视频，然后输入这个提示词：当我画完这个圆时，它变成了___。

Google AI Developers@googleaidevs · 5月30日43

We love this use of Managed Agents in the Gemini API by the team at @wandb. Silent bugs don't stand a chance. 🐛⬇️

译我们很欣赏@wandb团队在Gemini API中使用托管智能体的方式。隐蔽的bug无处遁形。🐛⬇️

Yuchen Jin@Yuchenj_UW · 5月30日35

Google is fighting every final boss at once: OpenAI & Anthropic in models, Nvidia in chips, AWS & Microsoft in cloud, Meta in ads, Tesla in self-driving, Apple in phones and OS. At $4.6T, it feels weirdly undervalued.

译Google正在同时对抗所有最终Boss： 在模型领域对抗OpenAI和Anthropic， 在芯片领域对抗Nvidia， 在云服务领域对抗AWS和Microsoft， 在广告领域对抗Meta， 在自动驾驶领域对抗Tesla， 在手机和操作系统领域对抗Apple。 市值4.6万亿美元，却感觉被奇怪地低估了。

Google Gemini@GeminiApp · 5月30日63

Gemini Spark is now available to all Google AI Ultra subscribers in the U.S. It can handle the heavy lifting and connect the dots across your digital ecosystem to take action where it matters most. Whether you watch it work or let it run in the background, Gemini Spark is always under your direction. Give it a try at http://gemini.google or in the app and let us know what you think.

译谷歌宣布Gemini Spark现已向所有美国的Google AI Ultra订阅用户开放。这是一款24/7个人AI智能体，可自主在后台工作，即使设备关闭也能执行任务。它旨在连接用户的数字生态系统并采取行动，但重大操作前会与用户确认。用户可通过gemini.google网页端或应用体验。

Google Gemini@GeminiApp · 5月30日63

From a newly redesigned Gemini experience to 24/7 agentic assistance with Gemini Spark, here’s a look at this month’s Gemini Drops. 🧵

译从全新设计的 Gemini 界面，到 Gemini Spark 提供的全天候智能体辅助，以下是本月 Gemini 更新概览。🧵

Google AI@GoogleAI · 5月30日64

Hear the architects of Gemini reflect on their journey to continue pushing the frontier of AI, on this episode of Release Notes. @JeffDean, @koraykv, @OriolVinyalsML, and @NoamShazeer sit down on camera together to share a behind-the-scenes look at the people behind the model, and how they saw the vision come together.

译聆听Gemini的架构师们回顾他们持续推动AI前沿的旅程，本期Release Notes节目。 @JeffDean、@koraykv、@OriolVinyalsML和@NoamShazeer一同出镜，分享模型背后团队的幕后故事，以及他们如何见证愿景的实现。

Rohan Paul@rohanpaul_ai · 5月29日56

Google fixed some issues around Gemini’s usage/quota limits. - The biggest issue was that 1 or 2 Omni videos could drain limits for some users because of a bug; Ultra users now get 2X Omni generations - Pro prompts now have a per-prompt quota cap - Failed requests won’t count against quota - Flash-Lite is free and won’t use quota - Granular usage breakdowns/alerts are coming - Selected model will stay remembered unless you change it or hit a cap

译Google针对Gemini应用配额问题推出多项修复。主要修复了一个导致1-2个Omni视频即耗尽部分用户配额的bug，Ultra用户的Omni生成次数提升至2倍。Pro提示词现在设有每提示配额上限，失败的请求不再计入配额。Flash-Lite模型免费使用且不占用配额。此外，系统将记住用户选择的模型，除非用户主动更改或达到配额上限。更详细的用量分析和提醒功能即将推出。

Rohan Paul@rohanpaul_ai · 5月29日23

Google omni is underrated indeed.

译Google omni确实被低估了。