谷歌Gemini 4 Carbon专攻网络安全
Google DeepMind发布Gemini 4 Carbon，定位网络安全和长程任务的前沿模型。同时Project Suncatcher卫星原型完成首次通信测试，Alphabet季度收入突破5000亿美元年运行率。
Gemini 4 Carbon选择网络安全作为突破口很精明——这是企业付费意愿最强但现有大模型表现最差的垂直领域之一，OpenAI和Anthropic在这块的落地案例都偏通用合规扫描，缺乏真正的渗透测试级能力。
Suncatcher卫星+AI模型的组合暗示谷歌正在构建太空边缘计算节点，这对国防和偏远地区通信是降维打击，Starlink的地面终端模式可能显得笨重。
OpenAI同期发"你想构建哪个未来"的抽象视频，对比谷歌连发三条硬产品动态，营销节奏上明显被压制，Sam Altman的模糊叙事策略正在失效。
RT @sundarpichai: A ‘hello world’ milestone for Project Suncatcher 🚀 After launching our prototype satellite a few weeks ago, we’ve now su…
查看原文 →RT @GoogleDeepMind: Gemini 4 Carbon is our next frontier model. It’s state-of-the-art across cybersecurity and long-horizon capabilities.…
查看原文 →RT @sundarpichai: Q3 is in the books! We’re now on a half-trillion annual revenue run rate, with Alphabet revenues growing at 25%. - Our A…
查看原文 →There are many futures. Which do you want to build? https://t.co/19NY7tgPHM
查看原文 →RT @alexolegimas: I joined @GoogleDeepMind to develop a research program on the economics of AGI. Today, together with Andrew Koh (@andrewj…
查看原文 →Privacy should advance as fast as intelligence. OpenAI Private Intelligence gives businesses stronger controls over their data while using our most capable models. We’re building these protections in close collaboration with some of our largest customers to help businesses apply frontier AI to their most sensitive work. https://t.co/BiA4N8FQVH
查看原文 →RT @arena: Exciting news: Gemini 4 Carbon (High) from @GoogleDeepMind just made a huge debut on Arena, landing #1 in Text Arena, #2 in Age…
查看原文 →RT @AlexiGlad: Energy-Based Models can now scale better than Diffusion models. Introducing TEM: Transformer Energy-based Models TLDR: • T…
查看原文 →RT @randall_balestr: The Platonic Representation Hypothesis is now a Theorem ◼️ Train JEPAs separately, on any modalities: they provably le…
查看原文 →RT @mercor: Gemini 4 Carbon debuts at #1 on APEX-Agents, and it's the only model on the leaderboard with a mean above 90%. 🥇Gemini 4 Carbo…
查看原文 →RT @RominaYalov: Can a JEPA world model provably avoid contraction and merging of latent states over long rollouts? Unconstrained autoregr…
查看原文 →Deterministic tests > Written instructions Anything that should be checked automatically should have a test case: • Checking behavior → Unit and integration tests • Checking formatting → Formatters and linters • Checking types → Static type checkers • Checking API contracts → Schema validation • Checking edge cases → Targeted tests • Checking regressions → Regression tests • Checking security → Static analysis and security scans Don't waste tokens telling an agent to follow rules you could enforce with deterministic tests.
查看原文 →This is a great model for exploring ideas quickly and cheaply. It's an image-to-video generation model. 5x faster and 80% lower inference cost than its base open-weight model. • Input: a starting image and a prompt describing what you want • Output: a 720p video • Advantages: Fast generation, low cost. Easy to iterate. • Disadvantages: Output doesn't have production quality.
查看原文 →This is a first for me: A 3D office where your coworkers are agents. Here's how it works: 1. You can create an agent and give it a job 2. You can connect the tools it needs 3. You can give it a task 4. You can review its work and give it feedback Every agent gets a cloud computer with access to a browser, files, and a terminal. The 3D aspect of this lets you "see" the agents and what they are working on.
查看原文 →People are celebrating how much time they're saving by letting agents review their code. But be honest: how much time are you spending fixing bugs afterward? Saving two hours on code review means nothing if you then spend four hours fixing problems. If you really want to know whether your automated code reviews are saving you time, you gotta measure the whole thing: 1. Track how much time you spend reviewing code, including the agent's feedback. 2. Track how much time you spend fixing bugs that make it past review. 3. Track how much time you spend investigating incidents and dealing with affected customers. Compare the total time with what it took before introducing agentic reviews. Ideally, measure it per PR or per change so you're comparing similar workloads. At the end of the day, nobody cares how much time you are saving on a particular task. The ultimate goal is to save more time overall without deploying crap to production.
查看原文 →I've never seen so many AI replies on this site. I think this is the worst it's ever been.
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