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was less popular than ICE. Yet the number of people using AI is still skyrocketing. ChatGPT hit a billion monthly users in May, according to the market analysis firm Sensor Tower. Google DeepMind’s Gemini is close behind, logging 950 million users in July. According to Pew, half of US adults now say they use a chatbot , more than twice the number who said they did in 2023. One in four people say they do so every day. And it’s a global habit: More than a third of adults across all 38 OECD countri

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tly begun speaking more openly about preparing for the age of artificial general intelligence (AGI). In his first Substack post in July, Demis Hassabis, co-founder and then-CEO of Google DeepMind, argued that “urgent action is needed to address risks that might arise as we get closer to AGI.” A similar consensus is emerging in China. Liang Wenfeng, CEO of DeepSeek, and Tang Jie, co-founder of Z.ai, have both recently discussed AGI publicly, emphasizing long-term development, safety evaluation, a

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Anthropic, OpenAI and Google DeepMind shipped 4 frontier-class models within 30 days. Claude Fable 5.1 arrived on September 1. GPT-6 Astra followed on September 3. GPT-6.1 Sol and Gemini 4 Argon landed in the last days of September. We covered each launch on its own. This piece puts them side by side. The benchmark scores overlap more than the launch posts suggest. The prices, access rules and cost per task do not. One change frames the lineup. OpenAI cancelled GPT-6.1 Astra on September 28 afte

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ce , trained on Landsat and Sentinel-2 imagery of the entire contiguous US and adapted for flood and wildfire mapping. IBM had announced Prithvi as part of its Watsonx platform . IBM developed TerraMind, the lunar model's base, in 2025 with ESA and Forschungszentrum Jülich for Earth observation. Google Deepmind is pursuing a related approach with AlphaEarth Foundations , compressing optical satellite imagery, radar, lidar scans, and climate simulations into compact embeddings of Earth's surface.

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ects it was trained on large amounts of 3D data like Blender scenes . 3D software makers are already gearing up for these kinds of agents. Unity has released official plugins for Claude Code and Codex . Other approaches skip code entirely and reconstruct scenes directly inside the model, like the Atlas world model from World Labs . Google Deepmind takes yet another route with GenCeption, using a video model for depth estimation and segmentation that matches the performance of specialized models.

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verned data; Brex improved AI answer accuracy to 90% Give your agent a single source of truth. GOOGLE 🧬 Google’s AI watermarks cross into the lab Image source: Google The Rundown: Google DeepMind just introduced SynthID Bio, a proof of concept that extends its AI watermarking tech to proteins, potentially helping DNA suppliers trace unfamiliar designs before filling an order. The details: SynthID Bio tweaks Google’s protein-folding AlphaFold 3 model to leave a hidden pattern in its predicted pro

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rings us closer to understanding how complex brains function. Learn about the new DeepMind Institute. The DeepMind Institute is a platform for researchers and thinkers from across Google DeepMind, Google, and the wider global research community to work on and publish creative, deeply informed ideas about a world with AGI. With AGI on the horizon, it’s incumbent on the creators of AI technology to sincerely and thoughtfully address its risks — but its transformative impact cannot be steered by te

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大量低质量、AI生成论文持续挤占审核资源。 当地时间10月1日，arXiv正式宣布实施最新投稿限制：每位提交者每自然月最多只能提交2篇论文，适用于计算机科学、数学、物理等全部学科分类。即便论文最终被拒绝，也会占用当月的投稿额度。 作为拥有超过300万篇论文、每月服务数百万用户的科研基础设施，arXiv早已成为AI研究者抢先公开成果的重要渠道。从OpenAI、Google DeepMind，到DeepSeek、阿里千问等大模型团队，研究论文经常通过arXiv率先进入公众视野，接受同行检验与讨论。 如今，这条科研成果快速传播的通道，第一次向所有学科统一设置了明确的月度投稿上限。 1单月涌入4万篇，arXiv被迫限流 arXiv在10月1日发布的官方博客《Fair Moderation,Equitable Access,and AI》中，开篇便指出，科研出版正在经历一场快速变化，研究者交流成果的方式也在发生重大转变。 过去，一名研究者能够独立完成多少篇论文，存在相对清晰的现实上限。因此，arXiv的志愿审核员主要需要关注少数投稿频率明显反常的用户，必要时限制其提交速度。 随着生成式AI工具愈

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gate in the world around us. The reason policymakers need to pay attention now is that we're seeing rapid commercial development. Major tech companies on both sides of the Pacific—Google DeepMind, Nvidia, Tencent, and startups—are pouring resources into this space. These aren't just research prototypes anymore. They're heading toward real-world deployment in robotics, autonomous vehicles, infrastructure planning, and national security applications. "We need to get ahead of this technology before

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ance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense,” according to chief AI architect and Google DeepMind SVP Koray Kavukcuoglu. But the company is limiting access at first to a “set of trusted cyber defenders,” and Kavukcuoglu says that Google is “actively engaged in the U.S. government’s voluntary process for pre-release model access while we gradually expand access.” Kavukcuoglu says Gemini 4 Argon is al

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e real-time monitoring to respond faster to misaligned behavior.” OpenAI’s rivals have taken note. Spurred by the fallout from the incident, the major AI labs—including Anthropic, Google DeepMind, and SpaceXAI—have all called for the pace of development to slow down. But how does that square with fierce international competition and trillion-dollar IPOs? “We’re not going to shoot ourselves in the foot and take ourselves far off the frontier—that’s just a horrible strategy,” he says. “I think it’

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uture developers can use Diffusion Controller for much more than just matching text prompts. Immediate next steps include using the framework to build advanced personalization tools, developing robust safety mechanisms to help mitigate harmful content generation, and adapting the steering damper network to control complex, next-generation video models. We would like to thank our co-authors and collaborators from Google Research, Google DeepMind, and academia for their contributions to this work.

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cent fund raise of $315 million in February . Its first release, GWM Worlds, was launched last December. Alongside Runway, there are several other notable projects in this domain: Google DeepMind’s Genie 3 (which also generates at 720p and 24 fps), Odyssey-2 Pro , and World Labs’ RTFM (Real-Time Frame Model). We’ve summarized their differences in the following table: Given the complexity and massive latency demands of real-time video and audio generation (which we’ll get into below), all of the

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th distinct accents and characteristics. 🔵 Gemini 3.8 Flash-Lite TTS: Built for efficiency and scale, choose from your created styles or our expansive… pic.twitter.com/iiZwtRBxgc— Google DeepMind (@GoogleDeepMind) September 23, 2026 Gemini 3.8 Flash TTSは自然言語プロンプトを使用して、100以上の言語と方言でキャラクターやアクセント、声の特徴をカスタマイズし、新しい音声をゼロから作成できる。メキシコスペイン語、ケベックフランス語、スコットランド英語などの地域的なバリエーションを含む、幅広い言語に対応した2,000種類以上の音声ライブラリを持っており、30秒の音声サンプルがあれば、一貫性のある音声プロファイルを再現する。 また近日公開予定の機能として、プロンプトを使って音声ライブラリから選んだ声の音色、ピッチ、ペース、アクセントを微調整して

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清晰，从互联网到新能源，再从新能源到具身智能。 2015年前后，最聪明的产品经理和算法工程师涌向造车新势力；2025年之后，最顶尖的AI人才和算法人才，开始不约而同地奔向机器人公司。 如果把近半年的高管变动列成一张表，会发现一个规律，走得最密集的，恰恰是那些被寄予厚望的“一号位”。 罗剑岚的履历十分华丽——博士毕业于加州大学伯克利分校，曾在Google X、Google DeepMind担任研究科学家。2025年4月罗剑岚高调加盟智元机器人，牵头组建智元具身智能研究中心，构建了超100万条真机操作数据的AgiBot World数据集，次年9月进入合伙人团队。然后，在智元官宣赴港上市仅10天后，他从合伙人名单中消失了。 智元方面回应称：“系内部岗位调整，没有离职。”不过，当被问及调整后罗剑岚的职务以及负责工作内容时，智元方面未透露更多信息。 丁琰的轨迹则是另一种版本。从上海AI Lab到一星机器人，再到鹿明机器人，他在14个月内换了三份工作。在一星机器人只待了4个月，公司就因吉利战略收缩而解散。辗转33天后，2025年11月他带着十余名骨干集体加入鹿明。结果不到280天，又走了。 一个值

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ity, labor restructuring, and scientific discovery Anu Madgavkar and Daniel Rock will lead Google's AI & Economy Research Program alongside Alex Imas, Director of AGI Economics at Google DeepMind, and Zanna Iscenko, AI & Economy Lead, in Google's Chief Economist's Office. Shaping future research and collective impact Maximizing AI’s economic opportunity while mitigating disruption requires sustained partnership. This expanded team of experts will serve as a scientific bridge, directly informing

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short the one thing it requires: everyone. In today’s AI rundown: Zuckerberg breaks ranks on the AI slowdown Nate's Notebook: Same-hole thinking A beginner’s guide to ChatGPT Work Google DeepMind starts an AGI think tank LATEST DEVELOPMENTS Image source: Mark Zuckerberg (@finkd on X) / The Rundown The Rundown: Meta CEO Mark Zuckerberg just pushed back on the coordinated AI slowdown, arguing each lab already has its own “responsibility and incentive” for pacing itself safely, in a seemingly veile

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ons across all target languages, preserving strict error hierarchies and streaming behavior, and integrating the generator directly into our internal monorepo and build system. At Google DeepMind, while we use AI across our development workflows, we believe in choosing the right tool for each layer of the stack. Transforming formal API specifications into multi-language SDKs demands determinism and strict type safety. With Speakeasy, we pair a fast, deterministic generator at the core with Antig

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ey. OpenAI CEO Sam Altman said that embedding third-party evaluators is a solid step. SpaceX and Tesla founder Elon Musk echoed that oversight is long overdue. Demis Hassabis from Google DeepMind called the essay a step in the right direction. Microsoft CEO Satya Nadella emphasized that pursuing AI without keeping human benefit at the center isn’t worth doing. Tech investor Gavin Baker posted a great write-up below summarizing these industry responses Will Chinese labs follow the suit? Some soci

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s is central to Andon’s business proposition: providing AI developers with evaluations grounded in situations that arose outside the lab. The company says it works with Anthropic, Google DeepMind, OpenAI, and SpaceXAI on research and evaluations. Andon’s physical businesses themselves remain decidedly less successful. When Andon Market’s Carson spoke with IEEE Spectrum , he was about an hour into his shift. Two customers had come in. Neither bought anything, although both left with free pins and

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