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Instagram users: Here’s how to stop Meta’s AI from using your photos
Users can opt out of having their public Instagram photos used by Meta's Muse Image tool to generate AI images.
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Lightpath to provide fiber infrastructure for two new hyperscale data center campuses
Lightpath will supply fiber connectivity to two newly planned hyperscale data center campuses located in Michigan and Wisconsin.
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Unitree and UBTECH: Two Divergent Commercial Experiments for China Humanoid Robots in 2026
Chinese robotics firms Unitree and UBTECH are pursuing contrasting commercialization strategies, focusing on affordable industrial humanoids and luxury consumer robots respectively.
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上半年全球销售额环比增长248%，追觅割草机器人多区域实现突破
Dreame Technology reported a 248 percent sequential increase in global sales for its robotic lawn mowers in the first half of 2026, driven by its AI-powered obstacle avoidance and navigation systems.
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Flint: A visualization language for the AI era
Microsoft Research has introduced Flint, an open-source visualization language designed to help AI agents generate expressive charts from compact specifications.
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Enhancing enterprise inference on Amazon SageMaker HyperPod with data capture, Hugging Face, NVMe, and Route 53 integration
Amazon Web Services has introduced five new capabilities for SageMaker HyperPod to improve enterprise AI inference, including direct Hugging Face deployment and faster NVMe model loading.
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Elliott据悉已成为软件公司CCC的大额投资方
Elliott Investment Management has reportedly acquired a significant stake in CCC Intelligent Solutions, an insurance software provider currently exploring a potential sale.
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How KTern.AI built agentic AI for SAP on Amazon Bedrock AgentCore
KTern.AI has transitioned its SaaS platform into an agentic AI system for SAP software by leveraging Amazon Bedrock AgentCore and the Strands Agents SDK.
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Compete Then Collaborate: Frontier AI Teachers Build a Verifiable Curriculum to Improve a Coding Student Beyond Imitation
A new compete-then-collaborate framework ranks frontier AI models to build a verifiable curriculum for training smaller student models in coding tasks.
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From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier
This paper explores the transition of large language model-driven theorem provers from solving well-defined problems to assisting with frontier mathematical research and open conjectures.
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韩国首尔综指下跌5%
South Korea's Kospi index fell five percent, with major AI memory chipmakers SK Hynix and Samsung Electronics experiencing sharp declines of nearly ten and over six percent, respectively.
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China’s top DRAM maker sets date for US$4.3b Shanghai IPO amid memory boom
Chinese memory manufacturer ChangXin Memory Technologies is launching a Shanghai initial public offering aiming to raise at least 4.3 billion dollars amid rising demand for memory chips.
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AI Models Overthink Problems—and It’s a Security Risk
Researchers have found that the step-by-step reasoning processes in advanced language models introduce vulnerabilities that attackers can exploit to slow down systems.
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China weighs open-weight AI’s security risks against national tech innovation strategy: researchers
Chinese regulators are balancing the security risks of open-weight artificial intelligence models against the strategic need for open-source innovation to maintain competitiveness with the United States.
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In China, parents turn to AI to help children select a university degree
Chinese parents are increasingly utilizing artificial intelligence tools to help their children navigate the complex university admissions process and select degree programs.
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Efficient Safety Alignment of Language Models via Latent Personality Traits
Researchers introduced Latent Personality Alignment, a method that aligns language model safety using a small set of harm-agnostic statements instead of large datasets of harmful prompts.
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ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning
Researchers have introduced ReCoLoRA, a framework that uses spectrum-aware recursive consolidation to enable continual fine-tuning of large language models without losing performance on prior tasks.
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Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning
This study investigates the cognitive gap in large language models where newly memorized facts during fine-tuning fail to generalize to downstream reasoning tasks.
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ResonatorLM: Causal Resonant Field Mixing for Efficient Long-Context Language Modeling
ResonatorLM is proposed as an alternative language modeling architecture that uses causal resonant field mixing to improve long-context processing efficiency.
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When LLMs Agree, Are They Right? Auditing Self-Consistency and Cross-Model Agreement as Confidence Signals
A new study demonstrates that consistency and agreement among language models are unreliable indicators of accuracy when evaluating AI outputs.
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video-SALMONN-R$^3$: Learning to ReWatch, ReAsk, and ReAnswer for Efficient Video Understanding
Researchers developed video-SALMONN-R3, a framework that improves video large language models by first localizing relevant segments and then re-analyzing them at higher resolutions.
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Peer-Predictive Self-Training for Language Model Reasoning
Peer-Predictive Self-Training is a collaborative, label-free fine-tuning framework where multiple language models use aggregated responses to mutually improve their reasoning capabilities.
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OpenCoF: Learning to Reason Through Video Generation
The OpenCoF framework introduces a method for models to perform logical reasoning through temporally connected video frames, termed Chain-of-Frame reasoning.
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EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Data
Researchers investigate whether training policies to predict both actions and environmental changes using World Action Models improves robot manipulation learning from egocentric human videos.