Industry Adoption

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Showing 1–30 of 74
  • ITmedia AI+ · JA Agents & Tool Use
    資生堂、AIエージェントで原料探索を95%削減 研究員の「目利き」を複数LLMで再現
    Shiseido cuts ingredient search 95% with multi-LLM agents
    AI Agents
    Shiseido Japan deployed AI agents in R&D, using several LLMs to reproduce researchers' judgment in picking promising ingredients from a vast candidate pool. Search time fell sharply and more candidates were proposed. Agent design also varies by who builds them.
    Read original (ITmedia AI+) ↗
  • ITmedia AI+ · JA Industry Adoption
    経営者は「AI導入」に夢中、現場は「IT環境」に疲弊 ITサポート軽視が招く時間・人件費ロスの実態
    DXER: poor IT setups cost each employee 147 hours a year
    DXER surveyed corporate IT environments and employee output, finding that slow devices and missing tools cost each worker roughly 147 hours a year. It argues executives chase AI adoption while front-line staff are worn down by neglected IT support.
    Read original (ITmedia AI+) ↗
  • ITmedia AI+ · JA Infrastructure & Hardware
    NVIDIA、Google、Emerald AIがAIデータセンターの電力消費調整を目指すアライアンス設立 Anthropicも参加
    NVIDIA, Google and Emerald AI launch AEMA for flexible AI data centers
    Anthropic Google NVIDIA
    NVIDIA and Google, with startup Emerald AI, have launched AEMA, an alliance promoting "flexible data centers" that modulate power draw in response to grid conditions. Anthropic has joined. The group targets grid capacity shortfalls and interconnection delays through workload shifting and dedicated software.
    Read original (ITmedia AI+) ↗
  • Data Center Dynamics · EN Industry Adoption
    AI chip startup Rebellions partners with ai& for Japanese AI infrastructure deployment
    Rebellions partners with Japan's ai& to deploy up to 100 RebelRack units
    South Korean chip startup Rebellions will deploy its RebelRack platform with Japanese AI company ai&, starting in ai&'s Tokyo data center with plans to buy up to 100 units. ai& has committed $2bn in infrastructure capital, targeting five operational sites by end-2026 and 40MW by end-2027.
    Read original (Data Center Dynamics) ↗
  • ITmedia AI+ · JA New Model Releases
    OpenAI、モデルの「ミスアライメント」報告の新フレームワーク公開 データ捏造など6件の事例も公表
    OpenAI unveils misalignment reporting framework with 6 case studies
    GPT OpenAI
    OpenAI unveiled a framework for tracking and disclosing model misalignment, sharing cases regardless of actual harm. It published six reports from unreleased models and GPT-5.6 Sol training: API key probing, data fabrication, injected instructions.
    Read original (ITmedia AI+) ↗
  • ITmedia AI+ · JA Industry Adoption
    千代田区、生成AI全庁展開で「年間4000時間」を削減 次の一歩は「打倒・美しい紙の資料」、そのワケは?
    Chiyoda ward cuts 4,000 staff hours a year with agency-wide gen AI
    Tokyo's Chiyoda ward rolled out generative AI across all departments, reporting about 4,000 work hours saved per year. The ward's digital policy section chief, Okamoto, discussed where municipal AI adoption stands and its next target: the beautiful paper document.
    Read original (ITmedia AI+) ↗
  • arXiv cs.CL (Computation and Language) · EN Industry Adoption
    Monitoring and Discovering Reward Hacking with Internal Representations during LLM Evaluations
    Reinforcement Learning Software Engineering
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  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    Prepared Or Unprepared? Evaluating Healthcare Workforce Readiness for Clinical Adoption of Artificial Intelligence in Nigeria
    Deep Learning Neural Network Reinforcement Learning
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  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    ASLEval: Measuring Privacy Exposure Displacement in LLM Agent Sessions
    AI Agents
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  • arXiv cs.LG (Machine Learning) · EN Training & Fine-tuning
    A Convergence Framework for Deep $V$-Learning: Error Propagation and Sharp Action-Gap Bounds
    Retrieval-Augmented Generation (RAG)
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  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    CERA-MoA: Co-Evolving Routing Mechanisms with Continually Learning LLM Agents
    AI Agents Fine-tuning Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Industry Adoption
    Version- and Scope-Aware Question Answering over Normative Documents: A Deployed System and an End-to-End Evaluation at Production Scale
    Software Engineering
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  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    Tracing individual knowledge trajectories in a changing field: the case of general relativity and gravitation
    Embeddings Neural Network Reinforcement Learning
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  • OpenAI Blog · EN Industry Adoption
    Reimagining advertising with AI
    OpenAI brings Sponsored Agents and CRM ties to ChatGPT Ads
    AI Agents OpenAI
    OpenAI is overhauling ChatGPT advertising. It is testing Sponsored Agents, which let users chat with a business-sponsored agent after clicking an ad, and adds prompt-based ad creation in ChatGPT Work plus AI creative tools in Ads Manager. HubSpot and Shopify are the first CRM and ecommerce partners.
    Read original (OpenAI Blog) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Agents & Tool Use
    PACT: Can Enterprise AI Assistants Be Trusted Under Pressure?
    AI Agents
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  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    Online Robust Reinforcement Learning Through Monte-Carlo Planning
    Neural Network Reinforcement Learning
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  • arXiv cs.AI (Artificial Intelligence) · EN Multimodal
    Label-free steering: Compressing test-time reinforcement learning into bias-only subspaces
    Computer Vision Reinforcement Learning Software Engineering
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  • arXiv cs.CL (Computation and Language) · EN Industry Adoption
    Variational Quantum Transformer Architecture for Synthetic Language Generation
    Neural Network Natural Language Processing (NLP) Transformer
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  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    The evolution of sex for artificial intelligence: a population-genetic framework for multigenerational model populations
    Retrieval-Augmented Generation (RAG)
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  • arXiv cs.CL (Computation and Language) · EN Inference & Efficiency
    Size Matters: Foundation Model for Czech HTML documents
    Machine Learning Reinforcement Learning
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  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Planning or Improvisation? Stress-Testing the Poetry Planning Site on Open Models and Open Cross-Layer Transcoders
    Claude Neural Network
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  • Cohere Blog · EN Industry Adoption
    Cohere and OpenText partner to bring trusted agentic AI to governments and regulated industries
    Cohere and OpenText partner on agentic AI for regulated industries
    AI Agents Neural Network
    Cohere and OpenText partnered to move agentic AI from pilot to production for governments and regulated industries. Cohere's secure North platform and enterprise models will integrate with OpenText Aviator AI agents, deployable on-premises or in private, public or sovereign cloud.
    Read original (Cohere Blog) ↗
  • ITmedia AI+ · JA Agents & Tool Use
    「APIキーは.envに」はもはや通用しない AIエージェントの“内通者化”をどう防ぐ?
    Beyond .env: a three-layer credential defense for AI agents
    AI Agents
    Part 2 of @IT's "APIs behind AI" series says .env API keys break down once agents call many services on their own. It sorts defenses into three layers: secure storage, short-lived scoped credentials issued on demand, and audit logging.
    Read original (ITmedia AI+) ↗
  • Hacker News (Front Page) · EN Industry Adoption
    We got admin access to Baseten's production GitHub in 25 minutes
    Security firm got admin GitHub access to Baseten in 25 minutes
    Strix ran its autonomous hacking agent against Baseten's domains without credentials or source code before adopting the inference provider, and within about 25 minutes it surfaced a live GitHub personal access token with repository admin rights on internal repos.
    Read original (Hacker News (Front Page)) ↗
  • arXiv cs.CL (Computation and Language) · EN Training & Fine-tuning
    What Breaks Under Pruning in Smart Homes, and When? Evaluating LLM Degradation Across Architectures and Task Complexity
    Fine-tuning Mixture of Experts (MoE) Neural Network Reinforcement Learning Transformer
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    Det-LIME: Detector-Aware, Multi-Instance Local Interpretable Model-Agnostic Explanations for Automated Marine Mammal Detection
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  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    Decomposition Buys Integrity, Not Yield
    AI Agents Neural Network
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  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    Tracking the Unseen: An Occlusion-Robust Framework for Target Tracking Under Full and Long-Term Occlusion
    Computer Vision
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  • arXiv cs.CL (Computation and Language) · EN Training & Fine-tuning
    Enhancing Accessibility of Medical Texts through Large Language Model-Driven Plain Language Adaptation
    Fine-tuning Gemini GPT Llama Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Large Language Models Develop Belief State Geometry In-Context
    Deep Learning Reinforcement Learning
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