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arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling GWM and reinforcement learning RL are often confounded because research papers rarely quantify how difficult the underlying transition prediction problem is at the declared interface pixels/tokens/latents with finite history.
arXiv:2608.18080v1 Announce Type: new Abstract: We present a review on the applications of large language models LLMs in health, e.g., social media analysis, clinical conversational agents, therapy support tools, prompt engineering, multimodal learning, and ethical considerations.
arXiv:2608.18081v1 Announce Type: new Abstract: Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time.
arXiv:2608.18086v1 Announce Type: new Abstract: The growth of openweight foundation models OWFMs has prompted the AI community to reevaluate strategies for effective downstream governance.
arXiv:2608.18088v1 Announce Type: new Abstract: Drone propeller faults can create safety and reliability risks when their effects are distributed across multiple flightlog channels rather than appearing as a single diagnostic signal.
arXiv:2608.18092v1 Announce Type: new Abstract: LLMbased multiagent systems MAS promise scalable collaboration, yet adding agents often reduces reliability.
arXiv:2608.18099v1 Announce Type: new Abstract: Investment management is a highstakes domain in which agentic AI systems must do more than generate plausible text.
arXiv:2608.18104v1 Announce Type: new Abstract: Large language model LLMbased agents are increasingly becoming selfevolving systems that persist across interactions, maintain memories, use tools, acquire skills, refine workflows, and coordinate with other agents.
arXiv:2608.18110v1 Announce Type: new Abstract: Agentic AI is gaining new insights and advancements in the field of Artificial Intelligence, fostering significant potential to enable rapid transformation across various domains.
With a fixed deadline and design resources committed elsewhere, Stampli used Codex and ChatGPT Work to compress weeks of launch production into days.
초대형 인공지능AI 반도체 설계 전문 기업 세레브라스 시스템즈Cerebras System가 지난 5월 14일, 미국 나스닥 상장 이후 18일현지시간, 차세대 랙 스케일 AI 가속기 ‘CS4’를 공개했다. 이 혁신적인 가속기는 새로운 웨이퍼 스케일 엔진과 랙 및 시스템 설계를 결합해 AI 추론 성능과 전력 효율, 대규모 모델 확장성을 동시에 강화했다고 밝혔다.회사 측에 따르면 CS4는 이전 세대인 CS3보다 최대 2배 빠른 성능을 제공하며, GPU 기반 솔루션과 비교하면 사용자당 초당 토큰 처리량TPS/user에서
인공지능AI·업무자동화 전문기업 파워젠대표 이정규이 지능형 문서인식 솔루션 ‘GEN OCR v6.0’을 19일 출시했다.GEN OCR v6.0은 기존 v5.0 대비 한글 학습 데이터를 1억 자에서 1억5천만 자로 확대해 인식 성능을 높였다. 인쇄체는 99% 이상, 필기체는 90% 이상의 인식 정확도를 지원하며, 대형 AI 모델을 활용한 테스트에서는 일반 OCR로 판독하기 어려운 수준의 필기체도 읽을 수 있는 것으로 확인됐다.이번 버전의 가장 큰 변화는 비정형 문서 처리의 편의성을 높였다는 점이다. AI가 문서의 양식과 내용을