A new study has found that multiple cloud-based password managers, including Bitwarden, Dashlane, and LastPass, are susceptible to password recovery attacks under certain conditions. “The attacks range in severity from integrity violations to the complete compromise of all vaults in an organization,” researchers Matteo Scarlata, Giovanni Torrisi, Matilda Backendal, and Kenneth G. Paterson said. Read More
How to Build Human-in-the-Loop Plan-and-Execute AI Agents with Explicit User Approval Using LangGraph and StreamlitMarkTechPost In this tutorial, we build a human-in-the-loop travel booking agent that treats the user as a teammate rather than a passive observer. We design the system so the agent first reasons openly by drafting a structured travel plan, then deliberately pauses before taking any action. We expose this proposed plan in a live interface where
The post How to Build Human-in-the-Loop Plan-and-Execute AI Agents with Explicit User Approval Using LangGraph and Streamlit appeared first on MarkTechPost.
In this tutorial, we build a human-in-the-loop travel booking agent that treats the user as a teammate rather than a passive observer. We design the system so the agent first reasons openly by drafting a structured travel plan, then deliberately pauses before taking any action. We expose this proposed plan in a live interface where
The post How to Build Human-in-the-Loop Plan-and-Execute AI Agents with Explicit User Approval Using LangGraph and Streamlit appeared first on MarkTechPost. Read More
The headlines scream about AI job displacement. But they could be missing the bigger story? Yes, AI will automate significant portions of work. The OECD finds that 27% of jobs across its member countries are in occupations at high risk of automation, defined as those where experts consider over 25% of skills to be easily […]
Lots of people assume AI Careers revolve around coding and machine learning. They’d only be partially right. The OECD analyzed online job vacancies and discovered something that contradicts popular wisdom. For occupations with high exposure to AI, the most in-demand skills aren’t specialized AI capabilities like machine learning (OECD Future of Work). Management, business processes, […]
AI Industry Battlegrounds Money talks. Lives matter. National security can’t fail (we hope). Those three principles explain why certain industries are driving the explosive demand for AI governance professionals while others lag behind. The pattern isn’t random. It directly follows risk levels, regulatory pressure, and the cost of getting AI wrong. Banking and Financial Services: […]
The Strangest Bottleneck in Modern LLMsTowards Data Science Why insanely fast GPUs still can’t make LLMs feel instant
The post The Strangest Bottleneck in Modern LLMs appeared first on Towards Data Science.
Why insanely fast GPUs still can’t make LLMs feel instant
The post The Strangest Bottleneck in Modern LLMs appeared first on Towards Data Science. Read More
URBN tests agentic AI to automate retail reportingAI News Retail decisions often depend on weekly performance reports, but compiling those reports can take hours of manual work. Urban Outfitters Inc. (URBN) is testing a new approach by using agentic AI systems to generate those reports automatically, changing routine analysis from staff to software. The retailer runs brands like Urban Outfitters, Anthropologie, and Free People,
The post URBN tests agentic AI to automate retail reporting appeared first on AI News.
Retail decisions often depend on weekly performance reports, but compiling those reports can take hours of manual work. Urban Outfitters Inc. (URBN) is testing a new approach by using agentic AI systems to generate those reports automatically, changing routine analysis from staff to software. The retailer runs brands like Urban Outfitters, Anthropologie, and Free People,
The post URBN tests agentic AI to automate retail reporting appeared first on AI News. Read More
CoPE-VideoLM: Codec Primitives For Efficient Video Language Modelscs.AI updates on arXiv.org arXiv:2602.13191v1 Announce Type: cross
Abstract: Video Language Models (VideoLMs) empower AI systems to understand temporal dynamics in videos. To fit to the maximum context window constraint, current methods use keyframe sampling which can miss both macro-level events and micro-level details due to the sparse temporal coverage. Furthermore, processing full images and their tokens for each frame incurs substantial computational overhead. To address these limitations, we propose to leverage video codec primitives (specifically motion vectors and residuals) which natively encode video redundancy and sparsity without requiring expensive full-image encoding for most frames. To this end, we introduce lightweight transformer-based encoders that aggregate codec primitives and align their representations with image encoder embeddings through a pre-training strategy that accelerates convergence during end-to-end fine-tuning. Our approach reduces the time-to-first-token by up to $86%$ and token usage by up to $93%$ compared to standard VideoLMs. Moreover, by varying the keyframe and codec primitive densities we are able to maintain or exceed performance on $14$ diverse video understanding benchmarks spanning general question answering, temporal reasoning, long-form understanding, and spatial scene understanding.
arXiv:2602.13191v1 Announce Type: cross
Abstract: Video Language Models (VideoLMs) empower AI systems to understand temporal dynamics in videos. To fit to the maximum context window constraint, current methods use keyframe sampling which can miss both macro-level events and micro-level details due to the sparse temporal coverage. Furthermore, processing full images and their tokens for each frame incurs substantial computational overhead. To address these limitations, we propose to leverage video codec primitives (specifically motion vectors and residuals) which natively encode video redundancy and sparsity without requiring expensive full-image encoding for most frames. To this end, we introduce lightweight transformer-based encoders that aggregate codec primitives and align their representations with image encoder embeddings through a pre-training strategy that accelerates convergence during end-to-end fine-tuning. Our approach reduces the time-to-first-token by up to $86%$ and token usage by up to $93%$ compared to standard VideoLMs. Moreover, by varying the keyframe and codec primitive densities we are able to maintain or exceed performance on $14$ diverse video understanding benchmarks spanning general question answering, temporal reasoning, long-form understanding, and spatial scene understanding. Read More
Self-Hosted AI: A Complete Roadmap for BeginnersKDnuggets Build your own private AI hub with Docker, Ollama, and n8n. A beginner’s guide to self-hosted, local automation with no cloud fees.
Build your own private AI hub with Docker, Ollama, and n8n. A beginner’s guide to self-hosted, local automation with no cloud fees. Read More
Top 5 Super Fast LLM API ProvidersKDnuggets Fast providers offering open source LLMs are breaking past previous speed limits, delivering low latency and strong performance that make them suitable for real time interaction, long running coding tasks, and production SaaS applications.
Fast providers offering open source LLMs are breaking past previous speed limits, delivering low latency and strong performance that make them suitable for real time interaction, long running coding tasks, and production SaaS applications. Read More
