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A Lie Detector Test for Language Models: Reading Knowledge a Model Won't Reveal
Large language models can hold knowledge they do not report. A model may sandbag on a capability evaluation, or answer against what it internally knows, and its outputs alone cannot tell whether it is hiding an answer or simply does not have one. We borrow the Concealed Information Test, a forensic method that identifies guilty knowledge by presenting a suspect with the true detail among plausible decoys and measuring a stronger response to the item they recognize. Our method, Probe of Internal Recognition (PIR), does the same inside a model. It presents a question with its candidate answers a
匹配采集文档中文标题、摘要、原始来源或文档类型。From Enablement to Execution, Egypt’s AI Ecosystem Reaches Production Scale
Today, Egypt’s AI builders gathered in the Grand Egyptian Museum for a reception that highlighted the nation’s rapidly growing AI ecosystem — spanning AI natives, developers, researchers, startups and enterprises — building applications across industries. The event included a keynote from Paolo Guglielmini, vice president of EMEA at NVIDIA. Ahmed Mostafa, regional AI adoption lead […]
匹配采集文档中文标题、摘要、原始来源或文档类型。Artificial intelligence-driven segmentation, targeting and positioning and SMMEs financial performance
Cogent Business & Management | article | This study investigates the effect of AI-driven segmentation, targeting and positioning on the financial performance of SMMEs and the mediating role of AI-driven consumer insight. Utilising a quantitative, cross-sectional research design, data were collected from 295 SMMEs and analysed using the PROCESS macro. The study proposes that AI-driven marketing strategies enhance financial performance through enhanced customer intelligence. The overall model explains a substantial 62.97% of the variance in financial performance. Specifically, AI-driven segmenta
匹配采集文档中文标题、摘要、原始来源或文档类型。COMPLEX: A Closed-Form Certified Embedding of Multiparameter Persistence Modules
Every multiparameter persistence vectorization we know of carries a one-sided Lipschitz upper bound and nothing below it: without a lower gauge there is no sense in which the features are faithful, and no per-prediction guarantee can be built on them. This paper supplies the missing side. COMPLEX is a closed-form, training-free embedding of multiparameter modules -- slice the module along a fixed near-diagonal net, embed each slice barcode by the certified PLACE/PALACE landmark map, concatenate. Under a checkable witnessing-slice coherence condition, holding on 100% of audited pairs on Orbit5k
匹配采集文档中文标题、摘要、原始来源或文档类型。Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers
AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA announced the launch of the AI Energy Management Alliance (AEMA), a first-of-its-kind coalition advancing data centers that can dynamically manage their electricity use […]
匹配采集文档中文标题、摘要、原始来源或文档类型。From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production
On a sweltering August evening in Silicon Valley, as the sun dropped and air conditioning loads spiked, Silicon Valley Power sent a signal to an AI factory to adjust its power consumption. Varun Sivaram was watching on Zoom with about forty others — his team at Emerald AI in their San Francisco conference room, engineers […]
匹配采集文档中文标题、摘要、原始来源或文档类型。AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories
Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA, Tuesday spoke on AI factory efficiency at the AI Infra Summit, the Santa Clara Convention Center event that has morphed into a Coachella of infrastructure tech. Before a packed audience — with more than 8,000 attendees this year, up from 3,500 last year — […]
匹配采集文档中文标题、摘要、原始来源或文档类型。Deploy Hugging Face models on Amazon SageMaker AI with coding agents
Deploy production-ready Hugging Face models on Amazon SageMaker AI using six open-source agent skills. Point a coding agent at a model and get back a real-time endpoint with the right serving container, autoscaling, Amazon CloudWatch alarms, and a verified teardown path.
匹配采集文档中文标题、摘要、原始来源或文档类型。Skild AI Taps NVIDIA Physical AI to Teach Robots New Tasks From a Single Video
Manufacturing floors, warehouses and production lines rarely stay fixed — tasks change, layouts shift and new products arrive, and most robots can’t keep up without significant reprogramming. Skild AI’s new S1 robot foundation model helps address this, designed to learn previously unseen, long-horizon tasks from a single video demonstration. The model, launched last week, uses […]
匹配采集文档中文标题、摘要、原始来源或文档类型。University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK
Air pollution is a serious public health risk, contributing to an estimated 30,000 deaths in the U.K. alone last year. Data-driven insights can help — but computing air quality with traditional chemistry-based models is expensive, which limits how detailed they can be and how regularly they can be run. David Topping, a professor in the […]
匹配采集文档中文标题、摘要、原始来源或文档类型。Enhancing industrial safety AI with synthetic data on Amazon SageMaker AI
Learn how to build a synthetic data augmentation pipeline on Amazon SageMaker AI and Amazon Rekognition that generates photo-realistic, auto-labeled training images for industrial safety AI. This approach improved person detection by up to 160% without manual annotation or hazardous data collection near heavy machinery.
匹配采集文档中文标题、摘要、原始来源或文档类型。Kubernetes v1.37: Scheduler Preemption for In-Place Pod Resize (Alpha)
In Kubernetes, resource allocation has historically been a static decision made during a Pod's initial scheduling and placement. With the graduation of the core in-Place Pod resize feature to General Availability in v1.35, application developers and cluster operators gained the powerful ability to dynamically adjust CPU and memory allocations of running containers without incurring disruptive restarts or application downtime. However, in-place resizing introduced a unique resource scheduling gap: if a running Pod requested a resource scale-up that exceeded the host node's allocatable headroom,
匹配采集文档中文标题、摘要、原始来源或文档类型。Available Guardrails: Certifying Selective Prediction across ML Systems
A selective predictor acts as a safety gate: it returns an output only when the prediction appears sufficiently trustworthy. Deployments increasingly require this reliability to be certified at a target precision for every reporting unit of interest, such as a tool, policy label, or patient subgroup. The main difficulty is often not whether a granted certificate is valid, but whether finite calibration data can produce one at all. As the gate becomes safer or more fine-grained, some units may receive too little evidence to certify. We make this notion of availability computable through classic
匹配采集文档中文标题、摘要、原始来源或文档类型。Two zones or three? A design framework for zone-resilient Azure workloads
Zone resiliency isn't a single number you apply to a whole workload. The useful question isn't “how many zones?” but “how many zones does each component need to survive the loss of one?” Decide zone patterns component by component, use service-managed zone redundancy wherever it fits, and reserve three-zone designs for the components that genuinely require a third failure domain. The post Two zones or three? A design framework for zone-resilient Azure workloads appeared first on Microsoft Azure Blog .
匹配采集文档中文标题、摘要、原始来源或文档类型。NVIDIA and Palantir Bring Sovereign Intelligence to Critical Supply Chains
News Summary: Collaboration establishes an AI stack combining Palantir sovereign AI and custom NVIDIA Nemotron open models for complex supply chain operations. The AI stack is first being deployed within NVIDIA’s supply chain to codify operational intelligence and accelerate the path from wafer to first token. Organizations can optimize their own supply chains through the Palantir Sovereign AI Operating System Reference Architecture running on cloud or on-premises infrastructure. Palantir Technologies Inc. (NASDAQ: PLTR) and NVIDIA (NASDAQ: NVDA) today announced a collaboration to bring sovere
匹配采集文档中文标题、摘要、原始来源或文档类型。Run Positron on Amazon SageMaker AI for data science workflows
Positron, Posit's IDE for data science, now runs on Amazon SageMaker AI. This post shows how a data scientist explores an Amazon Athena table, validates features in R, trains an XGBoost model in Python, deploys a real-time SageMaker AI endpoint, and reports results with Quarto, all in one governed SageMaker Studio Space.
匹配采集文档中文标题、摘要、原始来源或文档类型。Physical AI Takes the Wheel: How the World’s Robotaxi Leaders Are Building With NVIDIA Technologies
The global robotaxi market — physical AI’s first commercial breakthrough — is projected to reach $400 billion by 2035, with over 6 million commercial vehicles in operation as driverless fleets are already moving people through some of the world’s busiest and most complex streets. Deploying a driverless vehicle is one challenge. Scaling a fleet is […]
匹配采集文档中文标题、摘要、原始来源或文档类型。How to Evaluate AI Agents From Tool Calls to Task Completion
When you ship an AI agent, the key question is whether it can execute a chain of work across dozens of sequential tool calls against a live environment, and...
匹配采集文档中文标题、摘要、原始来源或文档类型。Legal, ethical and moral dilemma of human cloning: the conflict between technological progress and human dignity
Frontiers in Medicine | article | Human cloning involves creating a genetically identical copy of a human cell, tissue, or embryo. That is, human reproductive cloning, producing a genetic copy of an existing person, has never been successfully done and remains globally banned or restricted. While there is no scientific evidence of successful human reproductive cloning, biotechnology combines cloning methods with genetic engineering to drive advancements in medical research and disease treatment. With the development of genetic engineering and cloning technologies, human cloning, as a possible
匹配采集文档中文标题、摘要、原始来源或文档类型。The Economics of Agent Optimization: How AI agent governance controls cost and proves ROI
This blog post is the fourth and final installment of The Economics of Agent Optimization, which shares the strategies, capabilities, and proof points that can help you optimize agent costs and run AI as a managed investment system on Microsoft Foundry. The post The Economics of Agent Optimization: How AI agent governance controls cost and proves ROI appeared first on Microsoft Azure Blog .
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