Oct 12, 2026 Microsoft plans to deploy its Azure Maia AI chips at multi-gigawatt scale starting in 2027.** They'll becom…

IT之家 10 月 12 日消息，Scale AI 创始人、现任 Meta 首席 AI 官汪滔（Alexandr Wang）当地时间 10 月 11 日在做客 David Senra 播客节目时谈到了对首次创业者的建议：创办第一家公司时，创…

Physical AI is moving rapidly from research to large-scale deployment. By 2035, ABI Research projects an installed base …

We present a continuous, population-scale measurement record of autonomous language-model trading agents operating in pr…

Understanding agent behavior requires methods that scale to thousands of trajectories and surface new patterns in long, …

Scaling computer-use agents from individual actions to complex software work requires experience that connects decisions…

Predicting future physical states stands as a central challenge in embodied intelligence. Existing video world models le…

NVIDIA builds tools to enable safe agents across the stack. The NVIDIA OpenShell Reference Architecture, announced today…

Demand from AI-natives is pulling the European AI cloud ecosystem forward faster than ever. Developers need compute clos…

As AI factories grow from megawatts to gigawatts, building them takes more than advanced computing. Open standards are h…

Agentic reinforcement learning (RL) disaggregates training from rollout, so each policy update must reach the rollout cl…

Local AI is becoming more useful by the token. As AI agents move from experiments into everyday development, increasingl…

Real-world enterprise data science and analytics workflows require reasoning across dozens of tables, performing statist…

In this paper, we propose RGBD20K, a novel dataset for facilitating the development of more robust and general RGB-D sem…

When Sakeena Fiza describes her work as a validation engineer at NVIDIA, she does so in terms more befitting a detective…

Today, Egypt’s AI builders gathered in the Grand Egyptian Museum for a reception that highlighted the nation’s rapidly g…

Reference-to-video (R2V) generation is evolving toward increasingly general and versatile reference control, giving rise…

Reducing audio-encoder depth lowers the inference cost of speech large language models, but removing complete blocks per…

AI inference chipmaker d-Matrix today announced it will use NVLink Fusion to connect its next-generation Raptor XPUs to …

Speculative decoding accelerates rollout generation, which dominates the cost of reinforcement learning (RL) post-traini…

High-quality structured organic reaction data are essential for developing artificial intelligence for chemistry (AI4Che…

Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and…

数据标注是 AI 产业的「隐形地基」——它的形态随 AI 的需求升级了三代：众包打标签、专业质检线、再到 RLHF 的专家反馈工厂。数据工厂的竞争要素变了：比的不是便宜，是「谁身边坐着的博士多」。

Cities generate enormous amounts of data from cameras, sensors and operational systems, but turning it into useful actio…

At a glance Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of rea…

Building a startup means making decisions before you have all the answers. When should you scale? How do you know you re…

At GTC Berlin, banks, payment companies and financial data providers are showing what production-scale intelligence look…

As model parameters scale up, sparsely activated Mixture-of-Experts (MoE) approaches have become essential for model sca…

Large-scale action pretraining equips Embodied Foundation Models (EFMs) with strong manipulation capabilities, with part…

Across industries, the U.K. is putting the full stack to work. The scale of deployment is growing fast, from enterprises…

Computer-use agents (CUAs) are rapidly improving, yet synthesizing diverse and reliable software environments at scale r…

每个 LLM 基准都逃不过同一条生命周期曲线：出生时区分力强 → 大家刷分 → 分数挤在 90% 以上失去区分度 → 被质疑数据污染 → 退役换下一代。本文用 MMLU 的饱和与 Scale AI 的 GSM1k 对照实验拆解这条曲线的两个关键节点，并给出一套读分数的自查清单——看完你就知道哪些榜单数字可以直接划掉。

Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learn…

GPU-parallel simulation provides abundant robot interaction, but existing benchmarks rarely combine this scale with hete…

Mixture-of-Experts (MoE) transformers scale capacity by activating only a few experts per token, but this sparsity creat…

Learning general-purpose robot policies requires large-scale real-world interaction data, yet collecting robot demonstra…

A trainable input embedding table assigns each vocabulary item an independently adjustable vector. We investigate whethe…

Lookup-based memory has been a promising way to scale the parameters of large language models (LLMs). It retrieves learn…

Recent progress in frontier models has renewed interest in large-scale reinforcement learning (RL), but the cost of gene…

Large-scale Digital Surface Models (DSMs) can be produced cost-effectively from satellite images via stereo-photogrammet…

Tool-calling agents have become central to enterprise AI, yet training and evaluating them at scale remains severely con…

ShinyHunters, a prolific cybercriminal group known for large-scale data theft and extortion, says it has breached the FB…

Clean energy isn’t hard to come by, but the pace of large-scale adoption has historically been slow due to bottlenecks —…

Petlibro's new Granary 2 smart feeders use a built-in scale and (on pricier models) an AI camera to track exactly how mu…

Building an AI prototype is easy, but operating autonomous agents at scale requires production-grade tooling. Salesforce…

We need studies on conversational AI (CAI) at scale to understand human behavior and shape CAI design. However, fragment…

Recently, linear attention layers have been increasingly adopted to replace softmax attention at scale for long-context …

We introduce StepAudio 3 Music, a large-scale, long-form music generation model that supports explicit musical planning …

Training capable cyber agents is often treated primarily as a problem of model scale, yet open-weight post-training is c…

Compressing large-scale neural networks is essential for deploying models on resource-constrained devices. Most existing…