硬體

AI 晶片、GPU、資料中心、邊緣裝置與硬體安全。

AI 研究與訓練

VIGOR Dynamically Allocates RLVR Rollouts Based on Reward Variance, Cutting Sampling for Mathematical Reasoning Training by Up to 2.3×

A new study replaces the fixed number of reasoning trajectories generated for every problem with a strategy that concentrates additional compute on samples exhibiting greater reward disagreement. The authors report higher rollout efficiency on mathematics and coding tasks, but have not released their code, while actual GPU time and scalability to larger models remain to be verified.

最新模型

AMD Opens the Full Instella-MoE Training Pipeline, With the 16B Model Activating Only 2.8B Parameters per Token

AMD has released six Instella-MoE checkpoints spanning pretraining, mid-training, long-context extension, SFT, DPO, and reinforcement learning, along with the training frameworks, data recipes, and inference code. The model uses Gated MLA and FarSkip-Collective to reduce attention and cross-GPU communication costs, but a formal technical report and independent evaluations are still pending.

AI 安全

SiYuan MCP Endpoint Lacked Role Checks; Version 3.7.2 Fixes Flaw Allowing Low-Privilege Users to Invoke Core Tools

The newly disclosed CVE-2026-66012 shows that, before SiYuan 3.7.2, the `POST /mcp` endpoint checked only general authentication status, without enforcing an administrator role or read-only restrictions. Because MCP can expose core note-management capabilities to AI clients, accounts intended only to read content could potentially use it to perform state-changing operations.

最新模型

UK–US Joint Evaluation: Kimi K3 Completes a Simulated Enterprise Intrusion, but None of 41 Exploit Attempts Achieves Arbitrary Code Execution

Preliminary testing by the UK AISI and the US CAISI shows that Kimi K3 scored 32% on ExploitBench, outperforming GLM-5.2 but trailing the tested US frontier models by a wide margin. The model also completed a 32-step simulated enterprise attack once, but the limited evaluation conditions and sample size do not support direct conclusions about real-world attack success rates.

硬體

VibeVoice-ASR-BitNet Shrinks Speech Recognition to 1.58 GB With Heterogeneous Quantization, Enabling Real-Time Transcription on Three CPU Threads

Microsoft Research has released VibeVoice-ASR-BitNet, applying INT8 and ternary-weight quantization to the speech encoder and language model, respectively, so multilingual ASR can run without a GPU. Official tests show the model is 1.6× to 2.3× faster than Whisper.cpp at a similar size, though it currently supports only offline batch transcription.

機器人與模擬

NVIDIA Open-Sources Medical Robotics Physics Simulation Framework, Training Catheter Policies Across 8,192 Parallel Environments

NVIDIA has integrated Medical Physics Simulation into Isaac for Healthcare to simulate blood vessels, flexible instruments, contact friction, and X-ray sensing, then train robotic policies in GPU-parallel environments. An official demo reduced one training workload from more than five hours to under two minutes, but simulation speed does not equate to clinical efficacy or safety certification.

AI 基礎設施

NVIDIA ModelExpress Transfers Weights GPU-to-GPU, Cutting Scale-Out Time for an 806 GiB Model to Under Two Minutes

NVIDIA has detailed ModelExpress’s complete transfer path, allowing new inference replicas to copy weights and compilation caches from existing GPUs, with P2P RDMA as the preferred method. In an eight-B200 test, the company cut DeepSeek-V4-Pro’s time to API readiness from eight minutes to 1 minute 44 seconds, though the result depends heavily on identical GPU models, high-speed networking, and compatible tensor configurations.