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ニュース記事 90
“AI Code Guide”
b12191
The latest update to llama.cpp introduces enhanced MoE (Mixture of Experts) cache functionality, enabling computation of cache misses on the CPU with a configurable CPU share. A new tuning script, moe-cache-tune.py, automatically determines optimal cache size and CPU share settings based on system performance. The update also improves scheduling efficiency, removes redundant sync operations, and refactors code for better maintainability, while maintaining compatibility across multiple platforms including macOS, Linux, Windows, and Android.
b12202
The llama.cpp v1.220.2 release introduces enhanced BF16 precision support across multiple components, aligning with reference implementations by moving specific operations like GLM4 family projections, MiMoVL vision matmuls, and Qwen3-TTS speaker encoder conv1d to BF16 where appropriate. Backends such as CUDA, Hexagon, OpenCL, WebGPU, and Vulkan now uniformly handle GGML_PREC_BF16 similarly to F32, while CPU, SpaceMIT, and ET backends extend flash attention support to BF16 with F32 accumulation. Flash attention tests now include BF16 cases, and the KQ multiplication in Llama is updated to request BF16 precision. A TODO remains in clip.cpp for future work.
Show HN: Coldframe, a honeypot that poses as a supermarket fridge controller
I built Coldframe, a honeypot that pretends to be a supermarket refrigeration controller. Inspired by the events on industrial fridge installations in the past weeks, I wanted to see what people would try against a convincing fake.To learn more about this I built a honeypot that resembled perfectly the Danfoss AK-SM 800A and Dixell XWEB interfaces. Both of them are recognized on Shodan as real ones (an not as honeypots). It’s one Python file using only the standard library, and it builds on eppser/danfoss-ak-sm-decoy and public research by Synacktiv, Claroty and Ironhackers.Things that were fun to get right:- Matching real units. I used Shodan records of real devices to match header order, page titles, certificate fields and TLS versions. The Danfoss persona sends nginx headers in the same order as a real AK-SM 800A. The Dixell persona sends no Server header and pads its page to exactly 8,202 bytes.- Recognising exploit attempts. It recognises CVE-2025-41450, the Danfoss “code of the day” login bypass, and records whether the submitted code is correct for today. It also tags attempts targeting three other Danfoss CVEs and the XWEB vulnerabilities.- Letting them in. Default logins open a fake store dashboard with defrost buttons, so you see the second move, not just the first. Nothing behind it is real.Two instances have been live for a day. So far they’ve only seen generic scanners and Shodan’s crawler, which is called refrigerator.census.shodan.io.Feedback welcome, especially from anyone who has seen these devices in the field! Comments URL: https://news.ycombinator.com/item?id=50406292 Points: 15 # Comments: 1
Show HN: We Build Shareable Context Layer for Agent Teams
Article URL: https://github.com/volcengine/OpenViking Comments URL: https://news.ycombinator.com/item?id=50410477 Points: 1 # Comments: 1
b12179
The update introduces support for 3D convolution (conv_3d) on Hexagon hardware by generalizing the existing conv_2d implementation. It leverages the HMX tiled path, folds kernel dimensions into a virtual row, and uses a shared solver with an is3d flag. The host computes unfold divisors to avoid device-side division, prevents DMA queue overflow, and improves tile size selection based on VTCM usage. Additional changes include handling arbitrary positive strides, preserving load/shuffle paths for small strides, and fixing compiler warnings.
b12186
A change has been made to add the 'readonly' attribute to decodeBuf declarations in the Vulkan backend, with potential performance improvements expected in future driver versions.
b12187
The latest release of llama.cpp (b12187) includes the implementation of a WebGPU group norm kernel, with associated CI workflows, performance tests, and cleanup of related code. The update supports various platforms including macOS, Linux, Windows, Android, and specific hardware backends like Vulkan, CUDA, ROCm, OpenVINO, SYCL, and Snapdragon devices. Some builds remain disabled or experimental.
b12189
The metal backend's kernel_group_norm_f32 was updated to correctly handle tensors with ne03 > 1 and non-contiguous inputs by dispatching one threadgroup per (group, i03) pair, computing per-batch statistics, clamping group element count for incomplete groups, and supporting strided access via separate strides for source and destination. The fix also restricts GROUP_NORM to f32 inputs and improves performance through specialized pipeline variants.
How NVIDIA Open Source Tools Are Helping Researchers Build Next-Generation 6G Networks
A year ago, NVIDIA open sourced its Aerial wireless software, joining Sionna and a broader suite of open source tools for accelerating next-generation 6G network development. Together, they give researchers a foundation for testing ideas, comparing results and building on each other’s work — connecting simulation and AI training with experiments on real over-the-air wireless […]
SageMaker Inference now supports Multi-Instance GPU to maximize GPU utilization for model endpoints
Amazon SageMaker Inference now supports GPU partitioning with NVIDIA Multi-Instance GPU (MIG), which divides one GPU into hardware-isolated partitions so you can run a different model in each or take a right-sized fraction of a newer accelerator. This post shows how two optional API fields place one model per partition, and what we measured against a whole older GPU.