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뉴스 기사 93
“AI Code Guide”
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.
Serverless MCP server for AI agent data lake access on Amazon ECS Fargate
Learn how to build a serverless Model Context Protocol (MCP) server on Amazon ECS with AWS Fargate that gives AI agents secure, metadata-driven access to an enterprise data lake. Exposing a new dataset requires only a JSON file, with no per-dataset integration code.
Show HN: Combining Bursts of Images
An approach of taking many photos to enhance one final image is a technique called "stacking". Stacking alone doesn't account for everything so this is a take that helps get better alignment of images, allows comparisons, and drop bad images that dont match. Its not super resolution but it feels like when you look at it. it reduces the noise and makes it look more organic shot with less expensive hardware. enjoy! Comments URL: https://news.ycombinator.com/item?id=50401218 Points: 1 # Comments: 0
Show HN: Realtime sync engine without any new infra
Tandem is an open-source sync engine and client-side database that plugs into your existing infrastructure. Add the Tandem library to sync data in real time across your clients and server, without deploying any new services.I started work on Tandem 6 years ago as a side project. I was frustrated by the sync engine landscape at the time, thinking I could build a better DX and require less lock-in. Even now, sync engine companies and “full-stack databases” need you to migrate to their database or provision a separate service with auth, networking, etc. This makes them annoying to maintain and also harder to adopt incrementally.Tandem is designed to just be embedded into your existing frontend and backend code. You define a schema, set up a database adapter (any SQL-like database is supported), add the new sync endpoint to your existing API, and then you're good to go.Tandem uses DST (Deterministic Simulation Testing) on every PR and nightly to ensure correctness. Our DST system Gatekeeper lets us model not only storage and network failures, but also race conditions, by gating each call between client/server/other services independently.Tandem currently supports any React-based frontend, any serverful backend (like Cloudflare Durable Objects), and any SQL-like database. New adapters are easy to build, and PRs and issues are appreciated!Open-source and MIT licensed: https://github.com/tanishqkancharla/tandem Comments URL: https://news.ycombinator.com/item?id=50398763 Points: 1 # Comments: 0
Show HN: S3mail – Serverless personal email on AWS with JMAP
Article URL: https://github.com/zero11-0203/s3mail Comments URL: https://news.ycombinator.com/item?id=50401533 Points: 1 # Comments: 0
Show HN: Select – AI agents that earn autonomy through verified work
Article URL: https://github.com/Kirby54/Select Comments URL: https://news.ycombinator.com/item?id=50400882 Points: 1 # Comments: 0
Taxonomy of agentic primitives in Amazon Quick
As we built Amazon Quick, its agents grew from answering questions to taking actions, and the same primitives kept getting rebuilt under different names. This post shares the taxonomy we converged on — triggers, agents, capabilities, and learned context — found by decomposing agentic work into four plain questions: When, What, Who, and How.
b12135
The latest release of llama.cpp (b12135) introduces support for MEAN operations in WebGPU, enhancing performance and functionality across multiple platforms including macOS, Linux, Windows, Android, and iOS. The release includes precompiled binaries for various architectures and backends such as CUDA, Vulkan, ROCm, OpenVINO, SYCL, and zDNN, with specific builds for Apple Silicon, Snapdragon devices, and openEuler systems. Some features remain disabled or are under development.