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AI ShortWriting & content

AIS ALERT MANAGEMENT AND SHARED PLATFORM, QUICK COMMAND FOR MULTIPLE SCENARIOS

AI HINT COMMAND分类推荐榜首Pricing unverifiedView details
KiroCoding & development

Kiro is an AI engineering tool for developers that organizes requirements into specifications, architectures, and tasks, generates code via agents, and supports the entire workflow—from planning to code review—through property-based testing, execution memory, and integration with development tools.

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JAXModels & infrastructure

JAX is a Python numerical computing library designed for accelerators, specifically tailored for high-performance array computations and large-scale machine learning. It efficiently executes the same code across multiple hardware backends, including CPUs, GPUs, and TPUs.

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Open DesignDesign & 3D

OpenDesign is an open-source design workspace that can connect to local programming agents, use built-in model keys, or leverage cloud-based models, enabling the creation and editing of prototypes, web pages, presentations, and graphics within a design system; local software is free, while model services incur fees.

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MemoAIMusic & audio

MemoAI is an AI-powered audio-to-text tool that supports localized processing, eliminating the need to upload data and ensuring privacy and security. It can efficiently transcribe YouTube videos, podcasts, and local audio/video files (such as MP4, MP3, AAC, M4A, etc.) into text, while offering core features like multilingual translation, speaker diarization, real-time subtitles, and floating notes—making it ideal for meeting minutes, interview transcription, content learning, and more.

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EvoMapAgents & automation

EvoMap is an infrastructure designed for the reuse of AI agent experiences. It organizes reusable strategies and repair assets with validation records via the GEP protocol, offering market- and quality-based ranking to help different agents discover, evaluate, and inherit existing capabilities.

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FinBusiness & support

CLIENT-ORIENTED AI SMART BODY。

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RowsData & analytics

Rows is a spreadsheet tool that combines AI analytics, data integration, and interactive reporting, enabling you to organize documents and business data using natural language, merge datasets, generate reports, and build computational models. The official website currently indicates that it has been integrated with Superhuman and provides a corresponding link to continue using the service.

DATA PROCESSING FOR AI FORMS待评分 · 分类列表推荐Pricing unverifiedView details
ClipDropImages & editing

Clipdrop is a suite of AI-powered image creation and editing tools, covering background removal, local cleanup, image enlargement, upscaling, relighting, text removal, and background replacement. It allows users to process images directly in the browser and also provides developers with an API for integrating these capabilities into their applications.

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Udacity AI学院Education & languages

Udacity AI Academy is the gateway to AI courses and learning paths, covering machine learning, deep learning, computer vision, natural language processing, and AI product management, with courses and project-based training available at both beginner and advanced levels.

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AI, as it happens

1427 published stories
2026-11-08
Follow the timeline
05:28

b12192

The latest release of llama.cpp adds support for the MageVL-Cowork model and adjusts how rope frequencies are handled, now stored at the model level within clip_model instead of being copied into each clip_layer. The loader verifies that rope_freqs is a 32-bit floating-point array with dimensions matching d_head, ensuring compatibility with expected 4:6:6 splits in the computational graph.

Inference systems & deploymentRead original
05:11

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.

Inference systems & deploymentRead original
01:49

Show HN: UK: Skip Royal Mail QR Code Queues with the Prince of Post

This scratches an itch I experience most months. When you get a "super handy QR Code" from a service, like Asos, Vinted and others that means you have to physically go to a post office to post your parcel. About ten years ago this was revolutionary convenience, but now it's a frustration.If you're like me you use Royal Mail's collection service to ship most of your parcels/returns from home, and post offices are open for ridiculously narrow times of day these days. Royal Mail don't provide an online facility to create a label from these in-person QR codes, so I built one instead.Behold, Citizen - Prince of Post! https://princeofpost.comI had some fun designing this, and it's something that I'll genuinely use all the time, so I thought I'd share it for others with this problem too. I couldn't find any prior art, but if you want to ruin my day please do tell me about anywhere that does this already :-) Comments URL: https://news.ycombinator.com/item?id=50406466 Points: 1 # Comments: 0

Startups & new venturesRead original
01:27

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

Startups & new venturesRead original
2026-11-07
Follow the timeline
19:58

b12188

The server update addresses slot processing order by ensuring parent slots are visited before child slots, preventing delays caused by child tasks landing on lower slot IDs. This change ensures all child tasks join the same batch after being woken by their parent. Additionally, new test tags have been introduced for monitoring: __TEST_TAG_WAIT_PARENT_SLOT__ for child slot waits, __TEST_TAG_PROMPT_CACHE_RESTORE__ for prompt cache restores, and __TEST_TAG_PROMPT_CACHE_FULL_RESTORE__ when a cached prompt is fully contained in a new one based on token counts.

Inference systems & deploymentRead original
19:42

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.

Inference systems & deploymentRead original
19:11

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.

Inference systems & deploymentRead original
18:52

b12185

A fix for shared memory bank conflicts in the lightning indexer has been implemented for CUDA support in llama.cpp version b12185, improving performance and stability on CUDA-enabled devices.

Inference systems & deploymentRead original
17:47

b12184

The llama.cpp release b12184 includes a fix to add a missing link to pthread and privately link Threads::Threads, addressing potential runtime issues. The release provides precompiled binaries for multiple platforms including macOS, Linux, Windows, Android, and openEuler, supporting various backends such as CUDA, Vulkan, ROCm, OpenVINO, SYCL, and Snapdragon-specific hardware. Additional UI components are also available.

Inference systems & deploymentRead original
17:17

b12183

The release includes the addition of arange functionality for OpenCL, enhancing support for array operations in the OpenCL backend. This update is part of a broader set of improvements and compatibility fixes across multiple platforms, including macOS, Linux, Windows, Android, and various GPU and NPU backends.

Inference systems & deploymentRead original
11:30

b12182

The latest release of llama.cpp (v1.2182) includes a change to raise the compute view limit for buffers with few tensors in the meta backend, along with reverting the deepseek41 test model back to a 6-layer configuration. The release provides precompiled binaries for multiple platforms including macOS, Linux, Windows, Android, and iOS, supporting various backends such as CUDA, Vulkan, ROCm, OpenVINO, SYCL, and Snapdragon-specific hardware. Some openEuler builds remain disabled.

Inference systems & deploymentRead original
07:18

b12180

The release adds the Kimi-K3.1-Pro text model to llama.cpp, replacing full-attention MLA layers in K3 with DSA (Dynamic Sparse Attention) layers featuring a lightning indexer. The indexer uses an additive mask over the cache and reuses sparse flash attention paths, while preserving existing KDA layers and MoE components. The model's architecture includes four indexer tensors per DSA layer, hybrid memory for caching, and maintains quantization integrity by excluding indexer parameters from quant overrides. Verified against HF checkpoint with identical PPL beyond context length, and supports multiple platforms including macOS, Linux, Windows, Android, and iOS.

Inference systems & deploymentRead original
04:43

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.

Inference systems & deploymentRead original
01:09

b12177

A fix has been implemented to prevent crashes in the command-line interface when encountering invalid UTF-8 in prompts or files, with assistance from Claude. This update is part of the b12177 release of llama.cpp, which includes various binary distributions for macOS, Linux, Windows, Android, and other platforms.

Inference systems & deploymentRead original
00:39

b12176

The update qualifies calls to math functions like isnan and signbit with std:: to ensure compatibility with C++ standard library overloads, addressing issues on NetBSD 11.99.9/x86_64 with gcc 14.4.0. Additional C math function calls are standardized using std:: prefixes (e.g., std::fabs, std::copysign) instead of non-existent std::fabsf variants, improving accuracy by keeping computations in double precision. The change results in a minor behavioral difference with a relative error of at most 1.4e-7, well below test tolerances.

Inference systems & deploymentRead original
00:07

b12175

A fix was implemented to override the hardware_concurrency value in CI tests, addressing an issue where test-llama-context and test-backend-ops hung due to incorrect thread count estimation on 8-CPU runners. The solution sets default values of 8 for TEST_ARG_HARDWARE_CONCURRENCY and 4 for TEST_ARG_PARALLEL_WORKERS specifically for the cpu-x64-high-perf configuration.

Inference systems & deploymentRead original
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