21:38
Show HN: A free resume builder that runs in the browser (PDF and DOCX)
Article URL: https://myuscareerpath.com/tools/resume-builder Comments URL: https://news.ycombinator.com/item?id=50483310 Points: 1 # Comments: 0
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Models / 01Abstention Is Not Threshold Compliance: Stated Scoring Rules in Open Language ModelsarXiv cs.CL
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Abstention Is Not Threshold Compliance: Stated Scoring Rules in Open Language Models
arXiv cs.CLProducts & applications / 023 ways AI is changing the healthcare revenue cycleSiliconANGLE AI
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3 ways AI is changing the healthcare revenue cycle
SiliconANGLE AIModels / 034 insights from Block Builderlab Launch Event 2026: AI agents join the team as working colleaguesSiliconANGLE AI
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4 insights from Block Builderlab Launch Event 2026: AI agents join the team as working colleagues
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Open DesignDesign & 3DOpenDesign 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.
分类推荐榜首JJAXModels & infrastructureJAX 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.
分类推荐榜首MMemoAIMusic & audioMemoAI 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.
分类推荐榜首EEvoMapAgents & automationEvoMap 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.
分类推荐榜首KKiroCoding & developmentKiro 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.
分类推荐榜首AAI ShortWriting & contentAIS ALERT MANAGEMENT AND SHARED PLATFORM, QUICK COMMAND FOR MULTIPLE SCENARIOS
分类推荐榜首CClipDropImages & editingClipdrop 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.
待评分 · 分类列表推荐UUdacity AI学院Education & languagesUdacity 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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2026-11-13
Follow the timeline20:00
Protein Startups Are Selling Lots Of Snacks And Drinks. Our Sample Tasting Found Most Neither Great Nor Horrible
As we chronicled earlier this week, both startups and established food brands are making it simpler than ever to up protein intake. From sodas to snack bars to ice cream, it’s now possible to get a fix of this coveted macronutrient with foods and drinks more commonly associated with sugar, starch and fat. But, do they taste good? To find out, we hit up a local Target for a selection of protein foods sold by venture-backed startups and subjected them to a taste test. Here are our findings.
18:55
Show HN: A Python PoW ledger with post-quantum, vault and agent-allowance
Article URL: https://github.com/Sajidsaj/mycoin-research Comments URL: https://news.ycombinator.com/item?id=50481675 Points: 1 # Comments: 0
17:44
n8n@2.47.7
The n8n 2.47.7 update resolves a bug where executions using global credentials were incorrectly redacted, ensuring proper visibility of credential data in execution logs.
17:41
n8n@2.48.4
The n8n 2.48.4 update resolves a bug where executions using global credentials were incorrectly redacted, ensuring proper visibility of credential data in execution logs.
17:40
n8n@3.2.2
Bug fixes included in the n8n 3.2.2 release, published on November 13, 2026.
17:32
SET allow_preview_features = 1: Self-service previews in ClickHouse Cloud
ClickHouse Cloud now has a Previews page where anyone can discover preview features, enable some themselves, join waitlists for others, and send feedback, with API support for automation.
17:29
New in n8n: Public API rate limits that keep every team on your instance running
Cap public API requests per API key in n8n, with 429 headers that tell clients when to retry and idempotency keys for safe retries.
17:27
Is there a 'right amount' of AI?
Article URL: https://coyotetracks.org/blog/right-amount-of-ai/ Comments URL: https://news.ycombinator.com/item?id=50480659 Points: 32 # Comments: 40
16:28
n8n@1.123.96
The n8n 1.123.96 update addresses a bug that made JSON highlight color invisible on light themes and includes an update to the @modelcontextprotocol/sdk.
16:24
n8n@2.47.6
The n8n 2.47.6 update includes bug fixes for Redis cache handling, prompt caching, legacy data reading, JSON highlighting, and Pinecone Vector Store integration. New features enable Gateway credits promotions to be displayed in the editor. Performance improvements focus on reducing runtime bundle size and optimizing expression evaluation.
13:00
KernelMosaic: An Open Dataset and Agentic Framework for CUDA Kernel Generation
arXiv:2611.14604v1 Announce Type: new Abstract: Training large language models to generate efficient CUDA kernels requires supervision spanning diverse computational requirements and iterative code optimization. Constructing this supervision is challenging because of heterogeneous specifications, and useful implementations emerge through iterative complicated testing and refinement. We introduce KernelMosaic, an open dataset pairing diverse CUDA tasks with verified solutions and trajectories. Human-guided review and diversity-aware selection curate tasks expressed as natural-language descriptions, reference programs, mathematical specifications, and their intersections. To build the solutions and trajectories, our agentic framework guides a strong LLM through implementation, correctness repair, and performance optimization with reusable CUDA guidance and execution feedback. Supervised fine-tuning of a small open-source model on KernelMosaic raises correctness from 4%, 0%, and 0% to 88%, 82%, and 16% on KernelBench L1, L2, and L3, respectively, while increasing the fraction of tasks with kernels faster than PyTorch eager at every level. Further training experiments show that supervision from the curated trajectories substantially outperforms direct responses and promotes sustained testing and revision. These results demonstrate that KernelMosaic enables a general-purpose model to achieve substantial gains in CUDA kernel generation.
13:00
New AI “copilot” helps engineers design better structures
The system asks humans for feedback to increase trust in machine-generated designs for buildings and bridges.
07:36
Show HN: Agentview Chat – a chat UI for Claude Code background sessions
Article URL: https://github.com/clumsy-ug/agentview-chat Comments URL: https://news.ycombinator.com/item?id=50475982 Points: 1 # Comments: 0
05:31
Microsoft Research Focus – Edition #98
What's new in research at Microsoft? Host Anson Ho explores the latest, including AI-powered universal translation, a breakthrough in a 31-year-old mathematics challenge, and advances making AI coding agents faster and more efficient. The post Microsoft Research Focus – Edition #98 appeared first on Microsoft Research.
04:52
Kubernetes gets a second act as AI agents turn one prompt into thousands of inference calls
The rise of agentic AI systems is giving Kubernetes, long valued for its reliability and predictability, an unexpected second act. As AI spending shifts from training models toward serving them and running agents, the open-source community is developing tools to handle the growing volume of inference requests. The orchestration platform was built from the start […] The post Kubernetes gets a second act as AI agents turn one prompt into thousands of inference calls appeared first on SiliconANGLE.
03:07
LLMON: An LLM-Native Markup Language, now in Granite 4.1 3B and 8B
IBM has introduced LLMON (LLM Object Notation), a new markup language designed to explicitly communicate structure and semantics to large language models. Built to address issues like prompt injection attacks and brittle behavior in smaller models, LLMON uses reserved special-token delimiters to mark semantically coherent components such as instructions, data, and requirements, enabling precise binding between them. Two experimental preview models—granite-4.1-3b-LLMON-preview and granite-4.1-8b-LLMON-preview—are now available, alongside a GitHub repository with conversion tools, workflows, and examples. LLMON enhances robustness by separating instruction from data, reducing indirect prompt injection success rates nearly to zero while maintaining performance comparable to standard Granite 4.1 Instruct models. It also supports custom schemas via LoRA fine-tuning, as demonstrated in ScienceWorld and tool-calling agent use cases. The approach is distinct from JSON, which lacks model-friendly structure, and complements existing chat templates by adding semantic clarity across roles.
02:43
Optimizing cost per task and proving agent ROI on Amazon Bedrock
Comparing per-token prices hides the real cost of running a model on Amazon Bedrock. This post shows how to calculate the true cost per task across four hidden cost drivers, reduce it with caching, routing, and output constraints, and prove agent ROI with human baselines, holdout experiments, and a five-dimension scorecard.
01:19
Own Your Intelligence: The Key to Lasting AI Advantage
Learn why companies must own their agent systems, governance, context, and feedback loops to turn generic AI into lasting business advantage.
00:16
Migrate to Amazon Bedrock Managed Knowledge Base with your coding agent
The migration guide in the amazon-bedrock skill helps you migrate a customer-managed Amazon Bedrock knowledge base to a Managed Knowledge Base. Your coding agent plans the move with read-only discovery, creates the new knowledge base or an infrastructure-as-code template alongside the original, and validates retrieval before you cut over.
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