Cewsco is a premium all-in-one AI platform.

homebutler is a tool that lets AI manage your homelab through the Model Context Protocol without requiring SSH access. It's just one binary away.

PDF Insight is a local-first AI tool that sorts and merges your PDFs entirely on your computer, ensuring privacy. Designed for accountants and self-employed users, it handles tax slips like T4 and RL-1, uses Ollama for AI and Tesseract for OCR locally. Offers a free trial and various pricing plans.

Foray is an AI-powered business blueprint generator that produces 100-160 page PDFs with market analysis, competitor landscape, financial models, and go-to-market strategy in 45-90 minutes. It stress-tests ideas through adversarial review and kill conditions, helping entrepreneurs validate viability before committing resources. Free tier and multiple pricing plans available.

Dribble is an open-source, AI-powered SQL IDE for databases. It connects to Postgres, lets you browse schemas, run queries in notebooks, explore tables, and chat with an AI agent (Claude Opus 4.8) that analyzes your data and writes read-only SQL.

Anthropic launches Claude Science, an AI workbench for life sciences researchers, integrated with Modal to provide elastic compute infrastructure for running data processing, structure prediction, and molecule design directly from a conversation.

Eight papers from Together AI accepted to ICML 2026, covering the full AI stack from agents to GPU kernels. These research works are integrated into the Together platform and already benefit production workloads.

Introducing GeneBench-Pro, a new benchmark testing AI performance in genomics, biology, and scientific research using complex, real-world datasets.

OpenAI engineers used large-scale core dump analysis to debug rare infrastructure crashes, uncovering both a hardware fault and a long-standing software bug.

Every Eval Ever (EEE) and Hugging Face Community Evals are now intercompatible, allowing cross-posting and interpretation of evaluation results with links to open models, leaderboards, and a unified standardized metadata store.

llmaker is an open-source platform that lets you run the complete modern LLM stack on your own infrastructure — large language models, vector databases, embeddings, caching, observability, and a built-in retrieval & agent layer — provisioned, networked, and production-shaped from a single command.

This article argues from a probabilistic perspective that AI alignment cannot fully eliminate jailbreaks, and in agentic systems, the fusion of control and data planes leads to privilege erosion, making any content readable by the model a potential attack vector.

Trajeckt is a runtime enforcement gateway for AI agents that blocks multi-step exploits deterministicly in ~1.6ms by enforcing sealed pre-session commitments. It catches data exfiltration sequences that per-action security checks miss.

OpenClaw has released native companion apps for iOS and Android. These apps are not standalone chatbots but turn a phone into a node in a self-hosted AI agent network. The phone connects via WebSocket to a Gateway that runs the actual agent, adding device hardware capabilities like camera, location, voice, and Canvas. The article covers architecture, capabilities, pairing, security, and use cases.

Google announced on Monday that the Gemini app's personalized image generation feature, powered by Nano Banana, is now available for free to all eligible users in the U.S., previously restricted to Plus, Pro, and Ultra subscribers. The feature uses data from users' Google accounts—such as Gmail, Google Photos, YouTube, and Search—to understand preferences and generate images reflecting their unique interests without the need to specify them in prompts.

Wall Street terminals cost up to $30k/year; this new platform brings similar capabilities to retail investors at a fraction of the price, including real-time breakouts, AI predictions, and institutional buying data.

AI Agent Audit is a Rust CLI tool for AI-assisted security review of Solidity smart contracts. It discovers vulnerabilities, deduplicates findings, generates runnable PoCs, and produces professional audit reports. It uses LLMs (default OpenAI Codex) and supports various audit types (Code4rena, Immunefi, etc.). Currently in public beta, it aims to accelerate expert review, not replace manual auditing.

South Korea designates physical AI as a national strategic industry, aiming to develop a world-model-based foundation model within three years and commercialize humanoid robots. Hyundai invests $5.8B in robot manufacturing and partners with Boston Dynamics to produce 30,000 Atlas robots annually by 2028. However, labor unions are striking over job security, and societal tensions arise over sharing AI-driven profits.

Envelope is a design tool for AI agent teams.

A Harvard Business School meta-analysis finds women are 22% less likely to use generative AI. Despite common explanations like lack of exposure, the gap persists even when training is provided. Women's caution stems from real issues: deepfakes targeting women, gender bias in AI systems, and a 'competence penalty' for using AI. The piece argues that the solution is not to push women to use more AI, but to take their concerns seriously.

Analyze, classify, summarize, and translate this AI news article. Root object must contain exactly one key: "translations". Do not include root keys named topics, tags, importanceScore, title, summary, key_points, generateBody, or locales. translations must contain exactly "zh-CN", "en", and "ja". Each translation must contain exactly title, summary, keyPoints, and body. The application derives topics, tags, importanceScore, whyItMatters, technicalImpact, audience, difficulty, zh-TW, and zh-HK after parsing. Do not include those fields in the JSON. summary should be concise and useful, with no fixed character limit. keyPoints should be an array of two to four concise strings. When input.generateBody is true and input.body is present, body must be a rewritten article in the target locale, generated in your own words from the source text. If input.originalLanguage is en, en.body must be null because the application uses input.body directly for English. If input.originalLanguage is ja, ja.body must be null because the application uses input.body directly for Japanese. If input.originalLanguage is zh-CN, zh-CN.body must be null because the application uses input.body directly for Simplified Chinese and derives Traditional Chinese with OpenCC. body must read as a complete in-site article, not a short summary. Preserve all substantive facts, context, caveats, and timeline details from input.body. For source text of 1,500+ characters, body must be a substantial multi-paragraph article, not a compressed digest. Use multiple coherent paragraphs for body when the source contains enough material. Do not copy source paragraphs verbatim into body. If input.generateBody is false or input.body is empty, body must be null for every locale. Required JSON shape example: { "translations": { "zh-CN": { "title": "简体中文标题", "summary": "简体中文摘要。", "keyPoints": [ "简体中文要点" ], "body": null }, "en": { "title": "English title", "summary": "English summary.", "keyPoints": [ "English key point" ], "body": null }, "ja": { "title": "日本語タイトル", "summary": "日本語の要約。", "keyPoints": [ "日本語の要点" ], "body": null } } } Input article: { "title": "Predict churn before customers leave", "excerpt": null, "body": "Uh oh!\n\nThere was an error while loading. Please reload this page.\n\nNotifications\nYou must be signed in to change notification settings\n\nFork\n3\n\nStar\n143\n\nCopy path\n\nMore options\n\nMore options\n\nMore options\n\nMore options\n\nLatest commit\n\n \n\nHistory\n\nHistory\n\nHistory\n\nCopy path\n\nFolders and files\n\nNameName\n\nLast commit message\n\nLast commit date\n\nparent directory\n\n..\n\n.env.example\n\n.env.example\n\n \n\n \n\nAPI.md\n\nAPI.md\n\n \n\n \n\nGUIDE.md\n\nGUIDE.md\n\n \n\n \n\nREADME.md\n\nREADME.md\n\n \n\n \n\napp.py\n\napp.py\n\n \n\n \n\nrequirements.txt\n\nrequirements.txt\n\n \n\n \n\nAI Customer Churn Predictor\n\nAI Customer Churn Predictor - analyze call/message patterns via Telnyx APIs, AI predicts churn risk and suggests interventions.\n\nTelnyx API Endpoints Used\n\nAI Inference: POST /v2/ai/chat/completions - API reference\n\nArchitecture\n\nAPI Request\n│\n▼\n┌──────────────────┐\n│ Your App │\n└────────┬─────────┘\n│\n├──► Telnyx AI Inference\n│\n├──► Classification / triage\n│\n▼\nJSON response\n\nEnvironment Variables\n\nCopy .env.example to .env and fill in:\n\nVariable\nType\nExample\nRequired\nDescription\nWhere to get it\n\nTELNYX_API_KEY\nstring\nKEY0123456789ABCDEF\nyes\nTelnyx API v2 key\nPortal\n\nAI_MODEL\nstring\nmoonshotai/Kimi-K2.6\nno\nTelnyx AI Inference model name\nPortal\n\nPORT\ninteger\n5000\nno\nHTTP server port\n-\n\nSetup\n\ngit clone https://github.com/team-telnyx/telnyx-code-examples.git\ncd telnyx-code-examples/ai-customer-churn-predictor-python\ncp .env.example .env # ← fill in your credentials\npip install -r requirements.txt\npython app.py # starts on http://localhost:5000\n\nAPI Reference\n\nPOST /predict\n\nTriggers predict\n\ncurl -X POST http://localhost:5000/predict \\n-H "Content-Type: application/json" \\n-d '{}'\n\nResponse:\n\n{\n"id": "item-1750280400",\n"status": "created",\n"created_at": "2026-07-15T14:30:00Z"\n}\n\nPOST /predict/batch\n\nTriggers batch\n\ncurl -X POST http://localhost:5000/predict/batch \\n-H "Content-Type: application/json" \\n-d '{}'\n\nResponse:\n\n{\n"id": "item-1750280400",\n"status": "created",\n"created_at": "2026-07-15T14:30:00Z"\n}\n\nGET /predictions\n\nReturns predictions\n\ncurl http://localhost:5000/predictions\n\nResponse:\n\n{\n"items": [\n{\n"id": "item-001",\n"status": "active",\n"created_at": "2026-07-15T14:30:00Z"\n}\n]\n}\n\nGET /health\n\nReturns health\n\ncurl http://localhost:5000/health\n\nResponse:\n\n{\n"status": "ok",\n"uptime_seconds": 3842,\n"active_sessions": 2,\n"version": "1.0.0"\n}\n\nTroubleshooting\n\nIssue\nCause\nFix\n\n401 Unauthorized\nInvalid or missing API key\nVerify TELNYX_API_KEY in .env matches your key in the Portal\n\nWebhook not received\nLocal server not publicly reachable\nExpose it with a tunnel (e.g. ngrok) and set the webhook URL in the Telnyx Portal\n\n422 Unprocessable Entity\nMissing or malformed request fields\nCheck the request body against the API Reference above\n\nRelated Examples\n\nAI After Hours Emergency Triage (Python)\n\nAI Assistant Knowledge Base (Python)\n\nAI Assistant Multi Tool (Python)\n\nAI Assistant Phone Setup (Python)\n\nAI Audiobook Narrator (Python)\n\nResources\n\nAI Inference Guide\n\nTelnyx Developer Docs\n\nTelnyx Portal\n\nWhy Telnyx\n\nTelnyx is an AI Communications Infrastructure platform - voice, messaging, SIP, AI, and IoT on one private, global network.", "generateBody": true, "sourceId": "hacker-news-ai", "canonicalUrl": "https://github.com/team-telnyx/telnyx-code-examples/tree/main/ai-customer-churn-predictor-python", "originalLanguage": "en" }

Kilo introduces Next-Edit powered by Inception's Mercury Edit 2, which predicts developers' next code edits using a diffusion LLM. It offers higher acceptance and selectivity, and is free for a month.

A new AI-powered framework could transform how astronomers measure the expansion of the Universe. By analyzing images of Type Ia supernovae and modeling their environments in unprecedented detail, researchers can estimate cosmic distances with near-spectroscopic accuracy. The technique is designed for the flood of data expected from the upcoming Vera C. Rubin Observatory and may greatly improve our understanding of dark energy.

We build a Colab-ready PyGraphistry workflow for interactive graph analytics on enterprise access data. We generate a synthetic dataset of users, devices, IPs, services, roles, and geos, then convert it into nodes and edges. We enrich the graph with risk scores, centrality metrics, community detection, Isolation Forest anomaly scores, and UMAP layout embeddings. We then bind the graph in PyGraphistry and produce local PyVis visualizations for full, ego, and high-risk views.

OutYet.ai is a platform that tracks upcoming AI model releases from major labs, providing status updates, release estimates, and alerts. It monitors official sources and requires two verifications before marking a model as released.

JetBrains has announced that JetBrains Air, its Agentic Development Environment (ADE) is now available for download on Windows x64 and ARM.

AI agents suffer from statelessness, requiring constant context reloading. Memora introduces a scalable memory system decoupling storage from retrieval, achieving state-of-the-art on long-context benchmarks while using up to 98% fewer tokens.

Xenoeye is a lightweight Netflow/IPFIX/sFlow collector and analyzer that uses PostgreSQL and Grafana for network traffic monitoring and analysis without AI. It supports multiple flow protocols, uses monitoring objects and moving averages for anomaly detection, and has low resource requirements.

The article discusses how Evals, as strategic intellectual property, will shape the future of AI and its critical role in the industry.

Tidal announced new policies for AI-generated music: starting July 15, it will label fully AI-generated tracks, but from today those tracks will no longer be monetizable. The platform also plans to label 'substantially AI-generated' content and will remove or block AI music associated with fraudulent activity.