# Artificial Intelligence News (`visita/artificial-intelligence-news`) Actor Transform the overwhelming flood of artificial intelligence news into precise, actionable intelligence. This actor monitors 25+ premier AI research blogs and news feeds, using advanced LLM analysis to extract model updates, benchmarks, and industry-defining shifts. - **URL**: https://apify.com/visita/artificial-intelligence-news.md - **Developed by:** [Visita Intelligence](https://apify.com/visita) (community) - **Categories:** News, AI, Developer tools - **Stats:** 18 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 summarize article (ai) - standards This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## ๐Ÿค– AI News Intelligence Actor Transform the overwhelming flood of artificial intelligence news into precise, actionable intelligence. This actor monitors 25+ premier AI research blogs and news feeds, using advanced LLM analysis to extract model updates, benchmarks, and industry-defining shifts. ### ๐Ÿš€ Key Features - **25+ Elite AI Sources**: Real-time monitoring of OpenAI, Google Research, DeepMind, NVIDIA, Anthropic, and more. - **AI Analyst Insights**: Every headline is processed by a specialized AI News Analyst to produce executive summaries. - **Model Tracking**: Automatically extracts mentions of new models (e.g., GPT-5, Claude 4, Llama 3) and associated benchmarks. - **Significance Scoring (0-100)**: Instantly identify high-impact research versus routine product updates. - **Database Synchronization**: Admin mode seamlessly syncs structured data to your Supabase `ai_news` table for long-term intelligence gathering. - **Discord Alerts**: Real-time notifications for major product launches and high-significance breakthroughs. ### ๐Ÿ“‹ Comprehensive Source Catalog Monitor the entire AI landscape from a single entry point: | Category | Sources | |---|---| | **The Titans** | OpenAI, Google, DeepMind, Meta, Microsoft, NVIDIA, Apple | | **Research Labs** | Berkeley AI (BAIR), MIT News, Hugging Face, Stanford | | **Industry News** | TechCrunch AI, The Verge, Wired, NYTimes, The Guardian | | **Deep Tech & ML** | IEEE Spectrum, ScienceDaily, ML Mastery, AWS ML Blog | | **Analytics & Data** | KDnuggets, Towards Data Science, MarkTechPost, Towards AI | ### ๐Ÿ› ๏ธ Output Data Structure The actor produces rich, structured JSON for every article: - `title`: Sanitized headline. - `summary`: AI-generated executive summary. - `affected_models`: List of models mentioned (e.g., `["GPT-4o", "Claude 3.5 Sonnet"]`). - `key_entities`: Relevant companies and organizations. - `impact_score`: Numeric significance (0 = Minor, 100 = Industry Defining). - `content_type`: Categorization (e.g., `Research Paper`, `Product Launch`, `Model Update`). - `benchmark_results`: Extracted performance metrics if available. ### โš™๏ธ Configuration 1. **Source Select**: Choose specific feeds or monitor "All AI Sources". 2. **Max Articles**: Control the depth of your intelligence gathering. 3. **๐Ÿ” Admin Mode**: Toggle to scan live sources and sync analyzed articles to the Intelligence Library database. 4. **Discord Webhook**: Enter your URL to receive instant alerts for high-impact news. ### ๐Ÿ“ˆ Use Cases - **Competitive Intelligence**: Stay ahead of competitor model releases. - **Curated Newsletters**: Power your AI-focused newsletter with high-quality, pre-summarized content. - **Market Analysis**: Track industry trends and investment shifts in real-time. - **Academic Monitoring**: Keep up with the latest research papers without manual scanning. --- *Built for the next frontier of AI. Powered by Apify.* # Actor input Schema ## `source` (type: `string`): Choose your preferred intelligence source. ## `customFeedUrl` (type: `string`): If 'Custom' is selected, paste the RSS URL here. ## `maxArticles` (type: `integer`): How many articles to analyze? (Max 50 recommended per run). ## `startDate` (type: `string`): Format: YYYY-MM-DD. Fetch articles published on or after this date. (Prioritizes newest). ## `endDate` (type: `string`): Format: YYYY-MM-DD. Fetch articles published on or before this date. ## `region` (type: `string`): Filter the intelligence reports to a specific geographical region. ## `discordWebhookUrl` (type: `string`): Optional: Send high-impact alerts (Score > 70) directly to a Discord channel. ## `adminMode` (type: `boolean`): If enabled, the actor scans live sources and syncs analyzed articles to the Intelligence Library database. ## `runTestMode` (type: `boolean`): Internal test mode for fast system checks without using AI credits or external requests. Returns dummy data. ## Actor input object example ```json { "source": "all", "maxArticles": 1, "region": "ALL", "adminMode": false, "runTestMode": true } ```` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "source": "all", "customFeedUrl": "", "maxArticles": 1, "region": "ALL", "discordWebhookUrl": "", "runTestMode": true }; // Run the Actor and wait for it to finish const run = await client.actor("visita/artificial-intelligence-news").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "source": "all", "customFeedUrl": "", "maxArticles": 1, "region": "ALL", "discordWebhookUrl": "", "runTestMode": True, } # Run the Actor and wait for it to finish run = client.actor("visita/artificial-intelligence-news").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "source": "all", "customFeedUrl": "", "maxArticles": 1, "region": "ALL", "discordWebhookUrl": "", "runTestMode": true }' | apify call visita/artificial-intelligence-news --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=visita/artificial-intelligence-news", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Artificial Intelligence News", "description": "Transform the overwhelming flood of artificial intelligence news into precise, actionable intelligence. This actor monitors 25+ premier AI research blogs and news feeds, using advanced LLM analysis to extract model updates, benchmarks, and industry-defining shifts.", "version": "0.0", "x-build-id": "N88HmjI96q5CMBBKE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/visita~artificial-intelligence-news/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-visita-artificial-intelligence-news", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/visita~artificial-intelligence-news/runs": { "post": { "operationId": "runs-sync-visita-artificial-intelligence-news", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/visita~artificial-intelligence-news/run-sync": { "post": { "operationId": "run-sync-visita-artificial-intelligence-news", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "source", "maxArticles" ], "properties": { "source": { "title": "๐Ÿ“ก News Source", "enum": [ "all", "openai", "ai_news_org", "techcrunch_ai", "google_blog", "guardian_ai", "nytimes_ai", "nvidia", "the_conversation_ai", "ai_business", "ieee_spectrum_ai", "sciencedaily_ai", "the_verge_ai", "ml_mastery", "aws_ml", "bair_blog", "google_research", "deepmind", "mit_ai", "kdnuggets", "marktechpost", "towards_ai", "apple_ml", "towards_ds", "huggingface", "custom" ], "type": "string", "description": "Choose your preferred intelligence source.", "default": "all" }, "customFeedUrl": { "title": "๐Ÿ”— Custom RSS Feed URL", "type": "string", "description": "If 'Custom' is selected, paste the RSS URL here." }, "maxArticles": { "title": "๐Ÿ”ข Maximum Articles", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many articles to analyze? (Max 50 recommended per run).", "default": 10 }, "startDate": { "title": "๐Ÿ“… Start Date (Optional)", "type": "string", "description": "Format: YYYY-MM-DD. Fetch articles published on or after this date. (Prioritizes newest)." }, "endDate": { "title": "๐Ÿ“… End Date (Optional)", "type": "string", "description": "Format: YYYY-MM-DD. Fetch articles published on or before this date." }, "region": { "title": "๐Ÿ“ Focus Region", "enum": [ "ALL", "US", "EU", "Global", "China", "ZA", "GB", "DE" ], "type": "string", "description": "Filter the intelligence reports to a specific geographical region.", "default": "ALL" }, "discordWebhookUrl": { "title": "๐Ÿ”” Discord Webhook URL", "type": "string", "description": "Optional: Send high-impact alerts (Score > 70) directly to a Discord channel." }, "adminMode": { "title": "๐Ÿ” Admin Mode (Sync to Library)", "type": "boolean", "description": "If enabled, the actor scans live sources and syncs analyzed articles to the Intelligence Library database.", "default": false }, "runTestMode": { "title": "๐Ÿงช QA / Test Mode", "type": "boolean", "description": "Internal test mode for fast system checks without using AI credits or external requests. Returns dummy data.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```