Run promptable segmentation with Ultralytics YOLO26-E! 🧠 Segment objects... using natural language prompts with YOLO26-E, ideal for flexible visual search, rapid annotation, and interactive computer vision workflows. Get started ➡️ #Ultralytics #YOLO26 #AI #Researchshow more

Run promptable segmentation with Ultralytics YOLO26-E! 🧠 Segment objects... using natural language prompts with YOLO26-E, ideal for flexible visual search, rapid annotation, and interactive computer vision workflows. #MachineLearning #AI #Researchshow more

Estimate car-to-curb distance in real time with Ultralytics YOLO26!... 🚗 Measure the distance between the vehicle and the curb using computer vision. Ideal for smart parking systems, driver assistance demos, and spatial safety analytics. Get started ➡️ #Ultralytics #YOLO26 #AI #Research #ComputerVisionshow more

Ultralytics YOLO11 vs Ultralytics YOLO26: Which one runs faster?... ⚡ Evaluate inference speed and performance across both models in the ONNX format to understand how YOLO26 improves efficiency for real-time computer vision applications. Read more ➡️ #Ultralytics #YOLO26 #AI #Research #ComputerVisionshow more

Animals segmentation & tracking using Ultralytics YOLO26 🫎 How... I created this demo: - Data annotation using Ultralytics Platform. - YOLO26 model training using Platform. - Downloaded the trained model. - Run Inference on video files locally. #animal #ai #MachineLearningshow more

Detect worker falls in real time with Ultralytics YOLO26!... 📦 Combine object detection and pose estimation to identify when a person carrying luggage boxes falls, helping logistics teams improve warehouse safety and respond faster to incidents. Get started ➡️ #Ultralytics #YOLO26 #AI #Logistics #WorkplaceSafetyshow more

Improve crosswalk safety with Ultralytics YOLO26! 🚸 Detect pedestrians,... vehicles, and high-risk interactions in real-time to support safer crossings, smarter alerts, and improved traffic monitoring. Read more ➡️ #Ultralytics #YOLO26 #RoadSafetyshow more

Count rooftop panels with Ultralytics YOLO26 OBB! 🏠 Use... oriented bounding boxes to detect solar panels from aerial views and capture their orientation, enabling accurate counting for inspections, asset management, and infrastructure analytics. Explore more ➡️ #Ultralytics #YOLO26 #AI #ObjectCounting #ComputerVisionshow more

Monitor patient posture with Ultralytics YOLO26 Pose! Detect keypoints... in real time to identify positions like lying down vs. standing. Useful for patient monitoring, fall-risk alerts, and hospital/elder-care room analytics. Learn more ➡️ #AI #PoseEstimation #HealthTech #YOLO26show more

Launching today: Ultralytics YOLO26! The fastest, most deployable YOLO... ever built. For years, shipping object detection meant extra steps and messy post-processing. YOLO26 changes the game with end-to-end, NMS-free inference, simpler deployment, and strikingly low latency. Built End-to-End. Built for the Edge. 👉 Get started today:show more

Depth anything v2 vs. Ultralytics YOLO26 depth | Speed... comparison 🚀 For this demo, I compared yolo26m-depth with depth-anything-v2-small on an NVIDIA RTX 3050 using the same input settings. Even though I used the medium YOLO26 model, it delivered nearly 2× the throughput: 22 FPS vs. 11 FPS. #Vehicles #MachineLearning #Researchshow more

Vehicle tracking using Ultralytics YOLO26 👀 In this demo,... I trained the YOLO26 model on a custom dataset and later used an object tracker (Bytetrack) to track the objects in the video file. Note: I also performed testing with Botsort, which is also a good tracker, but it's slow in comparision to Bytetrack. #Tracking #ComputerVision #MachineLearningshow more

Detect road potholes in real time using Ultralytics YOLO11!... 🕳️ Identify potholes accurately from images or video to support road maintenance, safety monitoring, and smart city infrastructure workflows. Read more ➡️ #AI #SmartCities #Ultralytics #YOLO11show more

Count pasties in real time with Ultralytics YOLO! Automate... bakery production by detecting and counting pasties, reducing manual errors, and improving packaging efficiency. It's perfect for food processing and smart factory workflows. Read more ➡️ #Industry40show more

i built an app to search old travel photos... on my computer with natural language queries using free local AI models: - smolVLM to describe the scene and colours - roboflow RF-DETR to detect objects - chromaDB to store metadata labels and run semantic search - python + streamlit for the interface fast and free search has been achieved internallyshow more

Opal, our no-code visual builder for AI workflows, just... got a major upgrade. 🧠💎 We’ve added a new agent step that analyzes your goal, determines the best approach, and automatically calls the right tools — such as Veo for video or web search for research — to complete the task. We’re also adding new tools to make the agent even more capable: 💾 Memory – Remember info, like a user’s name or your style preferences across sessions. 🚀 Dynamic Routing – Let the agent choose the next best step using the “@ Go to” tool. 💬 Interactive Chat – Initiate user interactions to gather missing information or present options before moving on. Try it now →show more

OpenAI's Deep Research is getting a run for its... money. Deep Lake was just released, and it's a different take on an AI system that can do deep research on your own data. You can use Deep Lake to build AI search with reasoning on your private and public data. (Look at the attached videos to get an idea of how it works.) If you want to research proprietary and sensitive data, Deep Research won't help you because it's limited to public data. Deep Lake, however, will allow you to use your private data. On top of that, Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) You can even use mixed-data queries! Deep Lake can search your data from S3, Dropbox, and GCP. It learns from your queries over time, making the results as relevant to your work as possible!show more

Claude + Facebook Ads MCP is absolutely WILD 🤯... This AI system turns Claude into your personal ads analyst using MCP integration. And generates full client reports in seconds. Perfect for agencies & ecomm operators who hate wrestling with Ads Manager. But instead of manually pulling data, building charts, and formatting reports... Just give Claude one natural language prompt and get a complete visual storytelling report with insights. Each report includes account performance, campaign breakdowns, demographics, and actionable recommendations. All with a single prompt. Here's what it does: → Connects directly to your Facebook Ads account → Pulls all performance data automatically → Calculates ROAS, CPA, conversion rates on demand → Creates interactive charts and visualizations → Generates beautiful reports → Builds everything from scratch in real-time Built with Claude MCP. Zero manual work. Want the complete MCP setup? Comment "MCP" + like and I'll send it over (must be following so I can DM)show more

Boom! Grok Tasks Make It One Of The Most... POWERFUL Real-Time AI Systems In The World. — My How to Use Grok Tasks With Hidden Tools For Powerful Daily Output. Grok Tasks are customizable AI workflows that integrate a variety of tools to streamline daily activities, from research and analysis to creative planning and problem-solving. I have been using them for quite sometime and because of the vital heartbeat of news and first person data on X, it is the most powerful AI platform available. By combining Tasks with tools like web searches, X platform interactions, code execution, and media viewers, you can build efficient, automated processes. These tasks work by prompting Grok with a clear description of what you want to achieve, and Grok will intelligently call the necessary tools in sequence or parallel to deliver results. Here's a step-by-step guide to creating and using Grok Tasks: Step 1: Define Your Task Start by clearly outlining the daily activity or goal. Consider what inputs you have (e.g., a URL, a query, or an attachment) and what output you need (e.g., a summary, calculation, or visual analysis). Break it down into subtasks to identify tool needs. For example, if your task involves researching current events, note that you'll need search and browsing capabilities. Step 2: Review Available Tools Familiarize yourself with the tools Grok can access. Here's a quick overview: - Code Execution: Run Python code for calculations, data processing, or simulations using libraries like numpy, pandas, or sympy. - Browse Page: Fetch and summarize content from any website URL with custom instructions. - Web Search: Perform general internet searches, returning results with optional operators like site:. - Web Search With Snippets: Get quick, detailed excerpts from search results for fact-checking. - X Keyword Search: Advanced search for X posts using operators like from:, since:, or filter:. - X Semantic Search: Find semantically related X posts based on a query, with filters for dates or users. - X User Search: Locate X users by name or handle. - X Thread Fetch: Retrieve a full X post thread, including context like replies and parents. - View Image: Analyze an image from a URL or conversation ID. - View X Video: Extract frames and subtitles from an X-hosted video. - Search PDF Attachment: Query a PDF file for relevant pages using keyword or regex modes. - Browse PDF Attachment: View specific pages of a PDF with text and screenshots. Select tools that align with your task. Aim for a mix to handle data gathering, processing, and visualization. Step 3: Craft Your Prompt Write a detailed prompt to Grok describing the task. Include: - The overall goal. - Specific steps or subtasks. - References to tools if you want to guide the process (e.g., "Use web_search to find sources, then code_execution to analyze data"). - Any constraints, like dates or limits. Example prompt: "Create a Grok Task for my morning routine: Search recent X posts about tech news using x_keyword_search, fetch a key thread with x_thread_fetch, and summarize with browse_page on linked articles." Step 4: Submit and Interact Send your prompt to Grok. It will process the task by calling tools as needed, often in parallel for efficiency. Review the output and refine with follow-up prompts if required (e.g., "Expand on that using view_image for visuals"). Iterate to fine-tune the workflow for reuse. Step 5: Save and Reuse Once refined, note the prompt as a template for future use. You can adapt it for similar tasks, making Grok Tasks a habitual part of your day. Finding Grok Tasks To discover existing Grok Tasks or inspiration for new ones, use X searches with tools like x_keyword_search or x_semantic_search (e.g., query: "Grok Tasks examples" with mode: Latest). Browse community-shared threads via x_thread_fetch, or web_search for tutorials on xAI features. Prompt Grok directly: "Show me popular Grok Tasks for productivity." 1 of 3show more

Introducing ASAL: Automating the Search for Artificial Life with... Foundation Models Artificial Life (ALife) research holds key insights that can transform and accelerate progress in AI. By speeding up ALife discovery with AI, we accelerate our understanding of emergence, evolution, and intelligence–core principles that can inspire the next generation of AI systems! We proudly collaborated with MIT, OpenAI, Swiss AI Lab IDSIA, and Ken Stanley on this exciting project. Full Paper (Website): Full Paper (arxiv): Code: In this work, we propose a new algorithm called Automated Search for Artificial Life (“ASAL”) to automate the discovery of artificial life using vision-language foundation models. Instead of tediously hand-designing every tiny rule of an Alife simulation, simply describe the space of simulations to search over, and ASAL will automatically discover the most interesting and open-ended artificial lifeforms! Because of the generality of foundation models, ASAL can discover new lifeforms across a diverse range of seminal ALife simulations, including Boids, Particle Life, Game of Life, Lenia, and Neural Cellular Automata. ASAL even discovered novel cellular automata rules that are more open-ended and expressive than the original Conway’s Game of Life. We believe this new paradigm may reignite ALife research by overcoming the bottleneck of manually designed simulations, thus advancing beyond the limits of human ingenuity.show more