Best AI tools for< Picking Up Objects >

Dobb·E is an open-source, general framework for learning household robotic manipulation. It aims to create a 'generalist machine' for homes, a domestic assistant that can adapt and learn various tasks cost-effectively. Dobb·E can learn a new task with just five minutes of demonstration, achieving an 81% success rate in 10 NYC homes. The system is designed to accelerate research on home robots and eventually enable robot butlers in every home.

Nomagic.ai is an intelligent robotics application that offers efficient item handling solutions for e-commerce and retail leaders seeking automation. The application provides services based on Intelligent Robotics to pick, sort, or pack a variety of SKUs, ensuring performance, reliability, and scalability. Nomagic combines expertise in robotics, cloud, and deep learning with logistics experience to deliver ROI below 2 years and cost reductions up to 75%. The application is designed to work seamlessly with AutoStore™ and offers dedicated solutions like justPick for reliable picking operations.

OSARO is an AI-powered automation tool designed to revolutionize warehouse operations by offering cutting-edge robotic piece-picking solutions. The tool utilizes proprietary SightWorks™ perception and control software, powered by advanced machine learning, to ensure unparalleled precision and reliability in tasks such as bagging, kitting, and mixed-case depalletizing. OSARO provides adaptive robotics that seamlessly integrate with AMR/ASRS systems, enhancing efficiency and creating better job opportunities. With flexible pricing models like Robot-as-a-Service (RaaS) plans and 24/7 worldwide customer support through OSARO Hypercare™, the tool offers a low-risk investment for businesses seeking smarter automation solutions.

Remove.bg is an online tool that allows users to remove the background from images automatically and for free. It is a powerful tool that can be used for a variety of purposes, including creating marketing materials, product photos, and social media images. Remove.bg is easy to use and can be used by anyone, regardless of their technical skills. Simply upload an image to the website and the tool will automatically remove the background. You can then download the resulting image in a variety of formats, including PNG, JPG, and TIFF.

Bgclearer.com is an AI-powered online tool that allows users to easily remove backgrounds from images for free. The tool utilizes advanced artificial intelligence algorithms to accurately detect and remove the background of any image, saving users time and effort. With a simple and user-friendly interface, users can upload their images, apply the background removal feature, and download the edited image in seconds. Bgclearer.com is a convenient and efficient solution for individuals and businesses looking to create professional-looking images without the need for complex photo editing software.

Brightpick is an AI-powered order fulfillment solution that revolutionizes warehouse operations by enabling fully automated order picking, consolidation, and dispatch. The Brightpick Autopicker, equipped with AI robots, streamlines the fulfillment process by efficiently picking a wide range of products, from groceries to pharmaceuticals, with precision and speed. Trusted by industry leaders, Brightpick helps businesses cut costs, increase efficiency, and enhance customer service in industries such as Ecommerce, 3PL, E-Grocery, and Medical. With its innovative technology and award-winning solutions, Brightpick is reshaping the future of order fulfillment.

Vicarious is a turnkey robotics solutions integrator that uses AI to automate tasks that are too complex and versatile for traditional automation. The company's solutions are built for flexible needs, with instant changeovers in high mix operations and no fixturing required. Vicarious' solutions have a bottom-line impact, with a 50-90% reduction in labor hours and a 15-40% reduction in monthly costs. The company offers Robots-as-a-Service solutions powered by AI-backed robotics, including kitting, palletizing, packaging, and wall picking.

Vicarious is a robotics solutions integrator that uses AI to automate tasks that are too complex and versatile for traditional automation. The company's solutions are built for flexible needs and can be used in a variety of industries, including e-commerce, manufacturing, and healthcare. Vicarious's robots are able to learn and adapt to changing conditions, making them ideal for tasks that require precision and dexterity.

Kardinal is an AI-powered Last-Mile Delivery Optimization Platform dedicated to providing carrier and shipper clients with tailored logistics intelligence solutions. The platform offers route optimization, delivery slot planning, transport procurement optimization, territory sectorization, parcel picking & sorting, and PUDO location services. Kardinal utilizes AI algorithms and machine learning to continuously optimize operations, adapt to real-time conditions, and enhance future optimizations. The platform helps businesses address critical questions from strategic to operational levels, enabling them to optimize continuously and in real-time while modeling reality without compromise.

The 'YouTube Comment Finder And AI Analysis' is a comprehensive web-based tool designed to simplify the process of searching, filtering, managing, and analyzing comments on YouTube videos. It empowers users to search, filter, sort, and analyze comments with ease, leveraging AI-powered comment analysis to gain insights into sentiment, trending topics, key points, and concise summaries of comments. The tool offers features such as comment search, filtering, sorting, exporting, and random comment picking, making it a valuable asset for content creators, marketers, and individuals looking to navigate the vast sea of comments on YouTube videos.

WhatToPack is a smart packing assistant designed to help travelers pack right every time. It offers tailored packing insights for different destinations, alleviating the stress of packing for travel. The application provides destination insights, packing feedback, personalized learning, and intelligent suggestions to enhance the travel preparations of users. With WhatToPack, users can receive guidance on packing choices, weather updates, cultural norms, activity tips, and safety recommendations specific to their travel spot, ensuring they are fully equipped for every journey.

The 'ShitSpotter' repository is dedicated to developing a poop-detection algorithm and dataset for creating a phone app that helps locate dog poop in outdoor environments. The project involves training a PyTorch network to detect poop in images and provides scripts for detecting poop in unseen images using a pretrained model. The dataset consists of mostly outdoor images taken with a phone, with a process involving before and after pictures of the poop. The project aims to enable various applications, such as AR glasses for poop detection and efficient cleaning of public areas by city governments. The code, dataset, and pretrained models are open source with permissive licensing and distributed via IPFS, BitTorrent, and centralized mechanisms.

The 'llm' package for Emacs provides an interface for interacting with Large Language Models (LLMs). It abstracts functionality to a higher level, concealing API variations and ensuring compatibility with various LLMs. Users can set up providers like OpenAI, Gemini, Vertex, Claude, Ollama, GPT4All, and a fake client for testing. The package allows for chat interactions, embeddings, token counting, and function calling. It also offers advanced prompt creation and logging capabilities. Users can handle conversations, create prompts with placeholders, and contribute by creating providers.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and includes a process of embedding docs, queries, searching for top passages, creating summaries, using an LLM to re-score and select relevant summaries, putting summaries into prompt, and generating answers. The tool can be used to answer specific questions related to scientific research by leveraging citations and relevant passages from documents.

Translate texts in manga/images. Some manga/images will never be translated, therefore this project is born. * Image/Manga Translator * Samples * Online Demo * Disclaimer * Installation * Pip/venv * Poetry * Additional instructions for **Windows** * Docker * Hosting the web server * Using as CLI * Setting Translation Secrets * Using with Nvidia GPU * Building locally * Usage * Batch mode (default) * Demo mode * Web Mode * Api Mode * Related Projects * Docs * Recommended Modules * Tips to improve translation quality * Options * Language Code Reference * Translators Reference * GPT Config Reference * Using Gimp for rendering * Api Documentation * Synchronous mode * Asynchronous mode * Manual translation * Next steps * Support Us * Thanks To All Our Contributors :

The 'judges' repository is a small library designed for using and creating LLM-as-a-Judge evaluators. It offers a curated set of LLM evaluators in a low-friction format for various use cases, backed by research. Users can use these evaluators off-the-shelf or as inspiration for building custom LLM evaluators. The library provides two types of judges: Classifiers that return boolean values and Graders that return scores on a numerical or Likert scale. Users can combine multiple judges using the 'Jury' object and evaluate input-output pairs with the '.judge()' method. Additionally, the repository includes detailed instructions on picking a model, sending data to an LLM, using classifiers, combining judges, and creating custom LLM judges with 'AutoJudge'.

SkyPilot is a framework for running LLMs, AI, and batch jobs on any cloud, offering maximum cost savings, highest GPU availability, and managed execution. SkyPilot abstracts away cloud infra burdens: - Launch jobs & clusters on any cloud - Easy scale-out: queue and run many jobs, automatically managed - Easy access to object stores (S3, GCS, R2) SkyPilot maximizes GPU availability for your jobs: * Provision in all zones/regions/clouds you have access to (the _Sky_), with automatic failover SkyPilot cuts your cloud costs: * Managed Spot: 3-6x cost savings using spot VMs, with auto-recovery from preemptions * Optimizer: 2x cost savings by auto-picking the cheapest VM/zone/region/cloud * Autostop: hands-free cleanup of idle clusters SkyPilot supports your existing GPU, TPU, and CPU workloads, with no code changes.

Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. It is designed to format your codebase for easy understanding by AI tools like Large Language Models (LLMs), Claude, ChatGPT, and Gemini. Repomix offers features such as AI optimization, token counting, simplicity in usage, customization options, Git awareness, and security-focused checks using Secretlint. It allows users to pack their entire repository or specific directories/files using glob patterns, and even supports processing remote Git repositories. The tool generates output in plain text, XML, or Markdown formats, with options for including/excluding files, removing comments, and performing security checks. Repomix also provides a global configuration option, custom instructions for AI context, and a security check feature to detect sensitive information in files.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

The 'gritlm' repository provides all materials for the paper Generative Representational Instruction Tuning. It includes code for inference, training, evaluation, and known issues related to the GritLM model. The repository also offers models for embedding and generation tasks, along with instructions on how to train and evaluate the models. Additionally, it contains visualizations, acknowledgements, and a citation for referencing the work.

This repository is a collection of papers on Tabular Large Language Models (LLMs) specialized for processing tabular data. It includes surveys, models, and applications related to table understanding tasks such as Table Question Answering, Table-to-Text, Text-to-SQL, and more. The repository categorizes the papers based on key ideas and provides insights into the advancements in using LLMs for processing diverse tables and fulfilling various tabular tasks based on natural language instructions.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and follows a process of embedding docs and queries, searching for top passages, creating summaries, scoring and selecting relevant summaries, putting summaries into prompt, and generating answers. Users can customize prompts and use various models for embeddings and LLMs. The tool can be used asynchronously and supports adding documents from paths, files, or URLs.

This repository provides an implementation of QA-MDT, integrating state-of-the-art models for music generation. It offers a Quality-Aware Masked Diffusion Transformer for enhanced music generation. The code is based on various repositories like AudioLDM, PixArt-alpha, MDT, AudioMAE, and Open-Sora. The implementation allows for training and fine-tuning the model with different strategies and datasets. The repository also includes instructions for preparing datasets in LMDB format and provides a script for creating a toy LMDB dataset. The model can be used for music generation tasks, with a focus on quality injection to enhance the musicality of generated music.

OpenMusic is a repository providing an implementation of QA-MDT, a Quality-Aware Masked Diffusion Transformer for music generation. The code integrates state-of-the-art models and offers training strategies for music generation. The repository includes implementations of AudioLDM, PixArt-alpha, MDT, AudioMAE, and Open-Sora. Users can train or fine-tune the model using different strategies and datasets. The model is well-pretrained and can be used for music generation tasks. The repository also includes instructions for preparing datasets, training the model, and performing inference. Contact information is provided for any questions or suggestions regarding the project.

I'm a fun music guessing game helper, picking random songs for you!

I'm Mystery Wordster, your witty, category-picking game host!

An agent to help you create beautiful images with methodology for AI marketplaces like Adobe Stock and by helping you in the process of picking a Category and help brainstorming and prompting,

Your motorcycle journey planner, from routes to packing.

Travel expert offering advice on travel, travel insurance, packing, and ticket buying. Contact: [email protected]

Going on or planning a business trip to Riyadh and don't know what to do to prepare? or how to start?I can help you out!Type help for more commands