Best AI tools for< Recycling Facility Manager >

Greyparrot provides AI-powered waste analytics solutions for recycling facilities and packaging companies. Their AI waste analytics platform, Greyparrot Analyzer, uses cameras to track materials passing on conveyor belts and translates images into real-time insights on a live dashboard. Greyparrot Sync connects that live data stream to existing or new hardware and software. Greyparrot's AI identifies all of the waste objects found in global municipal recovery sites, with 67 waste categories and counting. Their AI waste analytics enable automation in sorting facilities and increase transparency at each stage of the global value chain.

EcoSnap is an AI tool designed to help users recycle plastic more effectively. By simply taking a picture of a plastic code, users can learn how to recycle the item properly. The tool aims to promote environmental sustainability by providing accurate recycling information based on artificial intelligence technology. EcoSnap is user-friendly and accessible, making it convenient for individuals looking to contribute to a greener planet.

AMP Smart Sortation™ is the waste sortation industry's permanent solution. As the leader in AI-powered sortation, AMP gives waste and recycling leaders the power to reduce labor costs, increase resource recovery, and deliver more reliable operations. AMP's AI-powered automation allows real-time material characterization and configuration to capture the most value from any material stream.

AMP Smart Sortation™ is waste sortation's permanent solution. As the leader in AI-powered sortation, we give waste and recycling leaders the power to reduce labor costs, increase resource recovery, and deliver more reliable operations. AMP's AI-powered automation allows real-time material characterization and configuration to capture the most value from any material stream.

Swapper is a peer-to-peer fashion marketplace where users can buy, sell, and swap pre-owned clothing items. The platform aims to promote sustainable fashion practices by encouraging the reuse and recycling of clothing. Users can create listings for their items, browse through a wide selection of clothing, and connect with other fashion enthusiasts. Swapper provides a convenient and eco-friendly way for individuals to refresh their wardrobe without contributing to fast fashion's negative environmental impact.

SummarAIze is an AI tool designed to help users repurpose content from podcasts or videos into engaging and shareable social posts, email content, summaries, quotes, and more. It uses AI technology to convert audio and video files into various types of content to support marketing channels, saving time and effort in content creation. With features like content recycling, content repurposing without manual work, and multiple content types generation, SummarAIze aims to help users 10X their content production and reach a wider audience.

Buckets is an AI-powered relationship management platform designed to transform networks from contacts to connections. In today's interconnected world, individuals face challenges in maintaining personal and business relationships due to the proliferation of social media and apps. Buckets offers features such as quick sharing of contact information, recalling contacts based on meeting details, and automating follow-ups without the need for physical cards. The platform aims to streamline networking processes and enhance relationship-building efforts.

Podwise is an AI-powered podcast tool designed for podcast lovers to extract structured knowledge from episodes at 10x speed. It offers features such as AI-powered summarization, mind mapping, content outlining, transcription, and seamless integration with knowledge management workflows. Users can subscribe to favorite content, get lightning-speed access to structured knowledge, and discover episodes of interest. Podwise aims to address the challenge of enjoying podcasts, recalling less, and forgetting quickly, by providing a meticulous, accurate, and impactful tool for efficient podcast referencing and note consolidation.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

Awesome-LLM-Inference: A curated list of 📙Awesome LLM Inference Papers with Codes, check 📖Contents for more details. This repo is still updated frequently ~ 👨‍💻‍ Welcome to star ⭐️ or submit a PR to this repo!

This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.

Bee is an ORM framework that provides easy and high-efficiency database operations, allowing developers to focus on business logic development. It supports various databases and features like automatic filtering, partial field queries, pagination, and JSON format results. Bee also offers advanced functionalities like sharding, transactions, complex queries, and MongoDB ORM. The tool is designed for rapid application development in Java, offering faster development for Java Web and Spring Cloud microservices. The Enterprise Edition provides additional features like financial computing support, automatic value insertion, desensitization, dictionary value conversion, multi-tenancy, and more.

Bee is an easy and high efficiency ORM framework that simplifies database operations by providing a simple interface and eliminating the need to write separate DAO code. It supports various features such as automatic filtering of properties, partial field queries, native statement pagination, JSON format results, sharding, multiple database support, and more. Bee also offers powerful functionalities like dynamic query conditions, transactions, complex queries, MongoDB ORM, cache management, and additional tools for generating distributed primary keys, reading Excel files, and more. The newest versions introduce enhancements like placeholder precompilation, default date sharding, ElasticSearch ORM support, and improved query capabilities.

Phi-3CookBook is a manual on how to use the Microsoft Phi-3 family, which consists of open AI models developed by Microsoft. The Phi-3 models are highly capable and cost-effective small language models, outperforming models of similar and larger sizes across various language, reasoning, coding, and math benchmarks. The repository provides detailed information on different Phi-3 models, their performance, availability, and usage scenarios across different platforms like Azure AI Studio, Hugging Face, and Ollama. It also covers topics such as fine-tuning, evaluation, and end-to-end samples for Phi-3-mini and Phi-3-vision models, along with labs, workshops, and contributing guidelines.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

Cherry Data Selection project introduces a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, minimizing manual curation and cost for instruction tuning. The project focuses on selecting impactful training samples ('cherry data') to enhance LLM instruction tuning by estimating instruction-following difficulty. The method involves phases like 'Learning from Brief Experience', 'Evaluating Based on Experience', and 'Retraining from Self-Guided Experience' to improve LLM performance.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

TTS Generation WebUI is a comprehensive tool that provides a user-friendly interface for text-to-speech and voice cloning tasks. It integrates various AI models such as Bark, MusicGen, AudioGen, Tortoise, RVC, Vocos, Demucs, SeamlessM4T, and MAGNeT. The tool offers one-click installers, Google Colab demo, videos for guidance, and extra voices for Bark. Users can generate audio outputs, manage models, caches, and system space for AI projects. The project is open-source and emphasizes ethical and responsible use of AI technology.

Nerve is a tool that allows creating stateful agents with any LLM of your choice without writing code. It provides a framework of functionalities for planning, saving, or recalling memories by dynamically adapting the prompt. Nerve is experimental and subject to changes. It is valuable for learning and experimenting but not recommended for production environments. The tool aims to instrument smart agents without code, inspired by projects like Dreadnode's Rigging framework.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

Kheish is an open-source, multi-role agent designed for complex tasks that require structured, step-by-step collaboration with Large Language Models (LLMs). It acts as an intelligent agent that can request modules on demand, integrate user feedback, switch between specialized roles, and deliver refined results. By harnessing multiple 'sub-agents' within one framework, Kheish tackles tasks like security audits, file searches, RAG-based exploration, and more.

This repository contains Python scripts that enable two-way voice conversations with Anthropic Claude, utilizing ElevenLabs for text-to-speech, Faster-Whisper for speech-to-text, and Pygame for audio playback. The tool operates by transcribing human audio using Faster-Whisper, sending the transcription to Anthropic Claude for response generation, and converting the LLM's response into audio using ElevenLabs. The audio is then played back through Pygame, allowing for a seamless and interactive conversation between the user and the AI. The repository includes variations of the main script to support different operating systems and configurations, such as using CPU transcription on Linux or employing the AssemblyAI API instead of Faster-Whisper.

HuixiangDou is a **group chat** assistant based on LLM (Large Language Model). Advantages: 1. Design a two-stage pipeline of rejection and response to cope with group chat scenario, answer user questions without message flooding, see arxiv2401.08772 2. Low cost, requiring only 1.5GB memory and no need for training 3. Offers a complete suite of Web, Android, and pipeline source code, which is industrial-grade and commercially viable Check out the scenes in which HuixiangDou are running and join WeChat Group to try AI assistant inside. If this helps you, please give it a star ⭐

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

Recycling assistant using image recognition to advise on recyclability.

Expert on global waste management and recycling data

Expert in waste management, recycling, and eco-friendly practices.

Offers strategies for waste reduction, recycling programs, and sustainable waste management practices.

Expert en recyclage, blockchain et modèles économiques coopératifs

Waste expert with witty, lightly condescending tone; more German.

I turn your waste into wonders with ideas, steps, pictures.

Your go-to guide for scrap metal pricing and tips.

Votre guide de tri des déchets pour Namur.

Moim zadaniem jest promowanie świadomości i angażowanie użytkowników w konkretne działania, które przyczyniają się do ochrony środowiska naturalnego.

Oarai's expert on waste sorting and weather.

Your guide to the environment and reducing carbon footprints.

Aide in recalling and piecing together memories.

I assist in recalling that elusive word or name at the tip of your tongue.

Friendly assistant for storing/recalling personal memories.