Best AI tools for< Reduce Waste Generation >

Toolpath is an AI-powered CAM automation tool for CNC machining. It analyzes parts for machinability, estimates costs, plans machining strategies, and generates CAM programs for Autodesk Fusion. The tool utilizes AI to optimize toolpaths and increase CNC machining productivity. Toolpath simplifies workflow by automating setup and toolpath generation, allowing users to focus on machining. It offers intelligent estimating, seamless CAM integration, and design for manufacturing capabilities. Designed by machinists, Toolpath aims to help both new and experienced users save time, reduce waste, and enhance productivity in the field of CNC machining.

LittleCook is a web and mobile application that helps users reduce food waste and save money by providing recipes based on the ingredients they already have on hand. The app also allows users to track their food inventory, plan their meals, and learn about nutrition. LittleCook is a valuable tool for anyone who wants to cook more efficiently and sustainably.

Flavorish is an AI-powered cooking assistant that helps users create delicious meals with ease. It offers a range of features to simplify the cooking process, including AI-powered recipe generation, smart shopping lists, recipe storage, and offline mode. With Flavorish, users can save time, reduce food waste, and explore new cuisines with confidence.

The Value Chain Generator® is an AI & Big Data platform for circular bioeconomy that helps companies, waste processors, and regions maximize the value and minimize the carbon footprint of by-products and waste. It uses global techno-economic and climate intelligence to identify circular opportunities, match with suitable partners and technologies, and create profitable and impactful solutions. The platform accelerates the circular transition by integrating local industries through technology, reducing waste, and increasing profits.

AI Recipe Generator is a user-friendly tool that helps you create delicious meals using ingredients you already have at home. With just a few clicks, you can generate a unique recipe tailored to your preferences and dietary restrictions. The AI-powered algorithm analyzes your ingredients and suggests recipes that are both tasty and nutritious.

RecipeGen AI is an AI-powered application that helps users discover delicious recipes based on the ingredients they already have. It offers personalized recipes tailored to individual preferences, reducing food waste and enhancing creativity in cooking. With a variety of chefs and ingredients to choose from, RecipeGen AI simplifies the recipe search process and saves time in meal planning.

Crumb is an AI food generator application that helps users create unique and delicious recipes by transforming their available ingredients. Users can simply dictate their ingredients to the AI tool, which then generates recipes to inspire everyday cooking and reduce food waste. With a variety of recipe ideas and tips available on the blog, Crumb aims to make cooking more creative and convenient for users.

ScrappyChef is an AI-powered application that helps users turn leftovers into creative meals. The platform offers a variety of recipes and meal ideas based on the ingredients available to the user. By utilizing artificial intelligence, ScrappyChef provides personalized suggestions and recommendations to make cooking more efficient and enjoyable. Users can subscribe to access more recipes and take advantage of the platform's innovative features.

Neurala is a company that provides visual quality inspection software powered by AI. Their software is designed to help manufacturers improve their inspection process by reducing product defects, increasing inspection rates, and preventing production downtime. Neurala's software is flexible and can be easily retrofitted into existing production line infrastructure, without the need for AI experts or expensive capital expenditures. The company's software is used by a variety of manufacturers, including Sony, AITRIOS, and CB Insights.

Inpulse.ai is an AI platform that revolutionizes inventory management and supplier ordering for restaurant chains. It assists managers in making informed decisions by accurately forecasting sales, anticipating production needs, and optimizing food supplies. The platform provides real-time performance monitoring, automated production planning, and centralized data management to help restaurants improve their margins and reduce waste. Inpulse.ai is used by over 3,000 restaurants, food kiosks, and bakeries on a daily basis, offering a comprehensive solution to streamline operations and boost profitability.

Fridge Leftovers AI is an innovative application that helps users transform their leftover ingredients into delicious meals. By utilizing cutting-edge AI technology, the app provides personalized recipe suggestions based on the ingredients available in the user's fridge. With a user-friendly interface and a focus on reducing food waste, Fridge Leftovers AI aims to simplify meal planning and inspire creativity in the kitchen.

Recipe Reactor is the ultimate kitchen companion that helps users unlock the full potential of their kitchen. It allows users to import, organize, plan meals, and explore new culinary horizons. With AI-powered recipe creation, effortless recipe importing, and comprehensive recipe management, Recipe Reactor simplifies, innovates, and masters the culinary world. Users can turn random ingredients into culinary masterpieces, reduce food waste, and enrich their cooking experience with educational insights.

Nanotronics is an AI-powered platform for autonomous manufacturing that revolutionizes the industry through automated optical inspection solutions. It combines computer vision, AI, and optical microscopy to ensure high-volume production with higher yields, less waste, and lower costs. Nanotronics offers products like nSpec and nControl, leading the paradigm shift in process control and transforming the entire manufacturing stack. With over 150 patents, 250+ deployments, and offices in multiple locations, Nanotronics is at the forefront of innovation in the manufacturing sector.

PWI is a company that partners with innovators to bring world-changing ideas to life through expert supply chain management and product development services. They are committed to reducing plastic waste and promoting eco-friendly alternatives, offering services such as new product development, sourcing of components, and contract manufacturing. PWI helps businesses create sustainable products and aims to have a positive impact on society and the environment.

ScanMyKitchen is an AI-powered application designed to help users create delicious meals using ingredients from their fridge. The app offers a variety of traditional and AI-powered recipe suggestions, customizable filters based on diet preferences, and alternative recipes for flexibility. Users can also utilize the camera scanning feature to scan ingredients and access recipe text or video tutorials. The mission of ScanMyKitchen is to inspire users to cook delicious meals, reduce food waste, save money, and benefit the planet. The app aims to simplify the cooking process and provide a seamless experience for users without the need for sign-ups.

Recipe Lens is an AI-powered platform that revolutionizes cooking by transforming photos and ingredients into culinary masterpieces. It offers advanced image recognition to identify dishes from photos and create custom recipes based on available ingredients. The application generates personalized recipes, provides detailed cooking instructions, nutritional information, and video tutorials. Recipe Lens aims to inspire creativity, simplify meal preparation, and empower users to discover new dishes while making the most out of their ingredients.

Wholesum is a group menu planning and shopping list tool that helps users save time, money, and reduce food waste. It allows users to easily adjust for dietary restrictions, group size, and duration. Wholesum also generates shopping lists and provides AI-powered recipes. With Wholesum, users can create sharable meal plans, estimate costs, and organize their meals by date and category.

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.

cloudNito is an AI-driven platform that specializes in cloud cost optimization and management for businesses using AWS services. The platform offers automated cost optimization, comprehensive insights and analytics, unified cloud management, anomaly detection, cost and usage explorer, recommendations for waste reduction, and resource optimization. By leveraging advanced AI solutions, cloudNito aims to help businesses efficiently manage their AWS cloud resources, reduce costs, and enhance performance.

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework known for its lightweight design, scalability, and high-speed performance. It offers features like tri-process asynchronous collaboration, Nopad for efficient attention operations, dynamic batch scheduling, FlashAttention integration, tensor parallelism, Token Attention for zero memory waste, and Int8KV Cache. The tool supports various models like BLOOM, LLaMA, StarCoder, Qwen-7b, ChatGLM2-6b, Baichuan-7b, Baichuan2-7b, Baichuan2-13b, InternLM-7b, Yi-34b, Qwen-VL, Llava-7b, Mixtral, Stablelm, and MiniCPM. Users can deploy and query models using the provided server launch commands and interact with multimodal models like QWen-VL and Llava using specific queries and images.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

This repository contains a library for constraining LLM generation to structured output, enforcing a JSON schema for precise data types and property names. It includes an acceptor/state machine framework, JSON acceptor, and JSON schema acceptor for guiding decoding in LLMs. The library provides reference implementations using Apple's MLX library and examples for function calling tasks. The tool aims to improve LLM output quality by ensuring adherence to a schema, reducing unnecessary output, and enhancing performance through pre-emptive decoding. Evaluations show performance benchmarks and comparisons with and without schema constraints.

VedAstro is an open-source Vedic astrology tool that provides accurate astrological predictions and data. It offers a user-friendly website, a chat API, an open API, a JavaScript SDK, a Swiss Ephemeris API, and a machine learning table generator. VedAstro is free to use and is constantly being updated with new features and improvements.

Extension | OS is an open-source browser extension that brings AI directly to users' web browsers, allowing them to access powerful models like LLMs seamlessly. Users can create prompts, fix grammar, and access intelligent assistance without switching tabs. The extension aims to revolutionize online information interaction by integrating AI into everyday browsing experiences. It offers features like Prompt Factory for tailored prompts, seamless LLM model access, secure API key storage, and a Mixture of Agents feature. The extension was developed to empower users to unleash their creativity with custom prompts and enhance their browsing experience with intelligent assistance.

Lobe Icons is a collection of popular AI / LLM Model Brand SVG logos and icons. It features lightweight and scalable icons designed with highly optimized scalable vector graphics (SVG) for optimal performance. The collection is tree-shakable, allowing users to import only the icons they need to reduce the overall bundle size of their projects. Lobe Icons has an active community of designers and developers who can contribute and seek support on platforms like GitHub and Discord. The repository supports a wide range of brands across different models, providers, and applications, with more brands continuously being added through contributions. Users can easily install Lobe UI with the provided commands and integrate it with NextJS for server-side rendering. Local development can be done using Github Codespaces or by cloning the repository. Contributions are welcome, and users can contribute code by checking out the GitHub Issues. The project is MIT licensed and maintained by LobeHub.

Baal is an active learning library that supports both industrial applications and research use cases. It provides a framework for Bayesian active learning methods such as Monte-Carlo Dropout, MCDropConnect, Deep ensembles, and Semi-supervised learning. Baal helps in labeling the most uncertain items in the dataset pool to improve model performance and reduce annotation effort. The library is actively maintained by a dedicated team and has been used in various research papers for production and experimentation.

Voicechat2 is a fast, fully local AI voice chat tool that uses WebSockets for communication. It includes a WebSocket server for remote access, default web UI with VAD and Opus support, and modular/swappable SRT, LLM, TTS servers. Users can customize components like SRT, LLM, and TTS servers, and run different models for voice-to-voice communication. The tool aims to reduce latency in voice communication and provides flexibility in server configurations.

Consistency Large Language Models (CLLMs) is a family of efficient parallel decoders that reduce inference latency by efficiently decoding multiple tokens in parallel. The models are trained to perform efficient Jacobi decoding, mapping any randomly initialized token sequence to the same result as auto-regressive decoding in as few steps as possible. CLLMs have shown significant improvements in generation speed on various tasks, achieving up to 3.4 times faster generation. The tool provides a seamless integration with other techniques for efficient Large Language Model (LLM) inference, without the need for draft models or architectural modifications.

This repository contains codes related to Generative AI as per YouTube video. It includes various notebooks and files for different days covering topics like map reduce, text to SQL, LLM parameters, tagging, and Kaggle competition. The repository also includes resources like PDF files and databases for different projects related to Generative AI.

MaskLLM is a learnable pruning method that establishes Semi-structured Sparsity in Large Language Models (LLMs) to reduce computational overhead during inference. It is scalable and benefits from larger training datasets. The tool provides examples for running MaskLLM with Megatron-LM, preparing LLaMA checkpoints, pre-tokenizing C4 data for Megatron, generating prior masks, training MaskLLM, and evaluating the model. It also includes instructions for exporting sparse models to Huggingface.

AutoGPTQ is an easy-to-use LLM quantization package with user-friendly APIs, based on GPTQ algorithm (weight-only quantization). It provides a simple and efficient way to quantize large language models (LLMs) to reduce their size and computational cost while maintaining their performance. AutoGPTQ supports a wide range of LLM models, including GPT-2, GPT-J, OPT, and BLOOM. It also supports various evaluation tasks, such as language modeling, sequence classification, and text summarization. With AutoGPTQ, users can easily quantize their LLM models and deploy them on resource-constrained devices, such as mobile phones and embedded systems.

This repository contains an implementation of Ring Attention, a technique for processing large sequences in transformers. Ring Attention splits the data across the sequence dimension and applies ring reduce to the processing of the tiles of the attention matrix, similar to flash attention. It also includes support for Striped Attention, a follow-up paper that permutes the sequence for better workload balancing for autoregressive transformers, and grouped query attention, which saves on communication costs during the ring reduce. The repository includes a CUDA version of the flash attention kernel, which is used for the forward and backward passes of the ring attention. It also includes logic for splitting the sequence evenly among ranks, either within the attention function or in the external ring transformer wrapper, and basic test cases with two processes to check for equivalent output and gradients.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project caches pre-generated model results to reduce response time for similar requests and enhance user experience. It integrates various embedding frameworks and local storage options, offering functionalities like cache-writing, cache-querying, and cache-clearing through RESTful API. The tool supports multi-tenancy, system commands, and multi-turn dialogue, with features for data isolation, database management, and model loading schemes. Future developments include data isolation based on hyperparameters, enhanced system prompt partitioning storage, and more versatile embedding models and similarity evaluation algorithms.

This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.

llmc is an off-the-shell tool designed for compressing LLM, leveraging state-of-the-art compression algorithms to enhance efficiency and reduce model size without compromising performance. It provides users with the ability to quantize LLMs, choose from various compression algorithms, export transformed models for further optimization, and directly infer compressed models with a shallow memory footprint. The tool supports a range of model types and quantization algorithms, with ongoing development to include pruning techniques. Users can design their configurations for quantization and evaluation, with documentation and examples planned for future updates. llmc is a valuable resource for researchers working on post-training quantization of large language models.

The NVIDIA TensorRT Model Optimizer is a library designed to quantize and compress deep learning models for optimized inference on GPUs. It offers state-of-the-art model optimization techniques including quantization and sparsity to reduce inference costs for generative AI models. Users can easily stack different optimization techniques to produce quantized checkpoints from torch or ONNX models. The quantized checkpoints are ready for deployment in inference frameworks like TensorRT-LLM or TensorRT, with planned integrations for NVIDIA NeMo and Megatron-LM. The tool also supports 8-bit quantization with Stable Diffusion for enterprise users on NVIDIA NIM. Model Optimizer is available for free on NVIDIA PyPI, and this repository serves as a platform for sharing examples, GPU-optimized recipes, and collecting community feedback.

Informative guide on industrial waste management and environmental impact.

A magical kitchen assistant turning fridge contents into recipes.

The Ultimate Recipe Generator: Personalized creations for the discerning chef!

It generates a recipe by entering the ingredients you have via text or by uploading an image. 家にある材料を入力したり、画像をアップロードすることでレシピを教えてくれます。

Improves operational efficiency by optimizing processes and reducing waste.

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

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

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

Votre guide de tri des déchets pour Namur.

AI sustainability coach for eco-friendly living and learning.

Recycling assistant using image recognition to advise on recyclability.

An informative guide on composting and its environmental benefits.

Friendly guide on sustainable living with accurate info.

Informative guide on bulk buying, highlighting benefits and cost-effective tips.

Optimizes production processes for improved efficiency and quality.

Optimizes manufacturing processes for efficiency and quality.

Guiding users in Six Sigma application.

Your guide to an eco-friendly lifestyle, offering sustainable tips and green solutions.

A friendly conservationist who helps find easy, eco-friendly solutions for day-to-day living.

Assists in developing a visual inventory management app.