Best AI tools for< Reduce Plastic Use >

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.

Pongo is an AI-powered tool that helps reduce hallucinations in Large Language Models (LLMs) by up to 80%. It utilizes multiple state-of-the-art semantic similarity models and a proprietary ranking algorithm to ensure accurate and relevant search results. Pongo integrates seamlessly with existing pipelines, whether using a vector database or Elasticsearch, and processes top search results to deliver refined and reliable information. Its distributed architecture ensures consistent latency, handling a wide range of requests without compromising speed. Pongo prioritizes data security, operating at runtime with zero data retention and no data leaving its secure AWS VPC.

DailyBot is an AI-powered toolkit for teams that want automation, better reporting, and customization. It offers a range of features to enhance team visibility, reduce meetings, and improve collaboration. With DailyBot, teams can run asynchronous standups, retros, and other meetings, send kudos and recognition, create surveys and collect data, and access a variety of add-ons like watercoolers and random coffees. DailyBot also integrates with popular tools like Zapier, Jira, and Trello, making it easy to connect with the tools teams already use. Trusted by leading companies and backed by Y Combinator, DailyBot is a valuable tool for teams looking to improve their collaboration and productivity.

Nametag is an identity verification solution designed specifically for IT helpdesks. It helps businesses prevent social engineering attacks, account takeovers, and data breaches by verifying the identity of users at critical moments, such as password resets, MFA resets, and high-risk transactions. Nametag's unique approach to identity verification combines mobile cryptography, device telemetry, and proprietary AI models to provide unmatched security and better user experiences.

SentinelOne is an advanced enterprise cybersecurity AI platform that offers a comprehensive suite of AI-powered security solutions for endpoint, cloud, and identity protection. The platform leverages AI technology to anticipate threats, manage vulnerabilities, and protect resources across the enterprise ecosystem. SentinelOne provides real-time threat hunting, managed services, and actionable insights through its unified data lake, empowering security teams to respond effectively to cyber threats. With a focus on automation, efficiency, and value maximization, SentinelOne is a trusted cybersecurity solution for leading enterprises worldwide.

Codimite is an AI-assisted offshore development company that provides a range of services to help businesses accelerate their software development, reduce costs, and drive innovation. Codimite's team of experienced engineers and project managers use AI-powered tools and technologies to deliver exceptional results for their clients. The company's services include AI-assisted software development, cloud modernization, and data and artificial intelligence solutions.

SentinelOne is an advanced enterprise cybersecurity AI platform that offers a comprehensive suite of AI-powered security solutions for endpoint, cloud, and identity protection. The platform leverages artificial intelligence to anticipate threats, manage vulnerabilities, and protect resources across the entire enterprise ecosystem. With features such as Singularity XDR, Purple AI, and AI-SIEM, SentinelOne empowers security teams to detect and respond to cyber threats in real-time. The platform is trusted by leading enterprises worldwide and has received industry recognition for its innovative approach to cybersecurity.

SnapMeasureAI is an AI-powered application that provides 99% accurate body measurements without the need to visit a tailor. It uses advanced AI technology to analyze body shapes and measurements from photos or videos, offering unparalleled precision and reliability. The application aims to reduce returns, save costs, and increase shopping confidence by ensuring a perfect fit for users. SnapMeasureAI is designed to accommodate any body type, skin tone, pose, or background, making it a versatile and user-friendly tool for personalized body measurements.

Video Highlight is an AI-powered tool that helps you summarize and take notes from videos. It uses the latest AI technology to generate timestamped summaries and transcripts, highlight key moments, and engage in interactive chats. With Video Highlight, you can save hours of research time and focus on exploring, analyzing, and absorbing content.

Hypergro is an AI-powered platform that specializes in UGC video ads for smart customer acquisition. Leveraging the 4th Generation of AI-powered growth marketing on Meta and Youtube, Hypergro helps businesses discover their audience, drive sales, and increase revenue through real-time AI insights. The platform offers end-to-end solutions for creating impactful short video ads that combine creator authenticity with AI-driven research for compelling storytelling. With a focus on precision targeting, competitor analysis, and in-depth research, Hypergro ensures maximum ROI for brands looking to elevate their growth strategies.

hirex.ai is an AI tool designed to make job interviews open, fair, and accessible for all. The platform offers the GenAI assistant to help users get interviewed instantly and jump the line to secure their dream job. With no credit card required, users can register for free early access and benefit from faster screening processes by interviewing candidates using the GenAI assistant. The website aims to transform HR and talent acquisition by providing innovative solutions for job seekers and employers.

Beebzi.AI is an all-in-one AI content creation platform that offers a wide array of tools for generating various types of content such as articles, blogs, emails, images, voiceovers, and more. The platform utilizes advanced AI technology and behavioral science to empower businesses and individuals in their marketing and sales endeavors. With features like AI Article Wizard, AI Room Designer, AI Landing Page Generator, and AI Code Generation, Beebzi.AI revolutionizes content creation by providing customizable templates, multiple language support, and real-time data insights. The platform also offers various subscription plans tailored for individual entrepreneurs, teams, and businesses, with flexible pricing models based on word count allocations. Beebzi.AI aims to streamline content creation processes, enhance productivity, and drive organic traffic through SEO-optimized content.

Parasoft is an intelligent automated testing and quality platform that offers a range of tools covering every stage of the software development lifecycle. It provides solutions for compliance standards, automated software testing, and various industries' needs. Parasoft helps users accelerate software delivery, ensure quality, and comply with safety and security standards.

LiveChatAI is an AI chatbot application that works with your data to provide interactive and personalized customer support solutions. It blends AI and human support to deliver dynamic and accurate responses, improving customer satisfaction and reducing support volume. With features like AI Actions, custom question & answers, and content import, LiveChatAI offers a seamless integration for businesses across various platforms and languages. The application is designed to be user-friendly, requiring no AI expertise, and offers instant localization in 95 languages.

GrapixAI is a leading provider of low-cost cloud GPU rental services and AI server solutions. The company's focus on flexibility, scalability, and cutting-edge technology enables a variety of AI applications in both local and cloud environments. GrapixAI offers the lowest prices for on-demand GPUs such as RTX4090, RTX 3090, RTX A6000, RTX A5000, and A40. The platform provides Docker-based container ecosystem for quick software setup, powerful GPU search console, customizable pricing options, various security levels, GUI and CLI interfaces, real-time bidding system, and personalized customer support.

Sprockets is an AI-powered hiring software designed to help businesses overcome today's unique hiring challenges. It automates manual tasks, reduces employee turnover, and helps businesses hire the best workers every time. Sprockets offers a range of features, including a virtual recruiter, sourcing, screening, applicant tracking, reporting, time to hire, background checks, and tax credits. It also integrates with a variety of other HR systems, making it easy to use alongside your existing tools. With Sprockets, businesses can improve their hiring process, save time and money, and find the best talent for their open positions.

Fraud.net is an AI-powered fraud detection and prevention platform designed for enterprises. It offers a comprehensive and customizable solution to manage and prevent various types of fraud, such as account takeover, application fraud, and payment fraud. The platform utilizes AI and machine learning technologies to provide real-time monitoring, analytics, and reporting, helping businesses reduce fraud losses and improve customer trust. Fraud.net is trusted by various industries, including financial services, e-commerce, gaming, government, and insurance, to combat fraud schemes and ensure secure transactions.

ASK BOSCO® is an AI reporting and forecasting tool designed for agencies and retailers. It connects and consolidates data for easy reporting, predicts media spend allocation, plans budgets, and forecasts future performance with 96% accuracy. The tool combines internal marketing data with algorithmic modeling to create personalized reporting dashboards, enabling data-driven marketing decisions and insights. ASK BOSCO® is trusted by leading brands and agencies, offering statistical modeling and machine learning for media budget planning and benchmarking against competitors.

CodexAtlas is an AI-powered tool designed to automate code documentation processes. It leverages the latest advancements in Artificial Intelligence to generate and maintain documentation for software projects, freeing developers from the time-consuming task of writing documentation. With features like real-time updates, onboarding time reduction, and use-case detection, CodexAtlas aims to streamline the documentation process and enhance developer productivity. The tool also offers code conversion capabilities, business domain knowledge integration, and the option for on-premise deployment to cater to diverse organizational needs.

GoCharlie is a leading Generative AI company specializing in developing cognitive agents and models optimized for businesses. Its AI technology enables professionals and businesses to amplify their productivity and create high-performing content tailored to their needs. GoCharlie's AI assistant, Charlie, automates repetitive tasks, allowing teams to focus on more strategic and creative work. It offers a suite of proprietary LLM and multimodal models, a Memory Vault to build an AI Brain for businesses, and Agent AI to deliver the full power of AI to operations. GoCharlie can automate mundane tasks, drive complex workflows, and facilitate instant, precise data retrieval.

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.

RLAIF-V is a novel framework that aligns MLLMs in a fully open-source paradigm for super GPT-4V trustworthiness. It maximally exploits open-source feedback from high-quality feedback data and online feedback learning algorithm. Notable features include achieving super GPT-4V trustworthiness in both generative and discriminative tasks, using high-quality generalizable feedback data to reduce hallucination of different MLLMs, and exhibiting better learning efficiency and higher performance through iterative alignment.

RouteLLM is a framework for serving and evaluating LLM routers. It allows users to launch an OpenAI-compatible API that routes requests to the best model based on cost thresholds. Trained routers are provided to reduce costs while maintaining performance. Users can easily extend the framework, compare router performance, and calibrate cost thresholds. RouteLLM supports multiple routing strategies and benchmarks, offering a lightweight server and evaluation framework. It enables users to evaluate routers on benchmarks, calibrate thresholds, and modify model pairs. Contributions for adding new routers and benchmarks are welcome.

RTL-Coder is a tool designed to outperform GPT-3.5 in RTL code generation by providing a fully open-source dataset and a lightweight solution. It targets Verilog code generation and offers an automated flow to generate a large labeled dataset with over 27,000 diverse Verilog design problems and answers. The tool addresses the data availability challenge in IC design-related tasks and can be used for various applications beyond LLMs. The tool includes four RTL code generation models available on the HuggingFace platform, each with specific features and performance characteristics. Additionally, RTL-Coder introduces a new LLM training scheme based on code quality feedback to further enhance model performance and reduce GPU memory consumption.

ResumeFlow is an automated system utilizing Large Language Models (LLMs) to streamline the job application process. It aims to reduce human effort in various steps of job hunting by integrating LLM technology. Users can access ResumeFlow as a web tool, install it as a Python package, or download the source code. The project focuses on leveraging LLMs to automate tasks such as resume generation and refinement, making job applications smoother and more efficient.

HaE is a framework project in the field of network security (data security) that combines artificial intelligence (AI) large models to achieve highlighting and information extraction of HTTP messages (including WebSocket). It aims to reduce testing time, focus on valuable and meaningful messages, and improve vulnerability discovery efficiency. The project provides a clear and visual interface design, simple interface interaction, and centralized data panel for querying and extracting information. It also features built-in color upgrade algorithm, one-click export/import of data, and integration of AI large models API for optimized data processing.

Acte is a framework designed to build GUI-like tools for AI Agents. It aims to address the issues of cognitive load and freedom degrees when interacting with multiple APIs in complex scenarios. By providing a graphical user interface (GUI) for Agents, Acte helps reduce cognitive load and constraints interaction, similar to how humans interact with computers through GUIs. The tool offers APIs for starting new sessions, executing actions, and displaying screens, accessible via HTTP requests or the SessionManager class.

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 facilitates sharing and exchanging technologies related to large model semantic cache through open-source collaboration.

Starmoon is an affordable, compact AI-enabled device that can understand and respond to your emotions with empathy. It offers supportive conversations and personalized learning assistance. The device is cost-effective, voice-enabled, open-source, compact, and aims to reduce screen time. Users can assemble the device themselves using off-the-shelf components and deploy it locally for data privacy. Starmoon integrates various APIs for AI language models, speech-to-text, text-to-speech, and emotion intelligence. The hardware setup involves components like ESP32S3, microphone, amplifier, speaker, LED light, and button, along with software setup instructions for developers. The project also includes a web app, backend API, and background task dashboard for monitoring and management.

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