Best AI tools for< Optimize Weight Rounding >

Superblog is an AI-powered blogging platform that serves as the best alternative for WordPress and Medium blogs. It is designed to provide users with a hassle-free blogging experience by automatically optimizing for SEO, speed, and design. With features like AI Helper, auto image optimization, and real-time hints for content creation, Superblog aims to streamline the blogging process and enhance user experience. Trusted by unicorns and YC companies, Superblog offers a user-friendly interface, privacy-friendly analytics, and seamless integration with existing websites or apps.

Mealmind is an AI-powered meal planning and nutrition tracking application that helps users optimize their nutrition and achieve their health and fitness goals. It provides personalized meal plans, interactive shopping lists, and tailored recipes based on individual dietary requirements, food preferences, and body goals. The application leverages AI algorithms to analyze user profiles, goals, and dietary restrictions to generate customized meal plans that meet their specific needs. Mealmind also offers an interactive shopping list that simplifies grocery shopping by providing a tailored list of ingredients required for the meal plan. Additionally, the application includes a recipe section with step-by-step instructions to guide users through the cooking process, making it easy for individuals to prepare delicious and nutritious meals at home.

FitnessAI is an AI-powered fitness app that provides personalized workouts based on 5.9 million workouts. It uses artificial intelligence to optimize sets, reps, and weight for each exercise, making it easy for users to get stronger and faster. FitnessAI is simple to use, with a user-friendly interface and clear workout recommendations. It also tracks progress over time, so users can see how the algorithm is helping them improve. FitnessAI is a great option for anyone looking to get fit or improve their fitness routine.

January AI is a free health app that utilizes predictive AI technology to help users monitor their blood sugar levels and make informed decisions about their nutrition. The app provides real-time insights on the glucose impact of various foods, offers nutrition facts, and suggests healthier alternatives. Founded by Dr. Michael Snyder and Noosheen Hashemi, January AI combines metabolic science with groundbreaking AI to empower users to optimize their nutrition and manage their blood sugar levels effectively.

Webflow Optimize is an AI-powered website optimization and personalization tool that empowers users to create high-performing sites, analyze site performance, maximize conversions through testing and personalization, and connect their site to various apps. With features like rapid insights, tailored visitor experiences, AI-powered delivery, and personalized site experiences, Webflow Optimize helps users enhance their online presence and boost conversion rates. The platform also offers audience insights, audience targeting, and advanced targeting options for businesses of all sizes. Webflow Optimize is designed to streamline the optimization process and deliver customized experiences to visitors for increased engagement and conversion rates.

Qualtrics XM is a leading Experience Management Software that helps businesses optimize customer experiences, employee engagement, and market research. The platform leverages specialized AI to uncover insights from data, prioritize actions, and empower users to enhance customer and employee experience outcomes. Qualtrics XM offers solutions for Customer Experience, Employee Experience, Strategy & Research, and more, enabling organizations to drive growth and improve performance.

Jobscan is a comprehensive job search tool that helps job seekers optimize their resumes, cover letters, and LinkedIn profiles to increase their chances of getting interviews. It uses artificial intelligence and machine learning technology to analyze job descriptions and identify the skills and keywords that recruiters are looking for. Jobscan then provides personalized suggestions on how to tailor your application materials to each specific job you apply for. In addition to its resume and cover letter optimization tools, Jobscan also offers a job tracker, a LinkedIn optimization tool, and a career change tool. With its powerful suite of features, Jobscan is an essential tool for any job seeker who wants to land their dream job.

TestMarket is an AI-powered sales optimization platform for online marketplace sellers. It offers a range of services to help sellers increase their visibility, boost sales, and improve their overall performance on marketplaces such as Amazon, Etsy, and Walmart. TestMarket's services include product promotion, keyword analysis, Google Ads and SEO optimization, and advertising optimization.

VWO is a comprehensive experimentation platform that enables businesses to optimize their digital experiences and maximize conversions. With a suite of products designed for the entire optimization program, VWO empowers users to understand user behavior, validate optimization hypotheses, personalize experiences, and deliver tailored content and experiences to specific audience segments. VWO's platform is designed to be enterprise-ready and scalable, with top-notch features, strong security, easy accessibility, and excellent performance. Trusted by thousands of leading brands, VWO has helped businesses achieve impressive growth through experimentation loops that shape customer experience in a positive direction.

Botify AI is an AI-powered tool designed to assist users in optimizing their website's performance and search engine rankings. By leveraging advanced algorithms and machine learning capabilities, Botify AI provides valuable insights and recommendations to improve website visibility and drive organic traffic. Users can analyze various aspects of their website, such as content quality, site structure, and keyword optimization, to enhance overall SEO strategies. With Botify AI, users can make data-driven decisions to enhance their online presence and achieve better search engine results.

Siteimprove is an AI-powered platform that offers a comprehensive suite of digital governance, analytics, and SEO tools to help businesses optimize their online presence. It provides solutions for digital accessibility, quality assurance, content analytics, search engine marketing, and cross-channel advertising. With features like AI-powered insights, automated analysis, and machine learning capabilities, Siteimprove empowers users to enhance their website's reach, reputation, revenue, and returns. The platform transcends traditional boundaries by addressing a wide range of digital requirements and impact-drivers, making it a valuable tool for businesses looking to improve their online performance.

SiteSpect is an AI-driven platform that offers A/B testing, personalization, and optimization solutions for businesses. It provides capabilities such as analytics, visual editor, mobile support, and AI-driven product recommendations. SiteSpect helps businesses validate ideas, deliver personalized experiences, manage feature rollouts, and make data-driven decisions. With a focus on conversion and revenue success, SiteSpect caters to marketers, product managers, developers, network operations, retailers, and media & entertainment companies. The platform ensures faster site performance, better data accuracy, scalability, and expert support for secure and certified optimization.

EverSQL is an AI-powered tool designed for SQL query optimization, database observability, and cost reduction for PostgreSQL and MySQL databases. It automatically optimizes SQL queries using smart AI-based algorithms, provides ongoing performance insights, and helps reduce monthly database costs by offering optimization recommendations. With over 100,000 professionals trusting EverSQL, it aims to save time, improve database performance, and enhance cost-efficiency without accessing sensitive data.

Attention Insight is an AI-driven pre-launch analytics tool that provides crucial insights into consumer engagement with designs before the launch. By using predictive attention heatmaps and AI-generated attention analytics, users can optimize their concepts for better performance, validate designs, and improve user experience. The tool offers accurate data based on psychological research, helping users make informed decisions and save time and resources. Attention Insight is suitable for various types of analysis, including desktop, marketing material, mobile, posters, packaging, and shelves.

Competera is an AI-powered pricing platform designed for online and omnichannel retailers. It offers a unified workplace with an easy-to-use interface, real-time market data, and AI-powered product matching. Competera focuses on demand-based pricing, customer-centric pricing, and balancing price elasticity with competitive pricing. It provides granular pricing at the SKU level and offers a seamless adoption and onboarding process. The platform helps retailers optimize pricing strategies, increase margins, and save time on repricing.

Inventoro is a smart inventory forecasting and replenishment tool that helps businesses optimize their inventory management processes. By analyzing past sales data, the tool predicts future sales, recommends order quantities, reduces inventory size, identifies profitable inventory items, and ensures customer satisfaction by avoiding stockouts. Inventoro offers features such as sales forecasting, product segmentation, replenishment, system integration, and forecast automations. The tool is designed to help businesses decrease inventory, increase revenue, save time, and improve product availability. It is suitable for businesses of all sizes and industries looking to streamline their inventory management operations.

Vic.ai is an AI-powered accounting software designed to streamline invoice processing, purchase order matching, approval flows, payments, analytics, and insights. The platform offers autonomous finance solutions that optimize accounts payable processes, achieve lasting ROI, and enable informed decision-making. Vic.ai leverages AI technology to enhance productivity, accuracy, and efficiency in accounting workflows, reducing manual tasks and improving overall financial operations.

Paro is a professional business finance and accounting solutions platform that matches businesses and accounting firms with skilled finance experts. It offers a wide range of services including accounting, bookkeeping, financial planning, budgeting, business analysis, data visualization, strategic advisory, growth strategy consulting, startup and fundraising consulting, transaction advisory, tax and compliance services, AI consulting services, and more. Paro aims to help businesses optimize faster by providing expert solutions to bridge gaps in finance and accounting operations. The platform also offers staff augmentation services, talent acquisition, and custom solutions to enhance operational efficiency and maximize ROI.

Seventh Sense is an AI software designed to optimize email delivery times using artificial intelligence for HubSpot and Marketo users. It helps email marketers improve engagement and conversions by personalizing email delivery times based on individual recipient behavior. The tool aims to address the challenges of email marketing in today's competitive digital landscape by leveraging AI to increase deliverability, engagement, and conversions. Seventh Sense has been successful in helping hundreds of companies enhance their email marketing performance and stand out in crowded inboxes.

Rewatch is an AI-powered meeting assistant and video hub that helps users capture meetings, create summaries, transcriptions, and action items. It centralizes all meeting videos, notes, and discussions in one place, replacing repetitive in-person meetings with asynchronous collaborative series. Rewatch also offers features like screen recording, integrations with other tools, and conversation intelligence to empower organizations with actionable insights. Trusted by productive businesses, Rewatch aims to optimize necessary meetings, eliminate useless ones, and enhance cross-functional collaboration in a unified hub.

AutoRound is an advanced weight-only quantization algorithm for low-bits LLM inference. It competes impressively against recent methods without introducing any additional inference overhead. The method adopts sign gradient descent to fine-tune rounding values and minmax values of weights in just 200 steps, often significantly outperforming SignRound with the cost of more tuning time for quantization. AutoRound is tailored for a wide range of models and consistently delivers noticeable improvements.

Intel® Neural Compressor is an open-source Python library that supports popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet. It provides key features, typical examples, and open collaborations, including support for a wide range of Intel hardware, validation of popular LLMs, and collaboration with cloud marketplaces, software platforms, and open AI ecosystems.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

This repository, Awesome Efficient AIGC, collects efficient approaches for AI-generated content (AIGC) to cope with its huge demand for computing resources. It includes efficient Large Language Models (LLMs), Diffusion Models (DMs), and more. The repository is continuously improving and welcomes contributions of works like papers and repositories that are missed by the collection.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

This repo contains a comprehensive paper list of **Model Quantization** for efficient deep learning on AI conferences/journals/arXiv. As a highlight, we categorize the papers in terms of model structures and application scenarios, and label the quantization methods with keywords.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

AIMET is a library that provides advanced model quantization and compression techniques for trained neural network models. It provides features that have been proven to improve run-time performance of deep learning neural network models with lower compute and memory requirements and minimal impact to task accuracy. AIMET is designed to work with PyTorch, TensorFlow and ONNX models. We also host the AIMET Model Zoo - a collection of popular neural network models optimized for 8-bit inference. We also provide recipes for users to quantize floating point models using AIMET.

Efficient Foundation Model Survey is a comprehensive analysis of resource-efficient large language models (LLMs) and multimodal foundation models. The survey covers algorithmic and systemic innovations to support the growth of large models in a scalable and environmentally sustainable way. It explores cutting-edge model architectures, training/serving algorithms, and practical system designs. The goal is to provide insights on tackling resource challenges posed by large foundation models and inspire future breakthroughs in the field.

uTensor is an extremely light-weight machine learning inference framework built on Tensorflow and optimized for Arm targets. It consists of a runtime library and an offline tool that handles most of the model translation work. The core runtime is only ~2KB. The workflow involves constructing and training a model in Tensorflow, then using uTensor to produce C++ code for inferencing. The runtime ensures system safety, guarantees RAM usage, and focuses on clear, concise, and debuggable code. The high-level API simplifies tensor handling and operator execution for embedded systems.

APOLLO is a memory-efficient optimizer designed for large language model (LLM) pre-training and full-parameter fine-tuning. It offers SGD-like memory cost with AdamW-level performance. The optimizer integrates low-rank approximation and optimizer state redundancy reduction to achieve significant memory savings while maintaining or surpassing the performance of Adam(W). Key contributions include structured learning rate updates for LLM training, approximated channel-wise gradient scaling in a low-rank auxiliary space, and minimal-rank tensor-wise gradient scaling. APOLLO aims to optimize memory efficiency during training large language models.

llm-analysis is a tool designed for Latency and Memory Analysis of Transformer Models for Training and Inference. It automates the calculation of training or inference latency and memory usage for Large Language Models (LLMs) or Transformers based on specified model, GPU, data type, and parallelism configurations. The tool helps users to experiment with different setups theoretically, understand system performance, and optimize training/inference scenarios. It supports various parallelism schemes, communication methods, activation recomputation options, data types, and fine-tuning strategies. Users can integrate llm-analysis in their code using the `LLMAnalysis` class or use the provided entry point functions for command line interface. The tool provides lower-bound estimations of memory usage and latency, and aims to assist in achieving feasible and optimal setups for training or inference.

DuoAttention is a framework designed to optimize long-context large language models (LLMs) by reducing memory and latency during inference without compromising their long-context abilities. It introduces a concept of Retrieval Heads and Streaming Heads to efficiently manage attention across tokens. By applying a full Key and Value (KV) cache to retrieval heads and a lightweight, constant-length KV cache to streaming heads, DuoAttention achieves significant reductions in memory usage and decoding time for LLMs. The framework uses an optimization-based algorithm with synthetic data to accurately identify retrieval heads, enabling efficient inference with minimal accuracy loss compared to full attention. DuoAttention also supports quantization techniques for further memory optimization, allowing for decoding of up to 3.3 million tokens on a single GPU.

Atom is an accurate low-bit weight-activation quantization algorithm that combines mixed-precision, fine-grained group quantization, dynamic activation quantization, KV-cache quantization, and efficient CUDA kernels co-design. It introduces a low-bit quantization method, Atom, to maximize Large Language Models (LLMs) serving throughput with negligible accuracy loss. The codebase includes evaluation of perplexity and zero-shot accuracy, kernel benchmarking, and end-to-end evaluation. Atom significantly boosts serving throughput by using low-bit operators and reduces memory consumption via low-bit quantization.

PromptAgent is a repository for a novel automatic prompt optimization method that crafts expert-level prompts using language models. It provides a principled framework for prompt optimization by unifying prompt sampling and rewarding using MCTS algorithm. The tool supports different models like openai, palm, and huggingface models. Users can run PromptAgent to optimize prompts for specific tasks by strategically sampling model errors, generating error feedbacks, simulating future rewards, and searching for high-reward paths leading to expert prompts.

llmaz is an easy, advanced inference platform for large language models on Kubernetes. It aims to provide a production-ready solution that integrates with state-of-the-art inference backends. The platform supports efficient model distribution, accelerator fungibility, SOTA inference, various model providers, multi-host support, and scaling efficiency. Users can quickly deploy LLM services with minimal configurations and benefit from a wide range of advanced inference backends. llmaz is designed to optimize cost and performance while supporting cutting-edge researches like Speculative Decoding or Splitwise on Kubernetes.

PowerInfer is a high-speed Large Language Model (LLM) inference engine designed for local deployment on consumer-grade hardware, leveraging activation locality to optimize efficiency. It features a locality-centric design, hybrid CPU/GPU utilization, easy integration with popular ReLU-sparse models, and support for various platforms. PowerInfer achieves high speed with lower resource demands and is flexible for easy deployment and compatibility with existing models like Falcon-40B, Llama2 family, ProSparse Llama2 family, and Bamboo-7B.

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