Best AI tools for< Optimize Cache Performance >

imgix is an end-to-end visual media solution that enables users to create, transform, and optimize captivating images and videos for an unparalleled visual experience. It simplifies the complex visual media technology, improves web performance, and delivers responsive design. Trusted by innovative companies worldwide, imgix offers features such as easy cloud storage connection, intelligent compression, fast loading with a globally distributed CDN, over 150 image operations, video streaming, asset management, intuitive analytics, and powerful SDKs & tools.

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.

CEREBRUMX is an AI-powered platform that offers preventive car maintenance telematics solutions for various industries such as fleet management, vehicle service contracts, electric vehicles, smart cities, and media. The platform provides data insights and features like driver safety, EV charging, predictive maintenance, roadside assistance, and traffic flow management. CEREBRUMX aims to optimize fleet operations, enhance efficiency, and deliver high-value impact to customers through real-time connected vehicle data insights.

CloudEagle.ai is a modern SaaS procurement and management platform that offers AI/ML capabilities. It helps optimize SaaS stacks, manage contracts, streamline procurement workflows, and ensure cost savings by identifying unused licenses. The platform also assists in vendor research, renewal management, and automating provisioning processes. CloudEagle.ai is recognized for its AI/ML capabilities in the 2024 Gartner Magic Quadrant.

Sellozo is an AI-driven automation platform designed to optimize Amazon advertising and boost sales. It offers a range of features such as AI Technology, Dayparting, Campaign Studio, Autopilot Repricer, and more. Sellozo provides flat-fee pricing without long-term contracts, helping users increase ad profit by an average of 70%. The platform leverages AI to automate advertising strategies, lower costs, and maximize profits. With Campaign Studio, users can easily design and refine their PPC campaigns, while the full PPC management service allows businesses to focus on growth while Sellozo handles advertising. Powered by billions of transactions, Sellozo is a trusted platform for Amazon sellers seeking to enhance their advertising performance.

Mooncake is a serving platform for Kimi, a leading LLM service provided by Moonshot AI. It features a KVCache-centric disaggregated architecture that separates prefill and decoding clusters, leveraging underutilized CPU, DRAM, and SSD resources of the GPU cluster. Mooncake's scheduler balances throughput and latency-related SLOs, with a prediction-based early rejection policy for highly overloaded scenarios. It excels in long-context scenarios, achieving up to a 525% increase in throughput while handling 75% more requests under real workloads.

GLake is an acceleration library and utilities designed to optimize GPU memory management and IO transmission for AI large model training and inference. It addresses challenges such as GPU memory bottleneck and IO transmission bottleneck by providing efficient memory pooling, sharing, and tiering, as well as multi-path acceleration for CPU-GPU transmission. GLake is easy to use, open for extension, and focuses on improving training throughput, saving inference memory, and accelerating IO transmission. It offers features like memory fragmentation reduction, memory deduplication, and built-in security mechanisms for troubleshooting GPU memory issues.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

The RAG ChatBot project combines Lama.cpp, Chroma, and Streamlit to build a Conversation-aware Chatbot and a Retrieval-augmented generation (RAG) ChatBot. The RAG Chatbot works by taking a collection of Markdown files as input and provides answers based on the context provided by those files. It utilizes a Memory Builder component to load Markdown pages, divide them into sections, calculate embeddings, and save them in an embedding database. The chatbot retrieves relevant sections from the database, rewrites questions for optimal retrieval, and generates answers using a local language model. It also remembers previous interactions for more accurate responses. Various strategies are implemented to deal with context overflows, including creating and refining context, hierarchical summarization, and async hierarchical summarization.

NanoFlow is a throughput-oriented high-performance serving framework for Large Language Models (LLMs) that consistently delivers superior throughput compared to other frameworks by utilizing key techniques such as intra-device parallelism, asynchronous CPU scheduling, and SSD offloading. The framework proposes nano-batching to schedule compute-, memory-, and network-bound operations for simultaneous execution, leading to increased resource utilization. NanoFlow also adopts an asynchronous control flow to optimize CPU overhead and eagerly offloads KV-Cache to SSDs for multi-round conversations. The open-source codebase integrates state-of-the-art kernel libraries and provides necessary scripts for environment setup and experiment reproduction.

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.

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.

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.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

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.

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

NeoCodeium is a free AI completion plugin powered by Codeium, designed for Neovim users. It aims to provide a smoother experience by eliminating flickering suggestions and allowing for repeatable completions using the `.` key. The plugin offers performance improvements through cache techniques, displays suggestion count labels, and supports Lua scripting. Users can customize keymaps, manage suggestions, and interact with the AI chat feature. NeoCodeium enhances code completion in Neovim, making it a valuable tool for developers seeking efficient coding assistance.

Solana AI Trade Bot is an advanced trading tool specifically designed for meme token trading on the Solana blockchain. It leverages AI technology powered by GPT-4.0 to automate trades, identify low-risk/high-potential tokens, and assist in token creation and management. The bot offers cross-platform compatibility and a range of configurable settings for buying, selling, and filtering tokens. Users can benefit from real-time AI support and enhance their trading experience with features like automatic selling, slippage management, and profit/loss calculations. To optimize performance, it is recommended to connect the bot to a private light node for efficient trading execution.

KIVI is a plug-and-play 2bit KV cache quantization algorithm optimizing memory usage by quantizing key cache per-channel and value cache per-token to 2bit. It enables LLMs to maintain quality while reducing memory usage, allowing larger batch sizes and increasing throughput in real LLM inference workloads.

GuideLLM is a powerful tool for evaluating and optimizing the deployment of large language models (LLMs). By simulating real-world inference workloads, GuideLLM helps users gauge the performance, resource needs, and cost implications of deploying LLMs on various hardware configurations. This approach ensures efficient, scalable, and cost-effective LLM inference serving while maintaining high service quality. Key features include performance evaluation, resource optimization, cost estimation, and scalability testing.

SpinQuant is a tool designed for LLM quantization with learned rotations. It focuses on optimizing rotation matrices to enhance the performance of quantized models, narrowing the accuracy gap to full precision models. The tool implements rotation optimization and PTQ evaluation with optimized rotation, providing arguments for model name, batch sizes, quantization bits, and rotation options. SpinQuant is based on the findings that rotation helps in removing outliers and improving quantization, with specific enhancements achieved through learning rotation with Cayley optimization.

Cursor Lens is an open-source tool that acts as a proxy between Cursor and various AI providers, logging interactions and providing detailed analytics to help developers optimize their use of AI in their coding workflow. It supports multiple AI providers, captures and logs all requests, provides visual analytics on AI usage, allows users to set up and switch between different AI configurations, offers real-time monitoring of AI interactions, tracks token usage, estimates costs based on token usage and model pricing. Built with Next.js, React, PostgreSQL, Prisma ORM, Vercel AI SDK, Tailwind CSS, and shadcn/ui components.

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.

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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Optimize a YouTube script based on the top viral videos

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Provides strategic financial guidance for investment behavior to optimize organization's wealth.

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Optimize and compress your images. Up to 80% in file size reduction.

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Manages purchase orders to optimize procurement operations.

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