Best AI tools for< Conduct Inference Optimization >

Workhub.ai is a website that offers a platform for conducting robot challenge screen tests. Users can assess the security of their site connection through this tool. The site prompts users to enable cookies in their browser settings to access the page.

SanptoBook is a personal accounting software designed to help individuals manage their finances efficiently. It offers features such as invoice and receipt management, reimbursement facilitation, tax filing assistance, bill splitting, and project tracking. The application aims to simplify financial tasks and improve overall financial organization for users. With AI-powered efficiency, SnaptoBook provides state-of-the-art receipt recognition technology and secure cloud storage for all receipts.

Poll the People is an AI-powered consumer research platform that offers 10X more effective surveys powered by ChatGPT. With a human panel of 500,000+ participants, the platform provides insights on brand testing, concept testing, logo testing, content testing, and more. By leveraging AI technology, users can make data-driven decisions, achieve faster insights, and access deep consumer understanding for better decision-making. The platform automates survey analysis, saving time and resources, and offers unbiased and accurate market insights. Poll the People is trusted by top brands worldwide for its efficiency and reliability in consumer research.

Rimo is a human-centered AI writer that helps you create high-quality content, fast. With Rimo, you can write blog posts, articles, website copy, social media posts, and more, in just a few minutes. Rimo's AI is trained on a massive dataset of human-written text, so it can generate content that is both informative and engaging.

The Website Audit AI is an AI-powered tool that offers free website audits and analysis for conversion rate optimization (CRO) and user experience (UX). It provides detailed insights and actionable recommendations to improve user experience and enhance conversion rates. The tool generates real reports based on data from actual users on genuine websites. With a focus on providing accurate and reliable information, Website Audit AI aims to help businesses optimize their online presence and drive better results.

Parroview is a revolutionary AI-powered user research platform that automates the process of conducting user interviews. It uses natural language processing (NLP) to engage with users in real-time conversations, asking follow-up questions and uncovering insights that would be difficult to obtain through traditional methods. Parroview is designed to be fully autonomous, allowing researchers to set up interviews and gather insights without the need for manual intervention. It supports multiple languages, making it accessible to a global audience. Parroview offers a range of features, including the ability to conduct interviews via text or voice, analyze insights in real-time, and generate detailed transcripts. It is suitable for a wide range of research needs, including product validation, consumer behavior analysis, post-purchase evaluations, brand perception studies, and customer persona development.

Wix.com is a website building platform that allows users to create stunning websites with ease. It offers a user-friendly interface with drag-and-drop functionality, making it simple for individuals and businesses to design their online presence. With a wide range of templates and customization options, Wix.com caters to users of all skill levels. Whether you're a beginner looking to build a personal blog or a professional wanting to showcase your portfolio, Wix.com provides the tools and features to bring your vision to life.

Recroo is a fully automated AI interview application that allows users to conduct interviews using artificial intelligence technology. The app is designed to streamline the screening process for recruiters by providing a real-interview like environment, complete feedback with ratings, AI assistant for answering questions, interview transcript review, and interview audio playback. Recroo simplifies the interview process by allowing users to provide job details and custom questions, while the AI engine takes care of conducting the interview. It is a powerful tool for recruiters looking to efficiently screen candidates and focus on other tasks.

EmpathixAI is an innovative AI tool designed to analyze and interpret human emotions through text and voice inputs. The tool uses advanced natural language processing and sentiment analysis algorithms to provide accurate insights into the emotional state of individuals. EmpathixAI helps businesses understand customer feedback, improve communication strategies, and enhance user experiences. With its user-friendly interface and powerful analytics capabilities, EmpathixAI is a valuable tool for companies looking to gain a deeper understanding of customer sentiment and emotions.

SciSpace is an AI-powered tool that helps researchers understand research papers better. It can explain and elaborate most academic texts in simple words. It is a great tool for students, researchers, and anyone who wants to learn more about a particular topic. SciSpace has a user-friendly interface and is easy to use. Simply upload a research paper or enter a URL, and SciSpace will do the rest. It will highlight key concepts, provide definitions, and generate a summary of the paper. SciSpace can also be used to generate citations and find related papers.

Search&AI is a comprehensive platform designed for patent due diligence, offering efficient and accurate results in minutes. It provides services such as prior art search, claim chart generation, novelty diligence analysis, portfolio analysis, document search, and AI-powered chatbot assistance. The platform is built by a team of experienced engineers and is tailored to streamline the patent discovery and analysis process, saving time and money compared to traditional outsourced search firms.

Ziggy is an AI-powered platform that automates 1-on-1 conversations, enabling users to conduct feedback interviews seamlessly with anyone, anytime. It helps businesses gather insightful and more natural responses from users than static forms ever could. Ziggy's commitment to collaboration and creativity helps teams work together to get the best results. Its powerful analytical tools help ensure users understand their users' wants and needs. With Ziggy, users can see the original responses from their users and use them to make better decisions.

Profundo is an AI-powered research assistant that automates data collection, analysis, and reporting. It enables users to conduct in-depth research on various topics efficiently and accurately. With cutting-edge AI algorithms, Profundo minimizes errors, maximizes productivity, and provides user-friendly interface for seamless integration with existing tools. Trusted by professionals, Profundo is used for self-study, content creation, academic research, industry analysis, and more.

Datarails is a financial planning and analysis platform for Excel users. It automates data consolidation, reporting, and planning while enabling finance teams to continue using their spreadsheets and financial models. With Datarails, finance teams can save time on repetitive tasks and focus on strategic insights that drive business growth.

InterviewAI is an AI-powered platform designed to streamline the interview process for both interviewers and candidates. It generates tailored interview questions in real-time, offers advanced practice tools, and provides automated scoring for candidate practice responses. The platform aims to enhance interview skills, boost confidence, and improve interview readiness for job seekers, companies, and educational institutions.

LawDroid is an AI legal assistant application designed to help legal professionals work smarter and more efficiently. It serves as a force multiplier, enabling users to accomplish more tasks without additional overhead. LawDroid offers features such as case law research, drafting emails and letters, and document analysis. It also provides benefits like intake new clients, data-driven decisions, automate documents, human in the loop automation, and building scalable tools. The application is used by students, faculty, and legal professionals to streamline legal processes and improve client experiences.

hirex.ai is an AI-powered platform that revolutionizes the job interview process by making it open, fair, and accessible to all. The platform utilizes GenAI assistant to help candidates get interviewed instantly, jump the line to secure their dream job, and undergo a faster screening process. With no credit card required, users can register for free early access, upload their resumes, and post job offers. The platform aims to transform HR and talent acquisition by providing innovative solutions for both job seekers and employers.

Branded Research, acquired by Dynata, provides access to AI-verified audience insights. It offers a range of research methods, including surveys, webcam studies, and emotional AI. With its advanced algorithms and extensive profiling, Branded helps businesses connect with their target audience and gain valuable insights to drive innovation. The company serves various industries, including tech, consumer goods, healthcare, and research agencies.

Cognosys is an AI-powered assistant that helps you simplify your workflows and automate tasks. With Cognosys, you can hand off tasks to AI Agents, so you can concentrate on what really matters. Cognosys can do more than answer questions. It's capable of breaking down complex objectives by creating tasks for itself and accomplishing them autonomously.

Effy AI is a free performance management software designed for teams to conduct 360 feedback and performance reviews efficiently. The AI-powered platform offers ready-to-use templates, flexible reviewer nominations, and insightful AI-generated reports to help companies build a culture of high-performing teams. With features like automated response collection, Slack integration, and a vast question bank, Effy AI streamlines the review process and provides valuable insights for employee development.

Tutel MoE is an optimized Mixture-of-Experts implementation that offers a parallel solution with 'No-penalty Parallism/Sparsity/Capacity/Switching' for modern training and inference. It supports Pytorch framework (version >= 1.10) and various GPUs including CUDA and ROCm. The tool enables Full Precision Inference of MoE-based Deepseek R1 671B on AMD MI300. Tutel provides features like all-to-all benchmarking, tensorcore option, NCCL timeout settings, Megablocks solution, and dynamic switchable configurations. Users can run Tutel in distributed mode across multiple GPUs and machines. The tool allows for custom MoE implementations and offers detailed usage examples and reference documentation.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) based on InternLM2-7B excelling in free-form text-image composition and comprehension. It boasts several amazing capabilities and applications: * **Free-form Interleaved Text-Image Composition** : InternLM-XComposer2 can effortlessly generate coherent and contextual articles with interleaved images following diverse inputs like outlines, detailed text requirements and reference images, enabling highly customizable content creation. * **Accurate Vision-language Problem-solving** : InternLM-XComposer2 accurately handles diverse and challenging vision-language Q&A tasks based on free-form instructions, excelling in recognition, perception, detailed captioning, visual reasoning, and more. * **Awesome performance** : InternLM-XComposer2 based on InternLM2-7B not only significantly outperforms existing open-source multimodal models in 13 benchmarks but also **matches or even surpasses GPT-4V and Gemini Pro in 6 benchmarks** We release InternLM-XComposer2 series in three versions: * **InternLM-XComposer2-4KHD-7B** 🤗: The high-resolution multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _High-resolution understanding_ , _VL benchmarks_ and _AI assistant_. * **InternLM-XComposer2-VL-7B** 🤗 : The multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _VL benchmarks_ and _AI assistant_. **It ranks as the most powerful vision-language model based on 7B-parameter level LLMs, leading across 13 benchmarks.** * **InternLM-XComposer2-VL-1.8B** 🤗 : A lightweight version of InternLM-XComposer2-VL based on InternLM-1.8B. * **InternLM-XComposer2-7B** 🤗: The further instruction tuned VLLM for _Interleaved Text-Image Composition_ with free-form inputs. Please refer to Technical Report and 4KHD Technical Reportfor more details.

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.

Vidur is a high-fidelity and extensible LLM inference simulator designed for capacity planning, deployment configuration optimization, testing new research ideas, and studying system performance of models under different workloads and configurations. It supports various models and devices, offers chrome trace exports, and can be set up using mamba, venv, or conda. Users can run the simulator with various parameters and monitor metrics using wandb. Contributions are welcome, subject to a Contributor License Agreement and adherence to the Microsoft Open Source Code of Conduct.

LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results. It allows users to control all elements of a typical experimentation pipeline - prompts, open-source LLMs, optimization strategy, and LLM testing - through a single YAML configuration file. The toolkit supports basic, intermediate, and advanced usage scenarios, enabling users to run custom experiments, conduct ablation studies, and automate fine-tuning workflows. It provides features for data ingestion, model definition, training, inference, quality assurance, and artifact outputs, making it a comprehensive tool for fine-tuning large language models.

LMOps is a research initiative focusing on fundamental research and technology for building AI products with foundation models, particularly enabling AI capabilities with Large Language Models (LLMs) and Generative AI models. The project explores various aspects such as prompt optimization, longer context handling, LLM alignment, acceleration of LLMs, LLM customization, and understanding in-context learning. It also includes tools like Promptist for automatic prompt optimization, Structured Prompting for efficient long-sequence prompts consumption, and X-Prompt for extensible prompts beyond natural language. Additionally, LLMA accelerators are developed to speed up LLM inference by referencing and copying text spans from documents. The project aims to advance technologies that facilitate prompting language models and enhance the performance of LLMs in various scenarios.

BoCoEL is a tool that leverages Bayesian Optimization to efficiently evaluate large language models by selecting a subset of the corpus for evaluation. It encodes individual entries into embeddings, uses Bayesian optimization to select queries, retrieves from the corpus, and provides easily managed evaluations. The tool aims to reduce computation costs during evaluation with a dynamic budget, supporting models like GPT2, Pythia, and LLAMA through integration with Hugging Face transformers and datasets. BoCoEL offers a modular design and efficient representation of the corpus to enhance evaluation quality.

MSCCL++ is a GPU-driven communication stack for scalable AI applications. It provides a highly efficient and customizable communication stack for distributed GPU applications. MSCCL++ redefines inter-GPU communication interfaces, delivering a highly efficient and customizable communication stack for distributed GPU applications. Its design is specifically tailored to accommodate diverse performance optimization scenarios often encountered in state-of-the-art AI applications. MSCCL++ provides communication abstractions at the lowest level close to hardware and at the highest level close to application API. The lowest level of abstraction is ultra light weight which enables a user to implement logics of data movement for a collective operation such as AllReduce inside a GPU kernel extremely efficiently without worrying about memory ordering of different ops. The modularity of MSCCL++ enables a user to construct the building blocks of MSCCL++ in a high level abstraction in Python and feed them to a CUDA kernel in order to facilitate the user's productivity. MSCCL++ provides fine-grained synchronous and asynchronous 0-copy 1-sided abstracts for communication primitives such as `put()`, `get()`, `signal()`, `flush()`, and `wait()`. The 1-sided abstractions allows a user to asynchronously `put()` their data on the remote GPU as soon as it is ready without requiring the remote side to issue any receive instruction. This enables users to easily implement flexible communication logics, such as overlapping communication with computation, or implementing customized collective communication algorithms without worrying about potential deadlocks. Additionally, the 0-copy capability enables MSCCL++ to directly transfer data between user's buffers without using intermediate internal buffers which saves GPU bandwidth and memory capacity. MSCCL++ provides consistent abstractions regardless of the location of the remote GPU (either on the local node or on a remote node) or the underlying link (either NVLink/xGMI or InfiniBand). This simplifies the code for inter-GPU communication, which is often complex due to memory ordering of GPU/CPU read/writes and therefore, is error-prone.

CogAgent is an advanced intelligent agent model designed for automating operations on graphical interfaces across various computing devices. It supports platforms like Windows, macOS, and Android, enabling users to issue commands, capture device screenshots, and perform automated operations. The model requires a minimum of 29GB of GPU memory for inference at BF16 precision and offers capabilities for executing tasks like sending Christmas greetings and sending emails. Users can interact with the model by providing task descriptions, platform specifications, and desired output formats.

The Bee Agent Framework is an open-source tool for building, deploying, and serving powerful agentic workflows at scale. It provides AI agents, tools for creating workflows in Javascript/Python, a code interpreter, memory optimization strategies, serialization for pausing/resuming workflows, traceability features, production-level control, and upcoming features like model-agnostic support and a chat UI. The framework offers various modules for agents, llms, memory, tools, caching, errors, adapters, logging, serialization, and more, with a roadmap including MLFlow integration, JSON support, structured outputs, chat client, base agent improvements, guardrails, and evaluation.

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.

Yalm (Yet Another Language Model) is an LLM inference implementation in C++/CUDA, emphasizing performance engineering, documentation, scientific optimizations, and readability. It is not for production use and has been tested on Mistral-v0.2 and Llama-3.2. Requires C++20-compatible compiler, CUDA toolkit, and LLM safetensor weights in huggingface format converted to .yalm file.

This repository, RAM, focuses on developing advanced algorithms and methods for Reasoning, Alignment, Memory. It contains projects related to these areas and is maintained by a team of individuals. The repository is licensed under the MIT License.

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

MInference is a tool designed to accelerate pre-filling for long-context Language Models (LLMs) by leveraging dynamic sparse attention. It achieves up to a 10x speedup for pre-filling on an A100 while maintaining accuracy. The tool supports various decoding LLMs, including LLaMA-style models and Phi models, and provides custom kernels for attention computation. MInference is useful for researchers and developers working with large-scale language models who aim to improve efficiency without compromising accuracy.

Build fast and accurate GenAI applications with GraphRAG SDK, a specialized toolkit for building Graph Retrieval-Augmented Generation (GraphRAG) systems. It integrates knowledge graphs, ontology management, and state-of-the-art LLMs to deliver accurate, efficient, and customizable RAG workflows. The SDK simplifies the development process by automating ontology creation, knowledge graph agent creation, and query handling, enabling users to interact and query their knowledge graphs effectively. It supports multi-agent systems and orchestrates agents specialized in different domains. The SDK is optimized for FalkorDB, ensuring high performance and scalability for large-scale applications. By leveraging knowledge graphs, it enables semantic relationships and ontology-driven queries that go beyond standard vector similarity, enhancing retrieval-augmented generation capabilities.

LangTest is a comprehensive evaluation library for custom LLM and NLP models. It aims to deliver safe and effective language models by providing tools to test model quality, augment training data, and support popular NLP frameworks. LangTest comes with benchmark datasets to challenge and enhance language models, ensuring peak performance in various linguistic tasks. The tool offers more than 60 distinct types of tests with just one line of code, covering aspects like robustness, bias, representation, fairness, and accuracy. It supports testing LLMS for question answering, toxicity, clinical tests, legal support, factuality, sycophancy, and summarization.

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.

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