Best AI tools for< Parallel Computing >

Nooks is an AI-powered parallel dialer and virtual salesfloor platform designed to automate manual call tasks, boost volume, connect rates, and conversion rates. It offers features like call analytics, AI training, and Nooks Numbers to improve data coverage and quality. The platform enables users to coach and collaborate on live calls, transcribe and analyze calls, and work on talk tracks with tough personas using AI training. Nooks also provides resources like a blog, customer stories, and events to help users supercharge their sales pipeline.

Koncert is an AI-powered sales dialer and remote salesfloor platform that helps businesses accelerate sales success. With its AI-enhanced dialing, automated local presence, and caller ID health heat map, Koncert helps sales teams connect with more prospects, have more conversations, and close more deals. Koncert also offers a range of other features, including a multi-channel sales sequencer, remote coaching, and conversation intelligence. With Koncert, sales teams can improve their productivity, increase their connect rates, and close more deals.

BuildShip is a batch processing tool for ChatGPT that allows users to process ChatGPT tasks in parallel on a spreadsheet UI with CSV/JSON import and export. It supports various OpenAI models, including GPT4, Claude 3, and Gemini. Users can start with readymade templates and customize them with their own logic and models. The data generated is stored securely on the user's own Google Cloud project, and team collaboration is supported with granular access control.

Keymate.AI is an AI application that allows users to build GPTs with advanced search, browse, and long-term memory capabilities. It offers a personalized long-term memory on ChatGPT, parallel search functionality, and privacy features using Google API. Keymate.AI aims to elevate research, projects, and daily tasks by providing efficient AI memory management and real-time data retrieval from the web.

GPT Prompt Tuner is an AI tool designed to enhance ChatGPT prompts by generating variations and running conversations in parallel. It simplifies 'Prompt Engineering,' an emerging field that can lead to high earnings. Users can customize prompts, receive AI-generated variations, and engage in multiple ChatGPT conversations simultaneously. The tool offers flexible subscription plans and requires an OpenAI API Key for usage.

Zappx is a powerful power dialer application designed for sales professionals to enhance their cold calling outreach. With Zappx, users can double their daily connection rate by implementing parallel calling, dial up to 5 prospects simultaneously, filter out wrong numbers, automate voice mails, and connect calls to live prospects. The application also offers AI-enhanced features such as automated call transcription, sentiment analysis, and real-time analytics for performance evaluation. Zappx is built by sales people for sales people, aiming to transform outbound sales approaches with lightning-fast dialing capabilities.

Otto is an AI-powered tool designed to streamline work processes by bringing reasoning to data. It allows users to define tables once and automate numerous tasks in minutes. With features like research capabilities, outbound message creation, and customizable columns, Otto enables users to work 10x faster by leveraging AI agents for parallel processing. The tool unlocks insights from various data sources, including websites, documents, and images, and offers an AI Assistant for contextual assistance. Otto aims to enhance productivity and efficiency by providing advanced data analysis and processing functionalities.

FlashIntel is a revenue acceleration platform that offers a suite of tools and solutions to streamline sales and partnership processes. It provides features like real-time enrichment, personalized messaging, sequence and cadence, email deliverability, parallel dialing, account-based marketing, and more. The platform aims to help businesses uncover ideal prospects, target key insights, craft compelling outreach sequences, research companies and people's contacts in real-time, and execute omnichannel sequences with AI personalization.

Cykel AI is an AI co-pilot designed to assist users in automating various digital tasks. It interacts with any website to complete complex tasks based on user instructions, allowing users to offload 50% of their to-do list to AI. From sending emails to updating spreadsheets, Cykel offers a seamless way to streamline digital workflows and boost productivity. With features like autonomous learning, scalable parallel tasking, and the ability to create and share shortcuts, Cykel aims to revolutionize task automation for individuals and teams across different industries.

Automata is a content repurposing tool that uses AI to help you turn your videos, blogs, and other content into a variety of other formats, such as social media posts, email newsletters, and more. It offers a variety of features to make content repurposing easy and efficient, including platform-specific writing styles, 15+ content output types, content repurposing templates, and parallel content creation. Automata also has an AI Chrome extension for LinkedIn that can help you repurpose your content directly from the platform.

Beam AI is the #1 end-to-end automated takeoff software designed for General Contractors, Subcontractors, and Suppliers in the construction industry. It leverages cutting-edge Artificial Intelligence technology to provide accurate and fast quantity takeoffs for various trades, saving up to 90% of the time typically spent on manual takeoffs. With Beam AI, users can streamline their bidding process, send out more estimates, and focus on value engineering to build competitive estimates. The software offers features such as cloud-based collaboration, 100% done-for-you quantity takeoffs, auto-detection of spec details, and the ability to process multiple takeoffs in parallel.

Wannafake is a user-friendly online platform that allows users to swap faces in videos using just one photo. The application enables users to easily create fun and original videos by uploading photos and videos for free, combining them to create new videos. Wannafake offers a simple face swap tool with no subscriptions, allowing users to pay as they go. Users can buy seconds and spend them whenever they want, with built-in video clipping feature to easily trim videos and pay only for the clipped part. The platform allows users to create multiple videos simultaneously, ensuring videos are created fast and in parallel. Wannafake also offers a 15-second free trial upon creating a free account. Terms of use, privacy policy, and contact information are provided for user convenience.

Iambic Therapeutics is a cutting-edge AI-driven drug discovery platform that tackles the most challenging design problems in drug discovery, addressing unmet patient need. Its physics-based AI algorithms drive a high-throughput experimental platform, converting new molecular designs to new biological insights each week. Iambic's platform optimizes target product profiles, exploring multiple profiles in parallel to ensure that molecules are designed to solve the right problems in disease biology. It also optimizes drug candidates, deeply exploring chemical space to reveal novel mechanisms of action and deliver diverse high-quality leads.

Imperative Execution is the parent company of IntelligentCross, a platform that uses artificial intelligence (AI) to optimize trading performance in the US equities market. The platform's matching logic enhances market efficiency by optimizing price discovery and minimizing market impact. IntelligentCross is built with high-performance, massively parallel transaction processing that fully utilizes modern multi-core servers.

Pentest Copilot by BugBase is an ultimate ethical hacking assistant that guides users through each step of the hacking journey, from analyzing web apps to root shells. It eliminates redundant research, automates payload and command generation, and provides intelligent contextual analysis to save time. The application excels at data extraction, privilege escalation, lateral movement, and leaving no trace behind. With features like secure VPN integration, total control over sessions, parallel command processing, and flexibility to choose between local or cloud execution, Pentest Copilot offers a seamless and efficient hacking experience without the need for Kali Linux installation.

SquadGPT is an AI-powered platform designed to help startups streamline their hiring process by creating accurate job descriptions and screening candidates efficiently. The tool allows users to generate job descriptions with AI assistance, share them on various platforms, and then sit back while the AI screens candidates in parallel. SquadGPT aims to revolutionize the recruitment process by providing personalized and conversational screening experiences, ultimately accelerating the hiring process for startups.

Long-Context-Attention (YunChang) is a unified sequence parallel approach that combines the strengths of DeepSpeed-Ulysses-Attention and Ring-Attention to provide a versatile and high-performance solution for long context LLM model training and inference. It addresses the limitations of both methods by offering no limitation on the number of heads, compatibility with advanced parallel strategies, and enhanced performance benchmarks. The tool is verified in Megatron-LM and offers best practices for 4D parallelism, making it suitable for various attention mechanisms and parallel computing advancements.

ChatGLM.cpp is a C++ implementation of ChatGLM-6B, ChatGLM2-6B, ChatGLM3-6B and more LLMs for real-time chatting on your MacBook. It is based on ggml, working in the same way as llama.cpp. ChatGLM.cpp features accelerated memory-efficient CPU inference with int4/int8 quantization, optimized KV cache and parallel computing. It also supports P-Tuning v2 and LoRA finetuned models, streaming generation with typewriter effect, Python binding, web demo, api servers and more possibilities.

femtoGPT is a pure Rust implementation of a minimal Generative Pretrained Transformer. It can be used for both inference and training of GPT-style language models using CPUs and GPUs. The tool is implemented from scratch, including tensor processing logic and training/inference code of a minimal GPT architecture. It is a great start for those fascinated by LLMs and wanting to understand how these models work at deep levels. The tool uses random generation libraries, data-serialization libraries, and a parallel computing library. It is relatively fast on CPU and correctness of gradients is checked using the gradient-check method.

ChatLLM.cpp is a pure C++ implementation tool for real-time chatting with RAG on your computer. It supports inference of various models ranging from less than 1B to more than 300B. The tool provides accelerated memory-efficient CPU inference with quantization, optimized KV cache, and parallel computing. It allows streaming generation with a typewriter effect and continuous chatting with virtually unlimited content length. ChatLLM.cpp also offers features like Retrieval Augmented Generation (RAG), LoRA, Python/JavaScript/C bindings, web demo, and more possibilities. Users can clone the repository, quantize models, build the project using make or CMake, and run quantized models for interactive chatting.

Colossal-AI is a deep learning system for large-scale parallel training. It provides a unified interface to scale sequential code of model training to distributed environments. Colossal-AI supports parallel training methods such as data, pipeline, tensor, and sequence parallelism and is integrated with heterogeneous training and zero redundancy optimizer.

This repository contains a student training series focusing on AI-driven science on supercomputers. It covers topics such as ALCF systems overview, AI on supercomputers, neural networks, LLMs, and parallel training techniques. The content is organized into subdirectories with prefixed indexes for easy navigation. The series aims to provide hands-on experience and knowledge in utilizing AI on supercomputers for scientific research.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

The `mystic` framework provides a collection of optimization algorithms and tools that allow the user to robustly solve hard optimization problems. It offers fine-grained power to monitor and steer optimizations during the fit processes. Optimizers can advance one iteration or run to completion, with customizable stop conditions. `mystic` optimizers share a common interface for easy swapping without writing new code. The framework supports parameter constraints, including soft and hard constraints, and provides tools for scientific machine learning, uncertainty quantification, adaptive sampling, nonlinear interpolation, and artificial intelligence. `mystic` is actively developed and welcomes user feedback and contributions.

The `Call-for-Reviewers` repository aims to collect the latest 'call for reviewers' links from various top CS/ML/AI conferences/journals. It provides an opportunity for individuals in the computer/ machine learning/ artificial intelligence fields to gain review experience for applying for NIW/H1B/EB1 or enhancing their CV. The repository helps users stay updated with the latest research trends and engage with the academic community.

CGraph is a cross-platform **D** irected **A** cyclic **G** raph framework based on pure C++ without any 3rd-party dependencies. You, with it, can **build your own operators simply, and describe any running schedules** as you need, such as dependence, parallelling, aggregation and so on. Some useful tools and plugins are also provide to improve your project. Tutorials and contact information are show as follows. Please **get in touch with us for free** if you need more about this repository.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

Tau is a framework for building low maintenance & highly scalable cloud computing platforms that software developers will love. It aims to solve the high cost and time required to build, deploy, and scale software by providing a developer-friendly platform that offers autonomy and flexibility. Tau simplifies the process of building and maintaining a cloud computing platform, enabling developers to achieve 'Local Coding Equals Global Production' effortlessly. With features like auto-discovery, content-addressing, and support for WebAssembly, Tau empowers users to create serverless computing environments, host frontends, manage databases, and more. The platform also supports E2E testing and can be extended using a plugin system called orbit.

ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. Key value propositions of ExecuTorch are: * **Portability:** Compatibility with a wide variety of computing platforms, from high-end mobile phones to highly constrained embedded systems and microcontrollers. * **Productivity:** Enabling developers to use the same toolchains and SDK from PyTorch model authoring and conversion, to debugging and deployment to a wide variety of platforms. * **Performance:** Providing end users with a seamless and high-performance experience due to a lightweight runtime and utilizing full hardware capabilities such as CPUs, NPUs, and DSPs.

This repository contains the complete archive of the 2024 version of the 'Intelligent Computing System' experiment at the University of Chinese Academy of Sciences. The experiment content for 2024 has undergone extensive adjustments to the knowledge system and experimental topics, including the transition from TensorFlow to PyTorch, significant modifications to previous code, and the addition of experiments with large models. The project is continuously updated in line with the course progress, currently up to the seventh experiment. Updates include the addition of experiments like YOLOv5 in Experiment 5-3, updates to theoretical teaching materials, and fixes for bugs in Experiment 6 code. The repository also includes experiment manuals, questions, and answers for various experiments, with some data sets hosted on Baidu Cloud due to size limitations on GitHub.

The Artificial Intelligence Controller Interface (AICI) lets you build Controllers that constrain and direct output of a Large Language Model (LLM) in real time. Controllers are flexible programs capable of implementing constrained decoding, dynamic editing of prompts and generated text, and coordinating execution across multiple, parallel generations. Controllers incorporate custom logic during the token-by-token decoding and maintain state during an LLM request. This allows diverse Controller strategies, from programmatic or query-based decoding to multi-agent conversations to execute efficiently in tight integration with the LLM itself.

This repository contains Jupyter-based tutorials for NLP, ML, AI in Python for classes in Computational Linguistics, Natural Language Processing (NLP), Machine Learning (ML), and Artificial Intelligence (AI) at Indiana University.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

Open-Sora-Plan is a project that aims to create a simple and scalable repo to reproduce Sora (OpenAI, but we prefer to call it "ClosedAI"). The project is still in its early stages, but the team is working hard to improve it and make it more accessible to the open-source community. The project is currently focused on training an unconditional model on a landscape dataset, but the team plans to expand the scope of the project in the future to include text2video experiments, training on video2text datasets, and controlling the model with more conditions.

Expert in CUDA for configuration, installation, troubleshooting, and programming.

Call me Data- I draw historical parallels to your queries // An education tool // "Nothing new under the sun"

Generates 3D stereogram pairs for parallel viewing.

The Multiversal Prediction Matrix (MPM) leverages the speculative nature of multiverse theories to create a predictive framework. By simulating parallel universes with varied parameters, MPM explores a multitude of potential outcomes for different events and phenomena.