Best AI tools for< Improve Training >

Letter AI is a revenue acceleration platform powered by Generative AI, designed to empower sales teams to find information faster and support revenue growth. The platform offers AI-powered training and coaching, content creation and management, real-time assistance from an AI co-pilot, and tools for deal pursuit automation. Letter AI combines generative AI technology with company-specific data to deliver a unified revenue enablement platform, enhancing user experience and driving cost savings. The platform ensures security and privacy by adhering to industry-leading standards and responsible data practices.

Dubify is an AI video dubbing tool that leverages generative AI to translate videos automatically, enabling users to reach a global audience. Users can upload their content, edit the AI-generated transcript, and download the translated videos. The tool caters to various use cases such as content creation, marketing, online courses, and employee training. Dubify offers realistic and human-like voices for dubbing, with pricing packages based on usage requirements.

Sereda.ai is an AI-powered platform designed to unleash a team's potential by bringing together all documents and knowledge into one place, conducting employee surveys and satisfaction ratings, facilitating performance reviews, and providing solutions to increase team productivity. The platform offers features such as a knowledge base, employee surveys, performance review tools, interactive learning courses, and an AI assistant for instant answers. Sereda.ai aims to streamline HR processes, improve employee training and evaluation, and enhance overall team productivity.

Readyy is an AI-powered tool designed to help users improve their reading speed and comprehension. It offers free tools and a user-friendly dashboard to track progress. The tool leverages GPT artificial intelligence to ensure fresh tests and provides a global leaderboard for competitive practice. Readyy is beneficial for individuals of all ages, from early childhood development to adult literacy and cognitive aging. It emphasizes the importance of reading comprehension for cognitive growth, academic achievement, and critical thinking in the digital age.

Voxal AI is an AI-powered chatbot solution designed to enhance sales, customer support, and user engagement on websites. It offers a range of features including multiple AI models, A/B testing, cross-platform compatibility, multilingual support, advanced analytics, customization options, and multi-platform integration. Voxal AI is suitable for various industries such as e-commerce, e-learning, and SaaS, and can be used for tasks such as product recommendations, lead qualification, and automated customer support.

SC Training, formerly known as EdApp, is a mobile learning management system that offers a wide range of features to enhance the training experience for both administrators and learners. The platform provides tools for creating, managing, and tracking training courses, with a strong focus on microlearning and gamification. SC Training aims to deliver bite-sized, engaging content that can be accessed anytime, anywhere, on any device. The application also incorporates AI technology to streamline course creation and improve the learning experience. With a diverse course library, practical assessments, and group training capabilities, SC Training is designed to help organizations deliver effective and efficient training programs.

Wonda is an AI-powered platform that enables users to create immersive learning experiences and simulations. It offers a range of features such as AI companions, quiz and assessments, virtual tours, role-playing games, and virtual workshops. Users can easily build interactive learning journeys without the need for coding. Wonda aims to enhance engagement and collaboration in training and onboarding processes, making learning experiences unforgettable and impactful. The platform supports integration with various learning management systems and provides advanced role management options for secure sharing. With Wonda, users can unleash their creativity and build virtual exhibits to showcase their ideas and projects in a fun and engaging way.

SymTrain is an AI-powered platform that automates training and coaching for contact center agents. By utilizing simulations and AI technology, SymTrain offers a cost-effective solution that enhances agent performance, reduces training time, and improves overall customer satisfaction. The platform provides automated role-play scenarios, consistent feedback, and data-driven coaching to help organizations streamline their training processes and achieve better results. SymTrain revolutionizes how companies train and coach their agents, leading to increased efficiency, revenue, and customer satisfaction.

Avais is a cutting-edge volleyball training application that revolutionizes the way athletes improve their game. It utilizes real-time analytics and AI technology to track and analyze volleyball matches, providing personalized coaching feedback to help users enhance their skills. With features like automatic highlight clip creation, competitive gameplay with friends and family, and easy scouting opportunities, Avais aims to empower athletes to reach their full potential conveniently from their mobile devices. The app focuses on growth and progress, offering professional coaching insights after every play to guide users towards success.

PocketCoach is an online AI-powered learning platform designed for athletes worldwide who aim to enhance their sports skills. The platform utilizes cutting-edge AI and computer vision technology to provide gamified drills, comprehensive analytics, and real-time feedback to help athletes break through plateaus and achieve faster results. PocketCoach also offers an innovative computer vision app called Playi, which transforms practice sessions by offering real-time analysis and personalized feedback on technique using a smartphone's camera.

Second Nature is an AI-powered sales training software that offers AI role-play simulations to help sales teams enhance their skills, boost sales, and increase productivity. The platform provides personalized AI training avatars for practicing various sales conversations, such as discovery calls, objection handling, and cold calling. Second Nature is used by leading companies to improve sales performance, accelerate proficiency attainment, and elevate customer satisfaction ratings.

Talkio AI is a language training app that uses AI technology to help users improve their oral language skills. It offers a variety of features, including voice conversations with AI tutors, pronunciation assessment, feedback on language skills, and a wide range of topics to discuss. Talkio AI is suitable for learners of all levels, from beginners to advanced speakers.

Lingio is an AI-powered employee training software designed for frontline workers, offering gamified learning experiences and mobile-based training solutions. The platform combines gamification and AI to enhance course completion rates and improve learning outcomes for deskless industries such as hospitality, cleaning, transportation, elderly care, and facility management.

Weekly Workout is an AI-powered fitness platform that provides personalized workout plans and tracks your progress. With Weekly Workout, you can get four days of invigorating exercise routines every week, tailored to your fitness level and goals. The platform also offers a weekly newsletter with tips and advice from fitness experts.

Grasply.ai is an AI-powered personalized training solution that transforms documents into impactful learning resources using multi-agent AI training assistants. It enhances productivity, improves skill transfer, and empowers teams to succeed by creating customized learning resources for training and assessment. Grasply allows users to upload documents, define learning goals, customize the learning experience, build tailored micro-courses with AI, share personalized courses, and track learner progress. It offers different pricing plans with varying features to cater to different user needs.

Atlanta Voiceover Studio is a professional voiceover training and recording studio based in Atlanta, GA. They offer a wide range of workshops and classes for voiceover artists of all levels, from beginners to experienced professionals. The studio provides training in various aspects of voiceover work, including animation, commercial voiceover, audiobook narration, and more. In addition to training, they also offer services such as auditions, demos, and business coaching to help voiceover artists succeed in the industry.

BuildAi is an AI tool designed to provide the lowest cost GPU cloud for AI training on the market. The platform is powered with renewable energy, enabling companies to train AI models at a significantly reduced cost. BuildAi offers interruptible pricing, short term reserved capacity, and high uptime pricing options. The application focuses on optimizing infrastructure for training and fine-tuning machine learning models, not inference, and aims to decrease the impact of computing on the planet. With features like data transfer support, SSH access, and monitoring tools, BuildAi offers a comprehensive solution for ML teams.

Impakt is an AI fitness coaching application that offers personalized workout plans, real-time feedback, community support, and tailored workouts to help users reach their fitness goals. The app allows users to track workouts, analyze performance, share progress, and receive insights to improve their fitness journey. With a focus on community engagement and athlete endorsements, Impakt aims to provide a comprehensive fitness experience for users of all levels.

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MyInterviewSkill is a gamified platform that offers AI-driven interview training to help users enhance their interview skills and boost their chances of landing their dream job. The platform provides personalized interview questions, tailored feedback, daily challenges, and interactive quests to make the preparation process engaging and effective. Users can earn experience points (XP), badges, and game credits as they progress through the training, ultimately improving their interview techniques and confidence.

Awesome MLSecOps is a curated list of open-source tools, resources, and tutorials for MLSecOps (Machine Learning Security Operations). It includes a wide range of security tools and libraries for protecting machine learning models against adversarial attacks, as well as resources for AI security, data anonymization, model security, and more. The repository aims to provide a comprehensive collection of tools and information to help users secure their machine learning systems and infrastructure.

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.

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.

YGO Agent is a project focused on using deep learning to master the Yu-Gi-Oh! trading card game. It utilizes reinforcement learning and large language models to develop advanced AI agents that aim to surpass human expert play. The project provides a platform for researchers and players to explore AI in complex, strategic game environments.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Uncheatable Eval is a tool designed to assess the language modeling capabilities of LLMs on real-time, newly generated data from the internet. It aims to provide a reliable evaluation method that is immune to data leaks and cannot be gamed. The tool supports the evaluation of Hugging Face AutoModelForCausalLM models and RWKV models by calculating the sum of negative log probabilities on new texts from various sources such as recent papers on arXiv, new projects on GitHub, news articles, and more. Uncheatable Eval ensures that the evaluation data is not included in the training sets of publicly released models, thus offering a fair assessment of the models' performance.

ProX is a lm-based data refinement framework that automates the process of cleaning and improving data used in pre-training large language models. It offers better performance, domain flexibility, efficiency, and cost-effectiveness compared to traditional methods. The framework has been shown to improve model performance by over 2% and boost accuracy by up to 20% in tasks like math. ProX is designed to refine data at scale without the need for manual adjustments, making it a valuable tool for data preprocessing in natural language processing tasks.

Foyle is a project focused on building agents to assist software developers in deploying and operating software. It aims to improve agent performance by collecting human feedback on agent suggestions and human examples of reasoning traces. Foyle utilizes a literate environment using vscode notebooks to interact with infrastructure, capturing prompts, AI-provided answers, and user corrections. The goal is to continuously retrain AI to enhance performance. Additionally, Foyle emphasizes the importance of reasoning traces for training agents to work with internal systems, providing a self-documenting process for operations and troubleshooting.

This repository contains the training and inference code needed to replicate the winning solution to the AI Mathematical Olympiad - Progress Prize 1. It consists of fine-tuning DeepSeekMath-Base 7B, high-quality training datasets, a self-consistency decoding algorithm, and carefully chosen validation sets. The training methodology involves Chain of Thought (CoT) and Tool Integrated Reasoning (TIR) training stages. Two datasets, NuminaMath-CoT and NuminaMath-TIR, were used to fine-tune the models. The models were trained using open-source libraries like TRL, PyTorch, vLLM, and DeepSpeed. Post-training quantization to 8-bit precision was done to improve performance on Kaggle's T4 GPUs. The project structure includes scripts for training, quantization, and inference, along with necessary installation instructions and hardware/software specifications.

RAG-FiT is a library designed to improve Language Models' ability to use external information by fine-tuning models on specially created RAG-augmented datasets. The library assists in creating training data, training models using parameter-efficient finetuning (PEFT), and evaluating performance using RAG-specific metrics. It is modular, customizable via configuration files, and facilitates fast prototyping and experimentation with various RAG settings and configurations.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

AvaTaR is a novel and automatic framework that optimizes an LLM agent to effectively use provided tools and improve performance on a given task/domain. It designs a comparator module to provide insightful prompts to the LLM agent via reasoning between positive and negative examples from training data.

Implementation of Double DQN reinforcement learning for OpenAI Gym environments with discrete action spaces. The algorithm aims to improve sample efficiency by using two uncorrelated Q-Networks to prevent overestimation of Q-values. By updating parameters periodically, the model reduces computation time and enhances training performance. The tool is based on the Double DQN method proposed by Hasselt in 2010.

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.

This project is a personal implementation and reproduction of a small-parameter Chinese LLM. It mainly refers to these two open source projects: https://github.com/charent/Phi2-mini-Chinese and https://github.com/DLLXW/baby-llama2-chinese. It includes the complete process of pre-training, SFT instruction fine-tuning, DPO, and PPO (to be done). I hope to share it with everyone and hope that everyone can work together to improve it!

A training tool for infosec professionals to improve their skills in GRC & security and help obtain related certifications.

Expert on altitude training research and benefits

I create tailored training manuals for various jobs and industries.

Designs effective training materials to enhance organizational learning and performance.

Language and Skill Training Centers collect personal information of learners, including progress tracking and sometimes payment details.

Training to help aspiring consultants & leaders think

Interactive soft skills training with visual storytelling.

full range of motion strength training at a pain-free level, one day at a time. prehab>rehab.

Memory training and cognitive skill enhancer

Memory training and cognitive skill enhancer

Simulates medical scenarios for advanced training.

PMP Training Instructor, providing lessons, answers, and practice questions on project management.

Assists with visual piano training and music theory.

Get the bootcamp training from comfort of your home.

ATC communication trainer for pilots, offering scenario-based training and feedback.

Authentic ATC sim for immersive pilot training. (KEMT is the default airfield).

Scholarly techniques, training, and philosophy.

I simulate tough Customer Support scenarios for Agent Training.

Sharpen your Roux solving skills with RouxGPT—your go-to for swift CMLL algorithms, effective training, and expert troubleshooting.

Custom lifting programs and strength coaching based off of your experience, goals, preferred training method, age, and available equipment.