Best AI tools for< Performance Trainer >

SportBoost AI is an AI-powered application designed to help athletes measure and improve their performance across various sports. The platform offers innovative solutions that leverage advanced Artificial Intelligence technology to track metrics such as ball speeds and jump performances. SportBoost AI aims to democratize access to performance data for athletes and coaches at all levels, from amateur to professional. The application is committed to scientific research and continuous innovation to enhance athletic excellence.

Uplift is an AI-powered platform that optimizes human movement performance by providing insights for sports performance, sports medicine, and sports media. It offers products like Uplift Capture and Uplift Vision to enhance performance, minimize risk, and elevate broadcasting experiences. The platform is utilized by Major League Baseball, professional sports teams, elite performance coaches, and Division I athletics programs. Uplift uses AI-powered movement analysis to unlock unrivaled insights for athletes and broadcasters, helping them improve performance, reduce injury risk, and engage fans effectively.

Allego Conversation Intelligence is an AI-powered platform that helps revenue teams enhance performance and revenue by analyzing sales conversations. The platform enables users to capture, review, coach, and share valuable insights from conversations with customers. It leverages AI-driven analysis to reveal successful outcomes and provides data-driven performance coaching to improve sales performance. Allego Conversation Intelligence allows users to search, filter, and leverage call intelligence to uncover key moments that impact revenue. Trusted by top companies, the platform offers integrations with existing systems and resources for modern sales teams.

Salesably is an AI-driven sales practice platform that transforms sales training from static to dynamic through interactive playbooks, AI-powered practice, skills certification, and performance analytics. It offers sales trainers and managers a cutting-edge platform to enhance programs, drive better results, and create new revenue streams. With features like practice against diverse personas, learning paths & certification, customizable platform, measurable impact, objection handling mastery, discovery questioning excellence, pitch optimization workshops, and actionable insights for sales leaders and trainers, Salesably empowers sales teams to become masters of buyer-centric selling.

Mindtickle is an AI-powered Sales Enablement & Revenue Productivity Platform designed to help organizations improve sales performance through training, coaching, content management, and analytics. The platform offers a comprehensive suite of tools to enhance sales readiness, optimize sales operations, and drive revenue growth. With features like Conversation Intelligence, Sales Forecasting, Digital Sales Rooms, and Analytics & Dashboards, Mindtickle empowers sales teams to achieve their targets efficiently. The platform is known for its ability to personalize training, increase revenue productivity, and reduce ramp time for new reps, ultimately leading to improved sales outcomes and customer satisfaction.

Tidalflow is an AI-powered personal trainer application that offers personalized workout routines based on individual preferences and performance. It provides expert feedback, tracks progress, and ensures correct exercise form to help users achieve their fitness goals. The app is available 24/7, anywhere, and adapts to users' lifestyles to maintain motivation and consistency. Tidalflow aims to revolutionize the fitness industry by combining AI technology with fitness expertise to deliver tailored workout experiences.

Retorio is a cutting-edge Behavioral Intelligence (BI) Platform that fuses machine learning with scientific findings from psychology and organizational research to ultimately take learning and development to a new level within organizations. At the core of Retorio’s capabilities are its AI-powered immersive video simulations. Through these engaging role-plays, learners using Retorio get to train and develop the necessary skills through realistic scenarios. Furthermore, the personalized, on-demand feedback learners receive allows for immediate behavior change and performance improvement. Retorio’s training platform transcends the limitation of scalability and redefines how individuals and teams train and develop, bringing talent development to a new dimension.

LearnUpon is an AI-powered Learning Management System (LMS) that offers a comprehensive platform for creating, delivering, and managing training programs. It provides a seamless learning experience for both teams and learners, with features such as course creation, training delivery, learner engagement, user management, AI-powered learning, portals, and reporting. LearnUpon Anywhere allows for the integration of customer education directly into product experiences. The platform is designed to streamline training tasks, automate processes, and personalize learning programs using AI technology. With a focus on customer experience, security, and scalability, LearnUpon aims to drive impactful learning outcomes for businesses of all sizes.

SweetRush is a corporate training and eLearning company that provides custom learning solutions, talent solutions, XR immersive tech for learning, voiceover services, and support for nonprofits. They specialize in creating engaging and effective learning programs that help businesses thrive. SweetRush has been recognized for its excellence in learning and development, winning numerous awards for its innovative and impactful work.

aiWORKOUT generator is an AI-powered fitness platform that offers personalized workout plans tailored to individual needs and circumstances. The platform combines advanced AI technology with certified fitness trainers to create hyper-personalized workout plans that are safe and effective. Users can choose from different membership tiers to access customized workout programs, nutrition plans, 1-on-1 training sessions, and ongoing expert adjustments. The platform's AI exercise generator takes into account users' current fitness levels, goals, and equipment availability to create evolving workout plans. With aiWORKOUT generator, users can experience the future of fitness by achieving their goals faster and more efficiently.

Kayyo is a personal MMA trainer application that offers interactive lessons for beginners and experts. It provides challenges, personalized feedback, and a variety of games to enhance punching and kicking prowess. With AI personal trainers, Kayyo transforms workouts into dynamic and entertaining sessions that adapt to the user's pace. The app aims to help users master their moves, engage in virtual fights, and improve their overall fitness performance. Kayyo is free to use and currently focuses on building its features for martial arts enthusiasts.

Athletica AI is an AI-powered athletic training and personalized fitness application that offers tailored coaching and training plans for various sports like cycling, running, duathlon, triathlon, and rowing. It adapts to individual fitness levels, abilities, and availability, providing daily step-by-step training plans and comprehensive session analyses. Athletica AI integrates seamlessly with workout data from platforms like Garmin, Strava, and Concept 2 to craft personalized training plans and workouts. The application aims to help athletes train smarter, not harder, by leveraging the power of AI to optimize performance and achieve fitness goals.

Rapid Muscle is a science-powered hypertrophy workout generator that offers a cutting-edge platform to accelerate muscle growth. It provides tools like the Hypertrophy Split Generator and Workout Tracker to optimize exercise selection, sequencing, and volume for physique development. The upcoming AI Personal Trainer chatbot enhances user experience by providing expert advice on training-related queries. Rapid Muscle aims to revolutionize hypertrophy programming by offering evidence-based solutions and eliminating contradictory influencer advice.

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.

UpT Golf is a cutting-edge application designed for golfers, athletes, and coaches to enhance their skills and performance. Powered by Computer Vision and Artificial Intelligence, the app offers in-depth swing analysis, progress tracking, personalized recommendations, and real-time feedback. It provides a user-friendly interface for golfers to monitor their progress and for coaches to analyze and guide their students effectively. UpT Golf also facilitates communication among players and coaches, creating a supportive community for sharing experiences and tips. With innovative features and advanced tools, UpT Golf revolutionizes golf training by making it more efficient, enjoyable, and accessible to users worldwide.

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.

Highspot is a leading sales enablement platform that helps businesses improve their sales performance. It provides a range of features to help sales teams manage content, train and coach reps, and engage buyers. Highspot's AI-driven insights help sales teams identify opportunities, close deals faster, and increase revenue.

Flockjay is a modern, unified Learning and Content Management System for all your sales enablement needs, with generative AI and 50+ integrations that bring the right knowledge to the right people, at the right time. Flockjay lets you easily manage your sales teams’ content, learning, deal insights, coaching, & more - with the help of Generative AI.

PEAR Health Labs is an AI-powered adaptive digital coaching software that offers hyperpersonalized coaching solutions to help individuals move smarter, get healthier, and live happier. The platform utilizes AI technology and physiological science to create personalized fitness experiences based on wearables and biometric feedback. PEAR Training Intelligence aims to change the landscape of preventative care by identifying health issues before they become problems. The software is cost-effective, scalable, and provides guidance on physical activity to improve overall health outcomes.

Wonderway is an AI Sales Coach and Sales Training Platform that leverages AI technology to provide automated sales coaching on every call. It helps sales teams train, upskill, and certify their members, leading to increased conversion rates and reduced ramp time. The platform offers personalized training, aligns teams faster, and improves sales onboarding efficiency. Wonderway uses AI to analyze sales team performance and provide tailored recommendations for improvement, making it a valuable tool for sales professionals seeking to enhance their skills and boost sales 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.

Caissa is a strong, UCI command-line chess engine optimized for regular chess, FRC, and DFRC. It features its own neural network trained with self-play games, supports various UCI options, and provides different EXE versions for different CPU architectures. The engine uses advanced search algorithms, neural network evaluation, and endgame tablebases. It offers outstanding performance in ultra-short games and is written in C++ with modules for backend, frontend, and utilities like neural network trainer and self-play data generator.

RWKV is an RNN with Transformer-level LLM performance, which can also be directly trained like a GPT transformer (parallelizable). And it's 100% attention-free. You only need the hidden state at position t to compute the state at position t+1. You can use the "GPT" mode to quickly compute the hidden state for the "RNN" mode. So it's combining the best of RNN and transformer - **great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding** (using the final hidden state).

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

PaddleNLP is an easy-to-use and high-performance NLP library. It aggregates high-quality pre-trained models in the industry and provides out-of-the-box development experience, covering a model library for multiple NLP scenarios with industry practice examples to meet developers' flexible customization needs.

Weights & Biases (W&B) is a platform that helps users build better machine learning models faster by tracking and visualizing all components of the machine learning pipeline, from datasets to production models. It offers tools for tracking, debugging, evaluating, and monitoring machine learning applications. W&B provides integrations with popular frameworks like PyTorch, TensorFlow/Keras, Hugging Face Transformers, PyTorch Lightning, XGBoost, and Sci-Kit Learn. Users can easily log metrics, visualize performance, and compare experiments using W&B. The platform also supports hosting options in the cloud or on private infrastructure, making it versatile for various deployment needs.

YuLan-Mini is a lightweight language model with 2.4 billion parameters that achieves performance comparable to industry-leading models despite being pre-trained on only 1.08T tokens. It excels in mathematics and code domains. The repository provides pre-training resources, including data pipeline, optimization methods, and annealing approaches. Users can pre-train their own language models, perform learning rate annealing, fine-tune the model, research training dynamics, and synthesize data. The team behind YuLan-Mini is AI Box at Renmin University of China. The code is released under the MIT License with future updates on model weights usage policies. Users are advised on potential safety concerns and ethical use of the model.

DeepRetrieval is a tool designed to enhance search engines and retrievers using Large Language Models (LLMs) and Reinforcement Learning (RL). It allows LLMs to learn how to search effectively by integrating with search engine APIs and customizing reward functions. The tool provides functionalities for data preparation, training, evaluation, and monitoring search performance. DeepRetrieval aims to improve information retrieval tasks by leveraging advanced AI techniques.

This repository contains convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language (that isn't English). The rationale behind this is that LLaMa3 is trained on primarily English data and while it works to some extent for other languages, its performance is poor compared to English.

AnglE is a library for training state-of-the-art BERT/LLM-based sentence embeddings with just a few lines of code. It also serves as a general sentence embedding inference framework, allowing for inferring a variety of transformer-based sentence embeddings. The library supports various loss functions such as AnglE loss, Contrastive loss, CoSENT loss, and Espresso loss. It provides backbones like BERT-based models, LLM-based models, and Bi-directional LLM-based models for training on single or multi-GPU setups. AnglE has achieved significant performance on various benchmarks and offers official pretrained models for both BERT-based and LLM-based models.

LLaMa2lang is a repository containing convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language that isn't English. The repository aims to improve the performance of LLaMa3 for non-English languages by combining fine-tuning with RAG. Users can translate datasets, extract threads, turn threads into prompts, and finetune models using QLoRA and PEFT. Additionally, the repository supports translation models like OPUS, M2M, MADLAD, and base datasets like OASST1 and OASST2. The process involves loading datasets, translating them, combining checkpoints, and running inference using the newly trained model. The repository also provides benchmarking scripts to choose the right translation model for a target language.

This repository contains an unofficial implementation of the xLSTM model introduced in Beck et al. (2024). It serves as a didactic tool to explain the details of a modern Long-Short Term Memory model with competitive performance against Transformers or State-Space models. The repository also includes a Lightning-based implementation of a basic LLM for multi-GPU training. It provides modules for scalar-LSTM and matrix-LSTM, as well as an xLSTM LLM built using Pytorch Lightning for easy training on multi-GPUs.

FastFit is a Python package designed for fast and accurate few-shot classification, especially for scenarios with many semantically similar classes. It utilizes a novel approach integrating batch contrastive learning and token-level similarity score, significantly improving multi-class classification performance in speed and accuracy across various datasets. FastFit provides a convenient command-line tool for training text classification models with customizable parameters. It offers a 3-20x improvement in training speed, completing training in just a few seconds. Users can also train models with Python scripts and perform inference using pretrained models for text classification tasks.

Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. It is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and allows users to integrate machine learning and deep learning models with their Java applications. The framework is deep learning engine agnostic, enabling users to switch engines at any point for optimal performance. DJL's ergonomic API interface guides users with best practices to accomplish deep learning tasks, such as running inference and training neural networks.

Unsloth is a tool that allows users to fine-tune large language models (LLMs) 2-5x faster with 80% less memory. It is a free and open-source tool that can be used to fine-tune LLMs such as Gemma, Mistral, Llama 2-5, TinyLlama, and CodeLlama 34b. Unsloth supports 4-bit and 16-bit QLoRA / LoRA fine-tuning via bitsandbytes. It also supports DPO (Direct Preference Optimization), PPO, and Reward Modelling. Unsloth is compatible with Hugging Face's TRL, Trainer, Seq2SeqTrainer, and Pytorch code. It is also compatible with NVIDIA GPUs since 2018+ (minimum CUDA Capability 7.0).

MindNLP is an open-source NLP library based on MindSpore. It provides a platform for solving natural language processing tasks, containing many common approaches in NLP. It can help researchers and developers to construct and train models more conveniently and rapidly. Key features of MindNLP include: * Comprehensive data processing: Several classical NLP datasets are packaged into a friendly module for easy use, such as Multi30k, SQuAD, CoNLL, etc. * Friendly NLP model toolset: MindNLP provides various configurable components. It is friendly to customize models using MindNLP. * Easy-to-use engine: MindNLP simplified complicated training process in MindSpore. It supports Trainer and Evaluator interfaces to train and evaluate models easily. MindNLP supports a wide range of NLP tasks, including: * Language modeling * Machine translation * Question answering * Sentiment analysis * Sequence labeling * Summarization MindNLP also supports industry-leading Large Language Models (LLMs), including Llama, GLM, RWKV, etc. For support related to large language models, including pre-training, fine-tuning, and inference demo examples, you can find them in the "llm" directory. To install MindNLP, you can either install it from Pypi, download the daily build wheel, or install it from source. The installation instructions are provided in the documentation. MindNLP is released under the Apache 2.0 license. If you find this project useful in your research, please consider citing the following paper: @misc{mindnlp2022, title={{MindNLP}: a MindSpore NLP library}, author={MindNLP Contributors}, howpublished = {\url{https://github.com/mindlab-ai/mindnlp}}, year={2022} }

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

This repository contains code for training reward models for Deep Reinforcement Learning-based Reward-modulated Hierarchical Fine-tuning (DRL-based RLHF), Iterative Selection Fine-tuning (Rejection sampling fine-tuning), and iterative Decision Policy Optimization (DPO). The reward models are trained using a Bradley-Terry model based on the Gemma and Mistral language models. The resulting reward models achieve state-of-the-art performance on the RewardBench leaderboard for reward models with base models of up to 13B parameters.

Co-LLM (Collaborative Language Models) is a tool for learning to decode collaboratively with multiple language models. It provides a method for data processing, training, and inference using a collaborative approach. The tool involves steps such as formatting/tokenization, scoring logits, initializing Z vector, deferral training, and generating results using multiple models. Co-LLM supports training with different collaboration pairs and provides baseline training scripts for various models. In inference, it uses 'vllm' services to orchestrate models and generate results through API-like services. The tool is inspired by allenai/open-instruct and aims to improve decoding performance through collaborative learning.

PyTorch Lightning is a framework for training and deploying AI models. It provides a high-level API that abstracts away the low-level details of PyTorch, making it easier to write and maintain complex models. Lightning also includes a number of features that make it easy to train and deploy models on multiple GPUs or TPUs, and to track and visualize training progress. PyTorch Lightning is used by a wide range of organizations, including Google, Facebook, and Microsoft. It is also used by researchers at top universities around the world. Here are some of the benefits of using PyTorch Lightning: * **Increased productivity:** Lightning's high-level API makes it easy to write and maintain complex models. This can save you time and effort, and allow you to focus on the research or business problem you're trying to solve. * **Improved performance:** Lightning's optimized training loops and data loading pipelines can help you train models faster and with better performance. * **Easier deployment:** Lightning makes it easy to deploy models to a variety of platforms, including the cloud, on-premises servers, and mobile devices. * **Better reproducibility:** Lightning's logging and visualization tools make it easy to track and reproduce training results.

Explores genomics and AI in sports medicine and performance.

Unleash Peak Brain Performance: Precision Nutrition for the Focused Warrior

Advanced BJJ training guide specialist, focusing on competition performance enhancement and holistic development.

Craft personalized Zone Diet meals with ease! 😊 Balance your macros in a 40:30:30 ratio for optimal health and performance. 🥑🥖🍚

Creates tailored Pilates routines based on user's goals and fitness level.

I create tailored training manuals for various jobs and industries.

Especialista em Educação Física e análise de dados

Bonjour ! Je suis Coach Courbis, votre entraîneur de football virtuel personnalisé.

Your AI Sports Scientist to help you level up your game - in and off the field

Guiding your triathlon journey, step by step.

Provides running splits for Strava Routes, accounting for distance and elevation changes

Txhawb kev tsim kom sai rau Chatgpt - Lus Hmoob

Sitecore expert MVPinny at your service!

Expert on sports drinks and hydration, providing practical, health-focused advice.

A comprehensive mental strength coach for athletes.

Expert in biohacking and natural supplement research, informative and precise.

你是一共拥有最前沿的知识储备，丰富的教学经验，优秀的课程设计能力的优秀教育工作者。

Design your perfect race calendar and training plans for your next race.

A chatbot trained on GA4 documentation, updated regularly, providing detailed guidance along with helpful links.

A detailed expert trained on all 5,588 pages of Apple CoreData, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️