Best AI tools for< Provide Training On Probationary Periods >

The Media Copilot is an AI tool that offers content, courses, and consulting services on how newsrooms, agencies, and other content-based organizations can integrate generative AI into their work. They provide training on using AI for content creation, offer courses for individuals and teams, and help build organizations' AI roadmap. The tool also provides public speaking services and sponsorships for reaching a large audience of media executives, journalists, PR professionals, and creatives.

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.

Grow with Google is an AI tool designed to provide training and resources to help individuals boost their productivity and skills in various fields such as cybersecurity, data analytics, digital marketing, IT support, project management, UX design, and AI essentials. The platform offers online courses, tools, and professional certificates to help users develop ideas, make informed decisions, and enhance their daily work tasks using generative AI tools. With a focus on career growth and business development, Grow with Google aims to empower individuals with essential AI skills to succeed in today's competitive job market.

Mursion is an immersive learning platform that utilizes human-powered AI to provide training simulations for developing interpersonal skills in various workplace scenarios. The platform offers 1:1 immersive training sessions with virtual avatars, designed to enhance communication and people skills. Mursion's simulations are supported by a team of Simulation Specialists who deliver realistic interactions to help learners practice and improve their skills effectively. The platform is backed by over a decade of research and psychology, focusing on providing a safe and impactful learning environment for individuals across different industries.

The Future of Privacy Forum (FPF) is an AI tool that serves as a catalyst for privacy leadership and scholarship, advancing principled data practices in support of emerging technologies. It provides resources, training sessions, and guidance on AI-related topics, online advertising, youth privacy legislation, and more. FPF brings together industry, academics, civil society, policymakers, and other stakeholders to explore challenges posed by emerging technologies and develop privacy protections, ethical norms, and best practices.

Accessibility Desk is an accredited research and training agency specializing in digital accessibility and the WCAG. They provide accessibility audits for websites and apps based on the WCAG-EM standard. The agency is committed to creating a digital world that is accessible to all by offering knowledge sharing, specific advice, and assistance to organizations in improving their accessibility.

RespectablyAI is an AI-driven platform revolutionizing workplace communication by combining gamification and AI insights to provide interactive and impactful learning experiences on respect, inclusivity, and diversity. The platform offers contextual learning, adaptive feedback, seamless integration with corporate systems, engaging gamified training, and insightful analytics for targeted learning. It aims to help organizations enhance workplace culture and create respectful, inclusive, and diverse environments.

HEROZ is a Japanese company that specializes in AI technology. They offer a variety of AI-related services, including AI/DX support, AI consulting, and AI development. HEROZ's mission is to use AI to solve various problems in different industries and create a better future.

Revvie is an AI-powered real estate coaching and brokerage support platform that offers 24/7 assistance to brokerages and teams. It provides custom AI solutions for compliance questions, instant sales support, live and on-demand training, and human coaching. Revvie helps save time on training, offers affordable pricing plans, and aims to address common challenges in the real estate industry. The platform combines AI technology with human touch to enhance agent skills, lead generation, and deal closures.

ChatFlow is an AI chatbot application designed to empower businesses by creating AI-powered chatbots for customer support. With ChatFlow, users can engage customers, increase conversions, and boost revenue effortlessly. The application allows for training chatbots on various content types, easy integration into websites, and customization of appearance to align with brand identity. ChatFlow is ideal for SaaS, E-commerce, or any online business looking to deliver automated customer service experiences and enhance user engagement.

Data Science Dojo is a globally recognized e-learning platform that offers programs in data science, data analytics, machine learning, and more. They provide comprehensive and hands-on training in various formats such as in-person, virtual instructor-led, and self-paced training. The focus is on helping students develop a think-business-first mindset to apply their data science skills effectively in real-world scenarios. With over 2500 enterprises trained, Data Science Dojo aims to make data science accessible to everyone.

Chatflot is an AI chatbot application that helps businesses automate up to 95% of customer queries. It allows users to create customized AI chatbots based on the ChatGPT language model, enabling them to provide on-demand information to customers through their website. Chatflot is suitable for various industries and offers features like training the chatbot on specific data, optimizing customer interactions, and integrating seamlessly with different CMS platforms. The application aims to enhance customer service, boost sales, and streamline support processes by providing personalized assistance and relevant information to users.

My AskAI is an AI-powered customer support tool that integrates with Intercom. It offers a more affordable alternative to Intercom's Fin AI chatbot, costing only $0.19 per AI resolution compared to Intercom's $0.99. My AskAI allows businesses to add AI customer support to their Intercom workspace without replacing their existing widget or training their team on a new tool. Businesses can choose how they want their AI chatbot to reply, either directly to customers or as 'notes' for their agents. My AskAI also supports human handover for when a human touch is needed.

JobInterview.guru is an AI-powered platform designed to provide personalized interview training for job seekers. Leveraging advanced AI technology, the platform offers realistic job interview simulations, detailed insights into interview questions, and personalized feedback to help users prepare effectively. With a focus on efficiency and cost-effectiveness, JobInterview.guru aims to empower users to confidently navigate their job interviews and land their dream jobs.

AIBrain is a tech start-up in Palo Alto, California with its focus on Education and Entertainment. AIBrain was recognized as a top 5 entertainment AI company in 2023 by Datamation. This includes bestseller AI courses, Autonomous Game AI, Humanoid AI, and Soccer AI/VR Assistant. AIBrain has also been actively involved in the Stanford Computer Forum as a member company since 2013. AIBrain has been leading the technology development on the areas of entertainment and education. AIBrain provides the Game Changer Football AI x VR solutions, called SAIVA (Sports AI Virtual Assistant) and SAICA (Sports AI Coach Assistant). As a world-class football / soccer solution, it was ranked at top 3 contender in the Camera Calibration Challenge, Soccer Net Challenges 2023. AIBrain Asia has been developing robotic AI such as Tyche, Talking Robot AI and Gretchen, Humanoid AI. In addition, we provide bestseller AI training program for non-AI professionals including Udemy Online: Automated Machine Learning for Beginners (Google & Apple), Bestseller, Udemy, 60,829 students, Dec 2023 Gretchen: Open Humanoid AI Platform. Beta Launch: January.

BotGPT is a 24/7 custom AI chatbot assistant for websites. It offers a data-driven ChatGPT that allows users to create virtual assistants from their own data. Users can easily upload files or crawl their website to start asking questions and deploy a custom chatbot on their website within minutes. The platform provides a simple and efficient way to enhance customer engagement through AI-powered chatbots.

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.

The website displays a '404 - Page not found' error message, indicating that the requested page does not exist or has been moved. It seems to be a standard error page that users encounter when they try to access a non-existent or relocated webpage.

Wonderway is an AI Sales Coach and Sales Training Platform that uses AI 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. Wonderway's AI technology understands where sales teams need help and provides recommendations for improvement, making it a valuable tool for sales professionals.

WTRI is an AI application that offers FutureView™, a suite of tools designed to help individuals and businesses rehearse their future scenarios in a virtual environment. By leveraging cognitive agility assessment, event generation, modeling, and virtual world platforms, WTRI aims to assist users in making agile decisions and adapting to rapidly changing business environments. With a focus on risk management and outcome optimization, WTRI provides a unique approach to strategic planning and preparedness.

AnyGPT is a unified multimodal language model that utilizes discrete representations for processing various modalities like speech, text, images, and music. It aligns the modalities for intermodal conversions and text processing. AnyInstruct dataset is constructed for generative models. The model proposes a generative training scheme using Next Token Prediction task for training on a Large Language Model (LLM). It aims to compress vast multimodal data on the internet into a single model for emerging capabilities. The tool supports tasks like text-to-image, image captioning, ASR, TTS, text-to-music, and music captioning.

Cambrian-1 is a fully open project focused on exploring multimodal Large Language Models (LLMs) with a vision-centric approach. It offers competitive performance across various benchmarks with models at different parameter levels. The project includes training configurations, model weights, instruction tuning data, and evaluation details. Users can interact with Cambrian-1 through a Gradio web interface for inference. The project is inspired by LLaVA and incorporates contributions from Vicuna, LLaMA, and Yi. Cambrian-1 is licensed under Apache 2.0 and utilizes datasets and checkpoints subject to their respective original licenses.

CIFAR-10 Airbench is a project offering fast and stable training baselines for CIFAR-10 dataset, facilitating machine learning research. It provides easily runnable PyTorch scripts for training neural networks with high accuracy levels. The methods used in this project aim to accelerate research on fundamental properties of deep learning. The project includes GPU-accelerated dataloader for custom experiments and trainings, and can be used for data selection and active learning experiments. The training methods provided are faster than standard ResNet training, offering improved performance for research projects.

AICIty-reID 2020 is a repository containing the 1st Place submission to AICity Challenge 2020 re-id track by Baidu-UTS. It includes models trained on Paddlepaddle and Pytorch, with performance metrics and trained models provided. Users can extract features, perform camera and direction prediction, and access related repositories for drone-based building re-id, vehicle re-ID, person re-ID baseline, and person/vehicle generation. Citations are also provided for research purposes.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Next-Token Prediction is a language model tool that allows users to create high-quality predictions for the next word, phrase, or pixel based on a body of text. It can be used as an alternative to well-known decoder-only models like GPT and Mistral. The tool provides options for simple usage with built-in data bootstrap or advanced customization by providing training data or creating it from .txt files. It aims to simplify methodologies, provide autocomplete, autocorrect, spell checking, search/lookup functionalities, and create pixel and audio transformers for various prediction formats.

Efficient Foundation Model Survey is a comprehensive analysis of resource-efficient large language models (LLMs) and multimodal foundation models. The survey covers algorithmic and systemic innovations to support the growth of large models in a scalable and environmentally sustainable way. It explores cutting-edge model architectures, training/serving algorithms, and practical system designs. The goal is to provide insights on tackling resource challenges posed by large foundation models and inspire future breakthroughs in the field.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

Vision-LLM-Alignment is a repository focused on implementing alignment training for visual large language models (LLMs), including SFT training, reward model training, and PPO/DPO training. It supports various model architectures and provides datasets for training. The repository also offers benchmark results and installation instructions for users.

The 'fms-fsdp' repository is a companion to the Foundation Model Stack, providing a (pre)training example to efficiently train FMS models, specifically Llama2, using native PyTorch features like FSDP for training and SDPA implementation of Flash attention v2. It focuses on leveraging FSDP for training efficiently, not as an end-to-end framework. The repo benchmarks training throughput on different GPUs, shares strategies, and provides installation and training instructions. It trained a model on IBM curated data achieving high efficiency and performance metrics.

llm-analysis is a tool designed for Latency and Memory Analysis of Transformer Models for Training and Inference. It automates the calculation of training or inference latency and memory usage for Large Language Models (LLMs) or Transformers based on specified model, GPU, data type, and parallelism configurations. The tool helps users to experiment with different setups theoretically, understand system performance, and optimize training/inference scenarios. It supports various parallelism schemes, communication methods, activation recomputation options, data types, and fine-tuning strategies. Users can integrate llm-analysis in their code using the `LLMAnalysis` class or use the provided entry point functions for command line interface. The tool provides lower-bound estimations of memory usage and latency, and aims to assist in achieving feasible and optimal setups for training or inference.

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.

The STM32 AI model zoo is a collection of reference machine learning models optimized to run on STM32 microcontrollers. It provides a large collection of application-oriented models ready for re-training, scripts for easy retraining from user datasets, pre-trained models on reference datasets, and application code examples generated from user AI models. The project offers training scripts for transfer learning or training custom models from scratch. It includes performances on reference STM32 MCU and MPU for float and quantized models. The project is organized by application, providing step-by-step guides for training and deploying models.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

NineRec is a benchmark dataset suite for evaluating transferable recommendation models. It provides datasets for pre-training and transfer learning in recommender systems, focusing on multimodal and foundation model tasks. The dataset includes user-item interactions, item texts in multiple languages, item URLs, and raw images. Researchers can use NineRec to develop more effective and efficient methods for pre-training recommendation models beyond end-to-end training. The dataset is accompanied by code for dataset preparation, training, and testing in PyTorch environment.

LLamaTuner is a repository for the Efficient Finetuning of Quantized LLMs project, focusing on building and sharing instruction-following Chinese baichuan-7b/LLaMA/Pythia/GLM model tuning methods. The project enables training on a single Nvidia RTX-2080TI and RTX-3090 for multi-round chatbot training. It utilizes bitsandbytes for quantization and is integrated with Huggingface's PEFT and transformers libraries. The repository supports various models, training approaches, and datasets for supervised fine-tuning, LoRA, QLoRA, and more. It also provides tools for data preprocessing and offers models in the Hugging Face model hub for inference and finetuning. The project is licensed under Apache 2.0 and acknowledges contributions from various open-source contributors.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

PyTorch Forecasting is a PyTorch-based package for time series forecasting with state-of-the-art network architectures. It offers a high-level API for training networks on pandas data frames and utilizes PyTorch Lightning for scalable training on GPUs and CPUs. The package aims to simplify time series forecasting with neural networks by providing a flexible API for professionals and default settings for beginners. It includes a timeseries dataset class, base model class, multiple neural network architectures, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. PyTorch Forecasting is built on pytorch-lightning for easy training on various hardware configurations.

Ce GPT spécialisé en Droit du Travail vous aide dans la gestion des périodes d’essai de vos salariés, en France en 2024⭐WARNING : consultez un juriste ou un avocat spécialisé pour valider ses réponses⭐ #RH #droitdutravail #périodedessai

Advises on labor relations policies, ensuring compliance and harmony.

Experto en asesoramiento jurídico laboral español basado en leyes vigentes 2024

Asistente experto en derecho laboral mexicano, ofrece asesoría legal en español.

Experto en derecho laboral español.

Legal expert in reviewing influencer agreement (Powered by LegalNow, ai.legalnow.xyz)

A guide on your side to help navigate the challenges and complexities of work.

Expert in baby sleep advice, offering practical tips and empathetic support.

Provides emergency training assistance with a focus on safety and clear guidelines.

An expert on EMT roles, emergency services, and training, with a medical tone.

Dr. Tiffany Love's open source AI boyfriend trained on my Ex's training data he collected during our relationship and filtered to be less of a, well you know

New Zealand HR assistant with a focus on local practices.

Guides companies to adhere to regulatory standards through training.

Expert in European Sustainability Reporting Standards (ESRS). Trained on official documentation as well as expert consultants across all sectors. Includes voluntary standards.

I think and respond like a dog, offering playful insights on dog behaviors.

競馬学習に然点を当てたGPT、実用的で直接的な情報を提供。

Inclusive relationship guide and sexual education instructor, knowledgeable in queer and kink cultures. Member of the Hipster Energy Team. https://hipster.energy/team

This chatbot answers questions and provides guidance on how the Army trains to compete, fight, and win, ensuring individuals are masters of their craft.

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

Explains clinical training at Tokamachi Hospital.