Best AI tools for< Race Commentator >

Skillroads is a trusted AI resume maker that empowers users in their job search process. The platform offers a range of services including resume writing, editing, LinkedIn profile makeover, AI resume checker, and career tips. Skillroads leverages Artificial Intelligence to create tailored resumes, cover letters, and job matches for users. The application simplifies the job application process by providing personalized job openings from top companies and career development plans. Users can access various career services, including resume creation, cover letter writing, and interview help, to enhance their job search experience.

ConquerortheCrown is an AI-powered mentor that provides guidance and support to users. It is designed to help users achieve their goals and live a more fulfilling life. ConquerortheCrown uses a variety of AI techniques to provide personalized advice and support to users. It can help users with a variety of tasks, including setting goals, making decisions, and overcoming challenges.

NSFW Character AI is a free and unfiltered AI chatbot that allows users to create and interact with their own custom AI characters. With NSFW Character AI, you can create characters of any gender, race, or sexual orientation, and explore a wide range of topics, including sex, relationships, and other adult themes. NSFW Character AI is a great way to explore your sexuality and fantasies in a safe and private environment.

XLSCOUT is an SOC 2 Type II-compliant, AI super intelligence platform for innovation and IP. It offers a comprehensive solution from instant prior-art searches and AI-assisted ideation to drafting high-quality patents and monetizing innovation. Leveraging Large Language Models (LLMs) and Generative AI, XLSCOUT provides high-quality IP data for patent search and analytics, automates R&D and IP workflows, and helps users stay ahead in the innovation and IP race. The platform ensures top security standards for protecting client data and complies with various industry standards like SOC 2, PCI, ISO, NIST, GDPR, CCPA, HIPAA, and CSA STAR.

The Dwarf Name Generator is an AI-powered tool that generates unique and authentic dwarven names for role-playing games. It offers two modes: Soldier Mode for quick name generation and Hero Mode for detailed character profiles. The generator draws from a vast ocean of linguistic data, historical records, and creative literature to create names that are not only unique but also deeply rooted in the fantasy genre's most cherished traditions. It is designed to enhance the role-playing experience by providing players with names that resonate with their character's race, class, and personal journey.

Empathy is a comprehensive support system for loss, helping families navigate life's most challenging moments. The platform offers personalized Care Plans, time-saving tools, grief support resources, and assistance with probate processes. Empathy aims to reduce stress and financial burden for families dealing with loss by providing emotional and logistical support. The application is designed to support individuals and families of all backgrounds, regardless of age, race, religion, ethnicity, gender identity, or sexual orientation.

Simulator Controller is a modular administration and controller application for Sim Racing, featuring a comprehensive plugin automation framework for external controller hardware. It includes voice chat capable Assistants like Virtual Race Engineer, Race Strategist, Race Spotter, and Driving Coach. The tool offers features for setup, strategy development, monitoring races, and more. Developed in AutoHotkey, it supports various simulation games and integrates with third-party applications for enhanced functionality.

KaibanJS is a JavaScript-native framework for building multi-agent AI systems. It enables users to create specialized AI agents with distinct roles and goals, manage tasks, and coordinate teams efficiently. The framework supports role-based agent design, tool integration, multiple LLMs support, robust state management, observability and monitoring features, and a real-time agentic Kanban board for visualizing AI workflows. KaibanJS aims to empower JavaScript developers with a user-friendly AI framework tailored for the JavaScript ecosystem, bridging the gap in the AI race for non-Python developers.

llmcord.py enables collaborative LLM prompting in your Discord server. It works with practically any LLM, remote or locally hosted. ### Features ### Reply-based chat system Just @ the bot to start a conversation and reply to continue. Build conversations with reply chains! You can do things like: - Build conversations together with your friends - "Rewind" a conversation simply by replying to an older message - @ the bot while replying to any message in your server to ask a question about it Additionally: - Back-to-back messages from the same user are automatically chained together. Just reply to the latest one and the bot will see all of them. - You can seamlessly move any conversation into a thread. Just create a thread from any message and @ the bot inside to continue. ### Choose any LLM Supports remote models from OpenAI API, Mistral API, Anthropic API and many more thanks to LiteLLM. Or run a local model with ollama, oobabooga, Jan, LM Studio or any other OpenAI compatible API server. ### And more: - Supports image attachments when using a vision model - Customizable system prompt - DM for private access (no @ required) - User identity aware (OpenAI API only) - Streamed responses (turns green when complete, automatically splits into separate messages when too long, throttled to prevent Discord ratelimiting) - Displays helpful user warnings when appropriate (like "Only using last 20 messages", "Max 5 images per message", etc.) - Caches message data in a size-managed (no memory leaks) and per-message mutex-protected (no race conditions) global dictionary to maximize efficiency and minimize Discord API calls - Fully asynchronous - 1 Python file, ~200 lines of code

Atlantis is an extensive Java framework based on JBWAPI 2.1.0, designed to simplify bot development for Starcraft. It provides clean and re-usable code, supports all three races with a focus on Terran, automates various tasks like modifying bwapi.ini and managing economy, includes tests and mini-maps, offers customizable build orders, scouts enemy bases, responds to threats, and more. The framework aims to streamline bot development by handling common tasks and providing advanced features for unit selection and decision-making.

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.

Koordinator is a QoS based scheduling system for hybrid orchestration workloads on Kubernetes. It aims to improve runtime efficiency and reliability of latency sensitive workloads and batch jobs, simplify resource-related configuration tuning, and increase pod deployment density. It enhances Kubernetes user experience by optimizing resource utilization, improving performance, providing flexible scheduling policies, and easy integration into existing clusters.

Large Language Models Play StarCraft II is a project that explores the capabilities of large language models (LLMs) in playing the game StarCraft II. The project introduces TextStarCraft II, a textual environment for the game, and a Chain of Summarization method for analyzing game information and making strategic decisions. Through experiments, the project demonstrates that LLM agents can defeat the built-in AI at a challenging difficulty level. The project provides benchmarks and a summarization approach to enhance strategic planning and interpretability in StarCraft II gameplay.

LLM Hallucination Index - RAG Special is a comprehensive evaluation of large language models (LLMs) focusing on context length and open vs. closed-source attributes. The index explores the impact of context length on model performance and tests the assumption that closed-source LLMs outperform open-source ones. It also investigates the effectiveness of prompting techniques like Chain-of-Note across different context lengths. The evaluation includes 22 models from various brands, analyzing major trends and declaring overall winners based on short, medium, and long context insights. Methodologies involve rigorous testing with different context lengths and prompting techniques to assess models' abilities in handling extensive texts and detecting hallucinations.

LLM price compass is an open-source tool for comparing inference costs on different GPUs across various cloud providers. It collects benchmark data to help users select the right GPU, cloud, and provider for their models. The project aims to provide insights into fixed per token costs from different providers, aiding in decision-making for model deployment.

llmcord.py is a tool that allows users to chat with Language Model Models (LLMs) directly in Discord. It supports various LLM providers, both remote and locally hosted, and offers features like reply-based chat system, choosing any LLM, support for image and text file attachments, customizable system prompt, private access via DM, user identity awareness, streamed responses, warning messages, efficient message data caching, and asynchronous operation. The tool is designed to facilitate seamless conversations with LLMs and enhance user experience on Discord.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

Holistic AI is an open-source library dedicated to assessing and improving the trustworthiness of AI systems. It focuses on measuring and mitigating bias, explainability, robustness, security, and efficacy in AI models. The tool provides comprehensive metrics, mitigation techniques, a user-friendly interface, and visualization tools to enhance AI system trustworthiness. It offers documentation, tutorials, and detailed installation instructions for easy integration into existing workflows.

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.

llmcord is a Discord bot that transforms Discord into a collaborative LLM frontend, allowing users to interact with various LLM models. It features a reply-based chat system that enables branching conversations, supports remote and local LLM models, allows image and text file attachments, offers customizable personality settings, and provides streamed responses. The bot is fully asynchronous, efficient in managing message data, and offers hot reloading config. With just one Python file and around 200 lines of code, llmcord provides a seamless experience for engaging with LLMs on Discord.

The RISE Journal Club is a bi-weekly reading group that provides a friendly environment for discussing state-of-the-art papers in medical image analysis, AI, and computer vision. The club aims to enhance critical and design thinking skills essential for researchers. Moderators introduce papers for discussion on various topics such as registration, segmentation, federated learning, fairness, and reinforcement learning. The club covers papers from machine and deep learning communities, offering a broad overview of cutting-edge methods.

Phidata is a framework for building AI Assistants with memory, knowledge, and tools. It enables LLMs to have long-term conversations by storing chat history in a database, provides them with business context by storing information in a vector database, and enables them to take actions like pulling data from an API, sending emails, or querying a database. Memory and knowledge make LLMs smarter, while tools make them autonomous.

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features include: * Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 70+ datasets with about 400,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. * Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. * Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue-type prompt templates, to easily stimulate the maximum performance of various models. * Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! * Experiment management and reporting mechanism: Use config files to fully record each experiment, and support real-time reporting of results.

The collection is actively updated with the help of an internal literature search engine.

AIStore is a lightweight object storage system designed for AI applications. It is highly scalable, reliable, and easy to use. AIStore can be deployed on any commodity hardware, and it can be used to store and manage large datasets for deep learning and other AI applications.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

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。

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Expert Homebrew DND tool for crafting detailed monsters, items, spells, races, classes with rich lore, stats, and habitats. V0.9: The Description Update - Added reactions, equipment and more to monster creation as well as more detail.