Hidden Door is an interactive fan experience platform that allows users to play, share, and remix their favorite books, movies, and TV shows. With Hidden Door, users can create their own universes and embark on weird, scary, romantic, or even totally non-weird adventures. Users can explore the Wizard of Oz and Pride & Prejudice during the closed alpha, and there's much more to come. Hidden Door gives users the worlds, tropes, mechanics, cards, visuals, and of course the always-on Narrator. What kind of universe users create is totally up to them and their friends.

Offrs.com is an AI-powered lead generation platform designed for real estate agents. The platform leverages predictive analytics and big data to help agents generate and convert listing leads efficiently. By targeting homeowners directly through popular channels like Google, Offrs.com provides agents with a steady stream of high-quality leads. The platform focuses on predictive sellers, in-market leads, and lead capture to ensure agents have a strong pipeline of potential clients. With a guarantee on the number of leads per month and a territory builder feature, Offrs.com aims to help agents save time and money while maximizing their listing opportunities.

Josh.ai is an advanced AI control system for the smart home that utilizes natural interfaces like voice and touch to orchestrate technology in all aspects of the home. It aims to inspire, embolden, and delight users by providing an exciting and effortless living experience. Josh.ai is evolving to deliver its supercharged JoshGPT assistant at home and on-the-go, offering seamless integration with connected devices for smart home control and customization. With a focus on privacy, innovation, beauty, peace, comfort, flexibility, simplicity, security, delight, time, wellness, intelligence, and magic, Josh.ai is designed to empower every family member with intuitive control and intelligent assistance.

Tonkean is an enterprise intake orchestration platform powered by AI. It helps businesses automate and streamline their intake processes, such as procurement, legal, and more. Tonkean's AI-powered features include an intelligent AI Front Door, guided intake, request status tracker, and custom apps for ops teams. With Tonkean, businesses can increase adoption, efficiency, and compliance in their intake processes.

Memoirist is an AI-assisted service that helps users self-author heartfelt memoirs and biographies of their loved ones. The platform prompts users with expert questions to uncover deep and meaningful stories effortlessly. It turns interviews into beautifully crafted memoirs, handles formatting and design, and delivers a printed book straight to the user's door. Memoirist aims to help families stay connected, preserve their history, and create lasting memories for themselves and future generations.

Sleek AI is an AI-powered marketing automation platform that helps businesses streamline their marketing operations. By automating content creation, publishing, campaign management, and optimization, Sleek AI aims to bring customers to your door easier, faster, and cheaper. With features like automated content generation, personalized messaging, and campaign optimization, Sleek AI offers a user-friendly solution for businesses looking to enhance their marketing efforts. The platform is designed to save time and money while improving marketing performance across all channels and target audiences.

MAVIS (Math Visual Intelligent System) is an AI-driven application that allows users to analyze visual data such as images and generate interactive answers based on them. It can perform complex mathematical calculations, solve programming tasks, and create professional graphics. MAVIS supports Python for coding and frameworks like Matplotlib, Plotly, Seaborn, Altair, NumPy, Math, SymPy, and Pandas. It is designed to make projects more efficient and professional.

Ollama GUI is a web interface for ollama.ai, a tool that enables running Large Language Models (LLMs) on your local machine. It provides a user-friendly platform for chatting with LLMs and accessing various models for text generation. Users can easily interact with different models, manage chat history, and explore available models through the web interface. The tool is built with Vue.js, Vite, and Tailwind CSS, offering a modern and responsive design for seamless user experience.

PyWhy-LLM is an innovative library that integrates Large Language Models (LLMs) into the causal analysis process, empowering users with knowledge previously only available through domain experts. It seamlessly augments existing causal inference processes by suggesting potential confounders, relationships between variables, backdoor sets, front door sets, IV sets, estimands, critiques of DAGs, latent confounders, and negative controls. By leveraging LLMs and formalizing human-LLM collaboration, PyWhy-LLM aims to enhance causal analysis accessibility and insight.

The LandingLens Python library contains the LandingLens development library and examples that show how to integrate your app with LandingLens in a variety of scenarios. The library allows users to acquire images from different sources, run inference on computer vision models deployed in LandingLens, and provides examples in Jupyter Notebooks and Python apps for various tasks such as object detection, home automation, satellite image analysis, license plate detection, and streaming video analysis.

Lovelaice is an AI-powered assistant for your terminal and editor. It can run bash commands, search the Internet, answer general and technical questions, complete text files, chat casually, execute code in various languages, and more. Lovelaice is configurable with API keys and LLM models, and can be used for a wide range of tasks requiring bash commands or coding assistance. It is designed to be versatile, interactive, and helpful for daily tasks and projects.

An asyncio-based scheduling framework designed for execution of periodic tasks with integrated support for dependency injection, enabling efficient and flexible task management. Aioclock is 100% async, light, fast, and resource-friendly. It offers features like task scheduling, grouping, trigger definition, easy syntax, Pydantic v2 validation, and upcoming support for running the task dispatcher on a different process and backend support for horizontal scaling.

Nesa is a tool that allows users to run on-prem AI for a fraction of the cost through a blind API. It provides blind privacy, zero latency on protected inference, wide model coverage, cost savings compared to cloud and on-prem AI, RAG support, and ChatGPT compatibility. Nesa achieves blind AI through Equivariant Encryption (EE), a new security technology that provides complete inference encryption with no additional latency. EE allows users to perform inference on neural networks without exposing the underlying data, preserving data privacy and security.

Craftium is an open-source platform based on the Minetest voxel game engine and the Gymnasium and PettingZoo APIs, designed for creating fast, rich, and diverse single and multi-agent environments. It allows for connecting to Craftium's Python process, executing actions as keyboard and mouse controls, extending the Lua API for creating RL environments and tasks, and supporting client/server synchronization for slow agents. Craftium is fully extensible, extensively documented, modern RL API compatible, fully open source, and eliminates the need for Java. It offers a variety of environments for research and development in reinforcement learning.

Neural Speed is an innovative library designed to support the efficient inference of large language models (LLMs) on Intel platforms through the state-of-the-art (SOTA) low-bit quantization powered by Intel Neural Compressor. The work is inspired by llama.cpp and further optimized for Intel platforms with our innovations in NeurIPS' 2023

Azure OpenAI Service is a central capability with Azure API Management, providing guidance and tools for organizations to implement Azure OpenAI in a production environment with an emphasis on cost control, secure access, and usage monitoring. It includes infrastructure-as-code templates, CI/CD pipelines, secure access management, usage monitoring, load balancing, streaming requests, and end-to-end samples like ChatApp and Azure Dashboards.

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.

VideoTuna is a codebase for text-to-video applications that integrates multiple AI video generation models for text-to-video, image-to-video, and text-to-image generation. It provides comprehensive pipelines in video generation, including pre-training, continuous training, post-training, and fine-tuning. The models in VideoTuna include U-Net and DiT architectures for visual generation tasks, with upcoming releases of a new 3D video VAE and a controllable facial video generation model.

Postgres.new is an in-browser Postgres sandbox with AI assistance that allows users to spin up unlimited Postgres databases directly in the browser. Each database comes with a large language model (LLM) enabling features like drag-and-drop CSV import, report generation, chart creation, and database diagram building. The tool utilizes PGlite, a WASM version of Postgres, to run databases in the browser and store data in IndexedDB for persistence. The monorepo includes a frontend built with Next.js and a backend serving S3-backed PGlite databases over the PG wire protocol using pg-gateway.

MisguidedAttention is a collection of prompts designed to challenge the reasoning abilities of large language models by presenting them with modified versions of well-known thought experiments, riddles, and paradoxes. The goal is to assess the logical deduction capabilities of these models and observe any shortcomings or fallacies in their responses. The repository includes a variety of prompts that test different aspects of reasoning, such as decision-making, probability assessment, and problem-solving. By analyzing how language models handle these challenges, researchers can gain insights into their reasoning processes and potential biases.

Okay, here is a JSON object with the requested information about the awesome-cuda-tensorrt-fpga repository:

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.

Firma Grupa Magnum specjalizuje się w sprzedaży akcesoriów do ciepłego montażu okien i drzwi. Oferują bogaty wybór narzędzi i akcesoriów, które są niezbędne do prawidłowego montażu stolarki okiennej i drzwiowej.

Expert carpentry advice with no external sources cited

door Chris van Vleuten - chrisvanvleuten.nl

Crack open the door to your future. (Partner tip: use the iPhone app for voice chat)

Create custom stickers of your furry friends, shipped right to your door!

I'll turn your crazy artwork ideas into posters, shipped straight to your door.

Uncle Donnie reviews your woodworking with wisdom and nostalgia.

Shalom! Ask me about carpentry and design in Israel. Start with 'Find', 'Show', or 'Tell me about'.