Best AI tools for< V2x Developer >

Mobility Engineering is a website that provides news, articles, and resources on the latest developments in mobility technology. The site covers a wide range of topics, including autonomous vehicles, connected cars, electric vehicles, and more. Mobility Engineering is a valuable resource for anyone interested in staying up-to-date on the latest trends in mobility technology.

Retro AIM Server is an instant messaging server that revives AOL Instant Messenger clients from the 2000s. It supports Windows AIM client versions 5.0-5.9, away messages, buddy icons, buddy list, chat rooms, instant messaging, user profiles, blocking/visibility toggle/idle notification, and warning. The Management API provides functionality for administering the server, including listing users, creating users, changing passwords, and listing active sessions.

Aiogram Dialog is a framework for developing interactive messages and menus in Telegram bots, inspired by Android SDK. It allows splitting data retrieval, rendering, and action processing, creating reusable widgets, and designing bots with a focus on user experience. The tool supports rich text rendering, automatic message updating, multiple dialog stacks, inline keyboard widgets, stateful widgets, various button layouts, media handling, transitions between windows, and offline HTML-preview for messages and transitions diagram.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

This repository is a curated list of awesome public object detection and recognition datasets. It includes a wide range of datasets related to object detection and recognition tasks, such as general detection and recognition datasets, autonomous driving datasets, adverse weather datasets, person detection datasets, anti-UAV datasets, optical aerial imagery datasets, low-light image datasets, infrared image datasets, SAR image datasets, multispectral image datasets, 3D object detection datasets, vehicle-to-everything field datasets, super-resolution field datasets, and face detection and recognition datasets. The repository also provides information on tools for data annotation, data augmentation, and data management related to object detection tasks.

Moon Dev AI Agents for Trading is an experimental project exploring the potential of artificial financial intelligence for trading and investing research. The project aims to develop AI agents to complement and potentially replace human trading operations by addressing common trading challenges such as emotional reactions, ego-driven decisions, inconsistent execution, fatigue effects, impatience, and fear & greed cycles. The project focuses on research areas like risk control, exit timing, entry strategies, sentiment collection, and strategy execution. It is important to note that this project is not a profitable trading solution and involves substantial risk of loss.

Skyrim is a weather forecasting tool that enables users to run large weather models using consumer-grade GPUs. It provides access to state-of-the-art foundational weather models through a well-maintained infrastructure. Users can forecast weather conditions, such as wind speed and direction, by running simulations on their own GPUs or using modal volume or cloud services like s3 buckets. Skyrim supports various large weather models like Graphcast, Pangu, Fourcastnet, and DLWP, with plans for future enhancements like ensemble prediction and model quantization.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

This project is a Chinese tutorial for domestic beginners based on the AutoDL platform, providing full-process guidance for various open-source large models, including environment configuration, local deployment, and efficient fine-tuning. It simplifies the deployment, use, and application process of open-source large models, enabling more ordinary students and researchers to better use open-source large models and helping open and free large models integrate into the lives of ordinary learners faster.

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