Best AI tools for< Ev Technician >

EV PEDIA is an AI-powered search engine and application designed to provide comprehensive information and assistance related to electric vehicles (EVs). The platform offers a one-stop solution for users to explore, manage, and stay updated on all aspects of electric cars, from vehicle recommendations and charging station locations to the latest models and industry trends. With a personalized AI agent, users can ask questions and receive optimized answers tailored to their specific needs and situations. EV PEDIA also features curated content, news updates, and a community platform for users to engage with creators and experts in the EV industry.

42dot is a mobility AI company that focuses on software-defined vehicles to shape the future of transportation. They use software and AI technology to solve mobility issues, aiming to create a world where everything operates autonomously and seamlessly. The company develops solutions optimized for SDVs and businesses based on software and AI, including Software-Defined Vehicle and Software-Defined Fleet. Their goal is to lead the mass adoption of autonomous mobility services through the TAP! platform and create Autonomous EVs for safer and innovative transportation experiences.

EV Intersection is a website dedicated to helping users find their next electric vehicle. The site provides detailed information on various electric vehicle models, including specifications such as range, price, motor type, acceleration, and horsepower. Users can easily compare different electric vehicles and make informed decisions about their next purchase.

CEREBRUMX is an AI-powered platform that offers preventive car maintenance telematics solutions for various industries such as fleet management, vehicle service contracts, electric vehicles, smart cities, and media. The platform provides data insights and features like driver safety, EV charging, predictive maintenance, roadside assistance, and traffic flow management. CEREBRUMX aims to optimize fleet operations, enhance efficiency, and deliver high-value impact to customers through real-time connected vehicle data insights.

InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) based on InternLM2-7B excelling in free-form text-image composition and comprehension. It boasts several amazing capabilities and applications: * **Free-form Interleaved Text-Image Composition** : InternLM-XComposer2 can effortlessly generate coherent and contextual articles with interleaved images following diverse inputs like outlines, detailed text requirements and reference images, enabling highly customizable content creation. * **Accurate Vision-language Problem-solving** : InternLM-XComposer2 accurately handles diverse and challenging vision-language Q&A tasks based on free-form instructions, excelling in recognition, perception, detailed captioning, visual reasoning, and more. * **Awesome performance** : InternLM-XComposer2 based on InternLM2-7B not only significantly outperforms existing open-source multimodal models in 13 benchmarks but also **matches or even surpasses GPT-4V and Gemini Pro in 6 benchmarks** We release InternLM-XComposer2 series in three versions: * **InternLM-XComposer2-4KHD-7B** 🤗: The high-resolution multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _High-resolution understanding_ , _VL benchmarks_ and _AI assistant_. * **InternLM-XComposer2-VL-7B** 🤗 : The multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _VL benchmarks_ and _AI assistant_. **It ranks as the most powerful vision-language model based on 7B-parameter level LLMs, leading across 13 benchmarks.** * **InternLM-XComposer2-VL-1.8B** 🤗 : A lightweight version of InternLM-XComposer2-VL based on InternLM-1.8B. * **InternLM-XComposer2-7B** 🤗: The further instruction tuned VLLM for _Interleaved Text-Image Composition_ with free-form inputs. Please refer to Technical Report and 4KHD Technical Reportfor more details.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

Implementation of the general framework for AMIE, from the paper Towards Conversational Diagnostic AI, out of Google Deepmind. This repository provides a Pytorch implementation of the AMIE framework, aimed at enabling conversational diagnostic AI. It is a work in progress and welcomes collaboration from individuals with a background in deep learning and an interest in medical applications.

Clipboard Conqueror is a multi-platform omnipresent copilot alternative. Currently requiring a kobold united or openAI compatible back end, this software brings powerful LLM based tools to any text field, the universal copilot you deserve. It simply works anywhere. No need to sign in, no required key. Provided you are using local AI, CC is a data secure alternative integration provided you trust whatever backend you use. *Special thank you to the creators of KoboldAi, KoboldCPP, llamma, openAi, and the communities that made all this possible to figure out.

Evalverse is an open-source project designed to support Large Language Model (LLM) evaluation needs. It provides a standardized and user-friendly solution for processing and managing LLM evaluations, catering to AI research engineers and scientists. Evalverse supports various evaluation methods, insightful reports, and no-code evaluation processes. Users can access unified evaluation with submodules, request evaluations without code via Slack bot, and obtain comprehensive reports with scores, rankings, and visuals. The tool allows for easy comparison of scores across different models and swift addition of new evaluation tools.

NeoCodeium is a free AI completion plugin powered by Codeium, designed for Neovim users. It aims to provide a smoother experience by eliminating flickering suggestions and allowing for repeatable completions using the `.` key. The plugin offers performance improvements through cache techniques, displays suggestion count labels, and supports Lua scripting. Users can customize keymaps, manage suggestions, and interact with the AI chat feature. NeoCodeium enhances code completion in Neovim, making it a valuable tool for developers seeking efficient coding assistance.

Awesome-Lists is a curated list of awesome lists across various domains of computer science and beyond, including programming languages, web development, data science, and more. It provides a comprehensive index of articles, books, courses, open source projects, and other resources. The lists are organized by topic and subtopic, making it easy to find the information you need. Awesome-Lists is a valuable resource for anyone looking to learn more about a particular topic or to stay up-to-date on the latest developments in the field.

Awesome-Lists is a curated index of selected resources spanning various fields including programming languages and theories, web and frontend development, server-side development and infrastructure, cloud computing and big data, data science and artificial intelligence, product design, etc. It includes articles, books, courses, examples, open-source projects, and more. The repository categorizes resources according to the knowledge system of different domains, aiming to provide valuable and concise material indexes for readers. Users can explore and learn from a wide range of high-quality resources in a systematic way.

LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

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.

An EV Charging Assistant for new and expert EV owners.

Comprehensive expert on all things electric vehicles, blending simplicity with depth.

电动汽车制造专家，解答与电动车相关的所有疑惑。

Delivers consistent, tailored EV charging site scores.

Expert tutor in Evolutionary Culturology. Engaging, educational, entertaining, & interactive!

Your go-to source for Tesla and EV knowledge.

Back-of-envelope estimations for almost everything: market sizes, regional EV adoption, and political support demographics.

A Pokémon competitive build expert, sourcing data from Smogon for single and double battles.