Best AI tools for< Meter Iot Devices >

Forwrd AI is an AI application that supercharges your go-to-market strategy by providing a comprehensive product platform for data integration, analysis, predictive modeling, and data activation. It offers various use cases such as marketing lead scoring, PQL scoring, account scoring, warmth meter, sales SAL prediction, opportunity scoring, territory management, customer success, churn prediction, and upsell prediction. With Forwrd AI, users can build and automate predictive AI models quickly without the need for technical expertise. The platform ensures data readiness for predictions, streamlines model creation and deployment, and leverages all available data points for accurate insights. Forwrd AI is trusted by industry leaders and helps users optimize marketing strategies, accelerate sales, and enhance customer retention through advanced BI, predictive insights, and analytics.

AI Storyboards is an AI tool that allows users to create storyboards using artificial intelligence technology. Users can generate visual storyboards for their content by leveraging advanced AI algorithms. The platform offers a user-friendly interface for creating and customizing storyboards, making it easy for users to bring their ideas to life. With AI Storyboards, users can quickly and efficiently create engaging visual content for various purposes, such as presentations, videos, and social media posts.

The Millshop Online is a specialized website offering a wide range of curtain and upholstery fabrics with unique and exclusive designs. Customers can explore a variety of fabric types, colors, and styles to create custom-made curtains and blinds. The website also provides upholstery supplies, tools, and accessories for DIY projects. With a focus on quality and British-made products, The Millshop Online aims to cater to customers looking to enhance their home interiors with premium fabrics.

OpenMeter is a real-time and scalable usage metering tool for AI, usage-based billing, infrastructure, and IoT use cases. It provides a REST API for integrations and offers client SDKs in Node.js, Python, Go, and Web. OpenMeter is licensed under the Apache 2.0 License.

AI-on-the-edge-device is a project that enables users to digitize analog water, gas, power, and other meters using an ESP32 board with a supported camera. It integrates Tensorflow Lite for AI processing, offers a small and affordable device with integrated camera and illumination, provides a web interface for administration and control, supports Homeassistant, Influx DB, MQTT, and REST API. The device captures meter images, extracts Regions of Interest (ROIs), runs them through AI for digitization, and allows users to send data to MQTT, InfluxDb, or access it via REST API. The project also includes 3D-printable housing options and tools for logfile management.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

GPT Home is a project that allows users to build their own home assistant using Raspberry Pi and OpenAI API. It serves as a guide for setting up a smart home assistant similar to Google Nest Hub or Amazon Alexa. The project integrates various components like OpenAI, Spotify, Philips Hue, and OpenWeatherMap to provide a personalized home assistant experience. Users can follow the detailed instructions provided to build their own version of the home assistant on Raspberry Pi, with optional components for customization. The project also includes system configurations, dependencies installation, and setup scripts for easy deployment. Overall, GPT Home offers a DIY solution for creating a smart home assistant using Raspberry Pi and OpenAI technology.

Humanoid-Gym is a reinforcement learning framework designed for training locomotion skills for humanoid robots, focusing on zero-shot transfer from simulation to real-world environments. It integrates a sim-to-sim framework from Isaac Gym to Mujoco for verifying trained policies in different physical simulations. The codebase is verified with RobotEra's XBot-S and XBot-L humanoid robots. It offers comprehensive training guidelines, step-by-step configuration instructions, and execution scripts for easy deployment. The sim2sim support allows transferring trained policies to accurate simulated environments. The upcoming features include Denoising World Model Learning and Dexterous Hand Manipulation. Installation and usage guides are provided along with examples for training PPO policies and sim-to-sim transformations. The code structure includes environment and configuration files, with instructions on adding new environments. Troubleshooting tips are provided for common issues, along with a citation and acknowledgment section.

Awesome MLSecOps is a curated list of open-source tools, resources, and tutorials for MLSecOps (Machine Learning Security Operations). It includes a wide range of security tools and libraries for protecting machine learning models against adversarial attacks, as well as resources for AI security, data anonymization, model security, and more. The repository aims to provide a comprehensive collection of tools and information to help users secure their machine learning systems and infrastructure.

The Synthetic-Voice-Detection-Vocoder-Artifacts repository provides the LibriSeVoc dataset containing self-vocoding samples created with six state-of-the-art vocoders to expose and exploit vocoder artifacts. It also introduces a new approach for detecting synthetic human voices by identifying signal artifacts left by neural vocoders and enhancing the RawNet2 baseline. The repository includes a paper and dataset for further reference and offers instructions for training the model and testing it in the wild.

The Microsoft AI for Earth program hosts geospatial data on Azure that is important to environmental sustainability and Earth science. This repo hosts documentation and demonstration notebooks for all the data that is managed by AI for Earth. It also serves as a "staging ground" for the Planetary Computer Data Catalog.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.

XR Animator is a video/webcam-based AI motion capture application designed for VTubing and the metaverse era. It uses machine learning solutions to detect 3D poses from a live webcam video, driving a 3D avatar as if controlled by the user's body. It supports full-body AI motion tracking, face tracking, and various XR/3D purposes. The tool can be used for VTubing, recording mocap motion, exporting motions to different formats, customizing backgrounds and scenes, and animating 3D models in other applications. It also supports AR on Android Chrome browser, AR selfie feature, and has relatively low system requirements for wide device compatibility.

Whisper Dictation is a fast, offline, privacy-focused tool for voice typing, AI voice chat, voice control, and translation. It allows hands-free operation, launching and controlling apps, and communicating with OpenAI ChatGPT or a local chat server. The tool also offers the option to speak answers out loud and draw pictures. It includes client and server versions, inspired by the Star Trek series, and is designed to keep data off the internet and confidential. The project is optimized for dictation and translation tasks, with voice control capabilities and AI image generation using stable-diffusion API.

LEADS is a lightweight embedded assisted driving system designed to simplify the development of instrumentation, control, and analysis systems for racing cars. It is written in Python and C/C++ with impressive performance. The system is customizable and provides abstract layers for component rearrangement. It supports hardware components like Raspberry Pi and Arduino, and can adapt to various hardware types. LEADS offers a modular structure with a focus on flexibility and lightweight design. It includes robust safety features, modern GUI design with dark mode support, high performance on different platforms, and powerful ESC systems for traction control and braking. The system also supports real-time data sharing, live video streaming, and AI-enhanced data analysis for driver training. LEADS VeC Remote Analyst enables transparency between the driver and pit crew, allowing real-time data sharing and analysis. The system is designed to be user-friendly, adaptable, and efficient for racing car development.

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

Awesome Green AI is a curated list of resources and tools aimed at reducing the environmental impacts of using and deploying AI. It addresses the carbon footprint of the ICT sector, emphasizing the importance of AI in reducing environmental impacts beyond GHG emissions and electricity consumption. The tools listed cover code-based tools for measuring environmental impacts, monitoring tools for power consumption, optimization tools for energy efficiency, and calculation tools for estimating environmental impacts of algorithms and models. The repository also includes leaderboards, papers, survey papers, and reports related to green AI and environmental sustainability in the AI sector.

Vivaria is a web application tool designed for running evaluations and conducting agent elicitation research. Users can interact with Vivaria using a web UI and a command-line interface. It allows users to start task environments based on METR Task Standard definitions, run AI agents, perform agent elicitation research, view API requests and responses, add tags and comments to runs, store results in a PostgreSQL database, sync data to Airtable, test prompts against LLMs, and authenticate using Auth0.

TRACE is a temporal grounding video model that utilizes causal event modeling to capture videos' inherent structure. It presents a task-interleaved video LLM model tailored for sequential encoding/decoding of timestamps, salient scores, and textual captions. The project includes various model checkpoints for different stages and fine-tuning on specific datasets. It provides evaluation codes for different tasks like VTG, MVBench, and VideoMME. The repository also offers annotation files and links to raw videos preparation projects. Users can train the model on different tasks and evaluate the performance based on metrics like CIDER, METEOR, SODA_c, F1, mAP, Hit@1, etc. TRACE has been enhanced with trace-retrieval and trace-uni models, showing improved performance on dense video captioning and general video understanding tasks.

Detects and measures information credibility. Provides a "BS Score" (0-100) based on content analysis for misinformation signs, including factual inaccuracies and sensationalist language. Real-time feedback.

Analyzes sentiments with creative, fun, and accurate emoji use.

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The Writing Metier Footnote Assistant is a specialized GPT model designed to help students efficiently create, format, and verify footnotes for their academic papers.

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Multiple Environment Threat Evaluation of Resources (METEOR)™ Space Threats and Operational Risks to Mission (STORM)™ non-profit product AI co-pilot

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I'm a search engine for jobs opportunities in the aerospace industry. DOWNLOAD YOUR CV or ENTER YOUR JOB TITLE / Je suis un moteur de recherche d'offres d'emploi, d'alternance, de stages dans le secteur de l'Aéronautique. TÉLÉCHARGER VOTRE CV ou SAISISSEZ LE TITRE DE VOTRE MÉTIER.