Best AI tools for< Inspect Aircraft >

Inspect is an open-source framework for large language model evaluations created by the UK AI Safety Institute. It provides built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can explore various solvers, tools, scorers, datasets, and models to create advanced evaluations. Inspect supports extensions for new elicitation and scoring techniques through Python packages.

Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

Ascento is an AI-powered robotics solution that enhances security by utilizing robotics and AI technology to secure assets and provide quantitative insights of premises. The application offers features such as detecting people on premises, verifying perimeter integrity, recording property lights, scanning for thermal anomalies, controlling parking lots, and checking doors and windows. Ascento provides advantages like faster threat detection with greater accuracy, cost reduction, autonomous operation, all-terrain capabilities, and comprehensive Robotics-as-a-Service solution. However, some disadvantages include the need for immediate cost-benefits, training and onboarding requirements, and potential limitations in certain weather conditions.

Neurala is a company that provides visual quality inspection software powered by AI. Their software is designed to help manufacturers improve their inspection process by reducing product defects, increasing inspection rates, and preventing production downtime. Neurala's software is flexible and can be easily retrofitted into existing production line infrastructure, without the need for AI experts or expensive capital expenditures. The company's software is used by a variety of manufacturers, including Sony, AITRIOS, and CB Insights.

Inedit is an AI-powered editor widget that enhances your ability to edit webpage content instantly. It offers features like AI and inline editing, manual mode for error correction, effortless editing of multiple elements, and the ability to inspect deeper structures of a webpage. The tool is powered by OpenAI GPT Models, providing unparalleled flexibility and advanced technology to streamline workflow and enhance productivity.

LangChain is a framework for developing applications powered by large language models (LLMs). It simplifies every stage of the LLM application lifecycle, including development, productionization, and deployment. LangChain consists of open-source libraries such as langchain-core, langchain-community, and partner packages. It also includes LangGraph for building stateful agents and LangSmith for debugging and monitoring LLM applications.

Fyusion is an AI-powered application that specializes in vehicle damage detection through advanced technology and deep AI understanding. It offers stunning 3D vehicle imagery and actionable insights for a comprehensive view of the vehicle's condition. Fyusion's technology revolutionizes the automotive industry by providing comprehensive condition reporting and interactive 3D imaging solutions. The application is utilized in various sectors, including wholesale, dealerships, and fleet operators, to enhance decision-making processes and streamline vehicle inspections.

Nanotronics is an AI-powered platform for autonomous manufacturing that revolutionizes the industry through automated optical inspection solutions. It combines computer vision, AI, and optical microscopy to ensure high-volume production with higher yields, less waste, and lower costs. Nanotronics offers products like nSpec and nControl, leading the paradigm shift in process control and transforming the entire manufacturing stack. With over 150 patents, 250+ deployments, and offices in multiple locations, Nanotronics is at the forefront of innovation in the manufacturing sector.

Pixian.AI is an AI tool that specializes in removing backgrounds from images. It offers a free service with no signup required, as well as a paid option for higher resolution images. The tool uses powerful GPUs and multi-core CPUs to analyze images and provide high-quality results. Pixian.AI aims to provide efficient and cost-effective AI image processing solutions to users, with a focus on quality and value.

Aviso is an end-to-end AI revenue platform that offers conversational intelligence and RevOps sales leadership bootcamp. It provides a single platform for accurate, prescriptive, and repeatable revenue execution by consolidating underperforming sales apps with an integrated AI platform. Aviso's AI Brain delivers personalized insights using AI Chief of Staff and bespoke Agentic workflows. The platform helps in extracting insights, monitoring deal progression, and running analytics to optimize rep performance and prioritize GTM activities.

Saara Inc offers AI tools for eCommerce to maximize profits by reducing returns, cutting costs, boosting loyalty, and increasing profits through AI-powered automation and smart agents. Their solutions focus on tackling key challenges in eCommerce such as high return rates, rising operational costs, and customer churn. By improving loyalty, reducing expenses, and streamlining processes with smart automation and AI agents, Saara Inc enables businesses to achieve sustainable growth and long-term profitability.

Scratchpad is an AI-powered workspace designed for sales teams to streamline their sales processes and enhance productivity. It offers a range of features such as AI Sales Assistant, Pipeline Management, Deal Rooms, Automations & Enablement, and Deal Inspection. With Scratchpad, sales teams can benefit from real-time notes, call summaries, and transcripts, as well as AI prompts for sales processes. The application aims to simplify sales execution, improve CRM hygiene, and provide better deal control through automation and in-line coaching.

People.ai is an AI-powered platform that revolutionizes the way businesses approach revenue generation. It offers a holistic solution combining automated activity capture with account and opportunity management to create a unified Go-To-Market (GTM) motion. The platform leverages generative AI to automate manual tasks, inspect account and deal health, and provide prescriptive coaching recommendations. People.ai helps businesses modernize by providing complete, accurate, and enriched data complemented by AI-driven insights to enhance sales team efficiency and effectiveness.

Slicker is an AI-powered tool designed to recover failed subscription payments and maximize subscription revenue for businesses. It uses a proprietary AI engine to process each failing payment individually, converting past due invoices into revenue. With features like payment recovery on auto-pilot, state-of-the-art machine learning model, lightning-fast setup, in-depth payment analytics, and enterprise-grade security, Slicker offers a comprehensive solution to reduce churn and boost revenue. The tool is fully transparent, allowing users to inspect and review every action taken by the AI engine. Slicker seamlessly integrates with popular billing and payment platforms, making it easy to implement and start seeing results quickly.

Inspecti.App is a game-changing property inspection and reporting generator designed to revolutionize the way Inventory Clerks conduct property inspections. By leveraging AI technology, Inspecti simplifies and automates the inspection process, saving time and improving accuracy. The platform eliminates manual work, enhances efficiency, and delivers comprehensive inspection reports in a fraction of the time compared to traditional methods. With features like AI-driven object detection, same-day report delivery, and tailored portfolio management, Inspecti empowers users to streamline property inspections and reduce operational costs. The application prioritizes personal interactions, compliance readiness, and consistent experience, making it a valuable tool for property professionals seeking to optimize their inspection workflows.

Bichos ID de Fucesa is an AI tool that allows users to explore and identify insects, arachnids, and other arthropods using artificial intelligence. Users can discover the most searched bugs, explore new discoveries made by the community, and view curated organisms. The platform aims to expand knowledge about the fascinating world of arthropods through AI-powered identification.

Inspect AI is a framework developed by the UK AI Safety Institute for evaluating large language models. It offers various built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can extend Inspect by adding new elicitation and scoring techniques through additional Python packages. The tool aims to provide a comprehensive solution for assessing the performance and safety of language models.

Gollama is a tool designed for managing Ollama models through a Text User Interface (TUI). Users can list, inspect, delete, copy, and push Ollama models, as well as link them to LM Studio. The application offers interactive model selection, sorting by various criteria, and actions using hotkeys. It provides features like sorting and filtering capabilities, displaying model metadata, model linking, copying, pushing, and more. Gollama aims to be user-friendly and useful for managing models, especially for cleaning up old models.

GGUF tools is a library designed to manipulate GGUF files commonly used in machine learning projects. The main goal of this library is to provide accessible code that documents GGUF files for the llama.cpp project. The utility implements subcommands to show detailed info about GGUF files, compare two LLMs, inspect tensor weights, and extract models from Mixtral 7B MoE. The library is under active development with well-commented code and a simple API. However, it has limitations in handling quantization formats.

AgentDojo is a dynamic environment designed to evaluate prompt injection attacks and defenses for large language models (LLM) agents. It provides a benchmark script to run different suites and tasks with specified LLM models, defenses, and attacks. The tool is under active development, and users can inspect the results through dedicated documentation pages and the Invariant Benchmark Registry.

Langfuse is a powerful tool that helps you develop, monitor, and test your LLM applications. With Langfuse, you can: * **Develop:** Instrument your app and start ingesting traces to Langfuse, inspect and debug complex logs, and manage, version, and deploy prompts from within Langfuse. * **Monitor:** Track metrics (cost, latency, quality) and gain insights from dashboards & data exports, collect and calculate scores for your LLM completions, run model-based evaluations, collect user feedback, and manually score observations in Langfuse. * **Test:** Track and test app behaviour before deploying a new version, test expected in and output pairs and benchmark performance before deploying, and track versions and releases in your application. Langfuse is easy to get started with and offers a generous free tier. You can sign up for Langfuse Cloud or deploy Langfuse locally or on your own infrastructure. Langfuse also offers a variety of integrations to make it easy to connect to your LLM applications.

A Rust based tool to evaluate LLM models, prompts and model params. It automates the process of selecting the best model parameters, given an LLM model and a prompt, iterating over the possible combinations and letting the user visually inspect the results. The tool assumes the user has Ollama installed and serving endpoints, either in `localhost` or in a remote server. Key features include: * Automatically fetches models from local or remote Ollama servers * Iterates over different models and params to generate inferences * A/B test prompts on different models simultaneously * Allows multiple iterations for each combination of parameters * Makes synchronous inference calls to avoid spamming servers * Optionally outputs inference parameters and response metadata (inference time, tokens and tokens/s) * Refetching of individual inference calls * Model selection can be filtered by name * List experiments which can be downloaded in JSON format * Configurable inference timeout * Custom default parameters and system prompts can be defined in settings

llm-swarm is a tool designed to manage scalable open LLM inference endpoints in Slurm clusters. It allows users to generate synthetic datasets for pretraining or fine-tuning using local LLMs or Inference Endpoints on the Hugging Face Hub. The tool integrates with huggingface/text-generation-inference and vLLM to generate text at scale. It manages inference endpoint lifetime by automatically spinning up instances via `sbatch`, checking if they are created or connected, performing the generation job, and auto-terminating the inference endpoints to prevent idling. Additionally, it provides load balancing between multiple endpoints using a simple nginx docker for scalability. Users can create slurm files based on default configurations and inspect logs for further analysis. For users without a Slurm cluster, hosted inference endpoints are available for testing with usage limits based on registration status.

**RVC_CLI: Retrieval-based Voice Conversion Command Line Interface** This command-line interface (CLI) provides a comprehensive set of tools for voice conversion, enabling you to modify the pitch, timbre, and other characteristics of audio recordings. It leverages advanced machine learning models to achieve realistic and high-quality voice conversions. **Key Features:** * **Inference:** Convert the pitch and timbre of audio in real-time or process audio files in batch mode. * **TTS Inference:** Synthesize speech from text using a variety of voices and apply voice conversion techniques. * **Training:** Train custom voice conversion models to meet specific requirements. * **Model Management:** Extract, blend, and analyze models to fine-tune and optimize performance. * **Audio Analysis:** Inspect audio files to gain insights into their characteristics. * **API:** Integrate the CLI's functionality into your own applications or workflows. **Applications:** The RVC_CLI finds applications in various domains, including: * **Music Production:** Create unique vocal effects, harmonies, and backing vocals. * **Voiceovers:** Generate voiceovers with different accents, emotions, and styles. * **Audio Editing:** Enhance or modify audio recordings for podcasts, audiobooks, and other content. * **Research and Development:** Explore and advance the field of voice conversion technology. **For Jobs:** * Audio Engineer * Music Producer * Voiceover Artist * Audio Editor * Machine Learning Engineer **AI Keywords:** * Voice Conversion * Pitch Shifting * Timbre Modification * Machine Learning * Audio Processing **For Tasks:** * Convert Pitch * Change Timbre * Synthesize Speech * Train Model * Analyze Audio

ChainForge is a visual programming environment for battle-testing prompts to LLMs. It is geared towards early-stage, quick-and-dirty exploration of prompts, chat responses, and response quality that goes beyond ad-hoc chatting with individual LLMs. With ChainForge, you can: * Query multiple LLMs at once to test prompt ideas and variations quickly and effectively. * Compare response quality across prompt permutations, across models, and across model settings to choose the best prompt and model for your use case. * Setup evaluation metrics (scoring function) and immediately visualize results across prompts, prompt parameters, models, and model settings. * Hold multiple conversations at once across template parameters and chat models. Template not just prompts, but follow-up chat messages, and inspect and evaluate outputs at each turn of a chat conversation. ChainForge comes with a number of example evaluation flows to give you a sense of what's possible, including 188 example flows generated from benchmarks in OpenAI evals. This is an open beta of Chainforge. We support model providers OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and Dalai-hosted models Alpaca and Llama. You can change the exact model and individual model settings. Visualization nodes support numeric and boolean evaluation metrics. ChainForge is built on ReactFlow and Flask.

This repository provides a Python implementation of a method that leverages pre-trained large language models to construct and utilize world models for model-based task planning. It includes scripts to generate domain models using natural language descriptions, correct domain models based on feedback, and support plan generation for tasks in different domains. The code has been refactored for better readability and includes tools for validating PDDL syntax and handling corrective feedback.

The Ramalama project simplifies working with AI by utilizing OCI containers. It automatically detects GPU support, pulls necessary software in a container, and runs AI models. Users can list, pull, run, and serve models easily. The tool aims to support various GPUs and platforms in the future, making AI setup hassle-free.

Data Formulator is an AI-powered tool developed by Microsoft Research to help data analysts create rich visualizations iteratively. It combines user interface interactions with natural language inputs to simplify the process of describing chart designs while delegating data transformation to AI. Users can utilize features like blended UI and NL inputs, data threads for history navigation, and code inspection to create impressive visualizations. The tool supports local installation for customization and Codespaces for quick setup. Developers can build new data analysis tools on top of Data Formulator, and research papers are available for further reading.

SciCode is a challenging benchmark designed to evaluate the capabilities of language models (LMs) in generating code for solving realistic scientific research problems. It contains 338 subproblems decomposed from 80 challenging main problems across 16 subdomains from 6 domains. The benchmark offers optional descriptions specifying useful scientific background information and scientist-annotated gold-standard solutions and test cases for evaluation. SciCode demonstrates a realistic workflow of identifying critical science concepts and facts and transforming them into computation and simulation code, aiming to help showcase LLMs' progress towards assisting scientists and contribute to the future building and evaluation of scientific AI.

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are: * `MLflow Tracking `_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects `_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models `_: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker. * `MLflow Model Registry `_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.

Invariant Analyzer is an open-source scanner designed for LLM-based AI agents to find bugs, vulnerabilities, and security threats. It scans agent execution traces to identify issues like looping behavior, data leaks, prompt injections, and unsafe code execution. The tool offers a library of built-in checkers, an expressive policy language, data flow analysis, real-time monitoring, and extensible architecture for custom checkers. It helps developers debug AI agents, scan for security violations, and prevent security issues and data breaches during runtime. The analyzer leverages deep contextual understanding and a purpose-built rule matching engine for security policy enforcement.

AIMET is a library that provides advanced model quantization and compression techniques for trained neural network models. It provides features that have been proven to improve run-time performance of deep learning neural network models with lower compute and memory requirements and minimal impact to task accuracy. AIMET is designed to work with PyTorch, TensorFlow and ONNX models. We also host the AIMET Model Zoo - a collection of popular neural network models optimized for 8-bit inference. We also provide recipes for users to quantize floating point models using AIMET.

LionAGI is a powerful intelligent workflow automation framework that introduces advanced ML models into any existing workflows and data infrastructure. It can interact with almost any model, run interactions in parallel for most models, produce structured pydantic outputs with flexible usage, automate workflow via graph based agents, use advanced prompting techniques, and more. LionAGI aims to provide a centralized agent-managed framework for "ML-powered tools coordination" and to dramatically lower the barrier of entries for creating use-case/domain specific tools. It is designed to be asynchronous only and requires Python 3.10 or higher.

LearnHouse is an open-source platform that allows anyone to easily provide world-class educational content. It supports various content types, including dynamic pages, videos, and documents. The platform is still in early development and should not be used in production environments. However, it offers several features, such as dynamic Notion-like pages, ease of use, multi-organization support, support for uploading videos and documents, course collections, user management, quizzes, course progress tracking, and an AI-powered assistant for teachers and students. LearnHouse is built using various open-source projects, including Next.js, TailwindCSS, Radix UI, Tiptap, FastAPI, YJS, PostgreSQL, LangChain, and React.

Inspect and rate futuristic AI conceived VTOL aircraft.

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