Best AI tools for< Observe Operating Status >

Wallaroo.AI is an AI inference platform that offers production-grade AI inference microservices optimized on OpenVINO for cloud and Edge AI application deployments on CPUs and GPUs. It provides hassle-free AI inferencing for any model, any hardware, anywhere, with ultrafast turnkey inference microservices. The platform enables users to deploy, manage, observe, and scale AI models effortlessly, reducing deployment costs and time-to-value significantly.

Observe.AI is a conversation intelligence software designed for contact centers, offering a suite of AI-powered tools to enhance customer interactions, support agents in real-time, and improve overall customer satisfaction. The platform combines advanced analytics, automation, and real-time assistance to drive continuous improvement and boost operational efficiency. Trusted by over 350 enterprises worldwide, Observe.AI helps businesses transform customer conversations into actionable insights, leading to measurable results such as increased sales conversions, improved compliance adherence, and enhanced customer sentiment.

Spreadsite is an AI-powered platform that turns spreadsheets into interactive web dashboards without the need for coding. It utilizes AI to transform data into visually appealing and interactive dashboards, offering features like agent-powered workflows, interactive data visualization, seamless sharing, and endless possibilities for data exploration. Spreadsite caters to various industries such as finance, marketing, and energy, providing users with the ability to create custom websites from their spreadsheet data effortlessly.

Radicalbit is an MLOps and AI Observability platform that helps businesses deploy, serve, observe, and explain their AI models. It provides a range of features to help data teams maintain full control over the entire data lifecycle, including real-time data exploration, outlier and drift detection, and model monitoring in production. Radicalbit can be seamlessly integrated into any ML stack, whether SaaS or on-prem, and can be used to run AI applications in minutes.

Sanctuary Cognitive Systems Corporation is a company that develops and manufactures general-purpose robots. Their flagship product, Phoenix™, is the world's first humanoid general-purpose robot powered by Carbon™, their pioneering AI control system. Phoenix™ is designed for work and is the only general-purpose robot featured in TIME's Best Inventions 2023. Sanctuary's robots are remotely piloted or supervised by people and are designed to both train and work alongside them. When instructed to do so, their robots will use their own built-in autonomous control system to observe, assess, and act on tasks in an efficient and prosperous manner.

MagicForm is an AI-powered lead generation tool that supercharges the top of your sales funnel with a 24/7 AI assistant. It learns about your business, follows up with leads, and helps increase conversions by providing personalized interactions. MagicForm is easy to train, instruct, trust, deploy, observe, integrate, and follow up with. It offers features like scanning websites, extracting facts, easy customization of conversation flow, and automation setup. The tool is powered by GPT-4 and offers different pricing plans to cater to solopreneurs, small businesses, and large companies.

Camel AGI is a groundbreaking platform that revolutionizes the way artificial intelligence is utilized to solve complex tasks by employing a unique role-playing method inspired by loop architecture, similar to that of BabyAGI and AutoGPT. At its core, CamelAGI facilitates the collaboration between two autonomous AI agents, each assigned specific roles, to work synergistically towards accomplishing a designated task. This innovative approach allows users to observe as the agents, equipped with distinct capabilities and perspectives, engage in a dynamic and context-aware dialogue, effectively mirroring the collaborative efforts seen in human interactions.

Observer is a news and media website that covers a wide range of topics, including business, finance, technology, media, lifestyle, arts, entertainment, and power lists. The website features articles, reviews, interviews, and videos from a team of experienced journalists and critics.

Privacy Observer is an AI-powered tool that makes privacy accessible by scanning and analyzing privacy policies of websites. It helps users understand when websites request excessive personal information without the need to read lengthy policies. The tool provides a detailed score for each website, ensuring users can make informed decisions about their online privacy. With features like unlimited background scans, anonymous checks by humans, and a user-friendly browser extension, Privacy Observer aims to empower users to protect their privacy online.

Revisor is a neural network-based software package designed for monitoring electoral procedures and counting the number of actual voters. It utilizes AI-enabled monitoring to provide fast, reliable, and cost-effective election observation missions with high precision in voter counting. The system is trainable and can work with different types of voting procedures and electoral systems in any country. Revisor operates based on video recordings, allowing immediate results post-election and detection of violations.

ENOVA is an open-source service for Large Language Model (LLM) deployment, monitoring, injection, and auto-scaling. It addresses challenges in deploying stable serverless LLM services on GPU clusters with auto-scaling by deconstructing the LLM service execution process and providing configuration recommendations and performance detection. Users can build and deploy LLM with few command lines, recommend optimal computing resources, experience LLM performance, observe operating status, achieve load balancing, and more. ENOVA ensures stable operation, cost-effectiveness, efficiency, and strong scalability of LLM services.

llamafile is a tool that enables users to distribute and run Large Language Models (LLMs) with a single file. It combines llama.cpp with Cosmopolitan Libc to create a framework that simplifies the complexity of LLMs into a single-file executable called a 'llamafile'. Users can run these executable files locally on most computers without the need for installation, making open LLMs more accessible to developers and end users. llamafile also provides example llamafiles for various LLM models, allowing users to try out different LLMs locally. The tool supports multiple CPU microarchitectures, CPU architectures, and operating systems, making it versatile and easy to use.

AirSane is a SANE frontend and scanner server that supports Apple's AirScan protocol. It automatically detects scanners and publishes them through mDNS. Acquired images can be transferred in JPEG, PNG, and PDF/raster format. The tool is intended to be used with AirScan/eSCL clients such as Apple's Image Capture, sane-airscan on Linux, and the eSCL client built into Windows 10 and 11. It provides a simple web interface and encodes images on-the-fly to keep memory/storage demands low, making it suitable for devices like Raspberry Pi. Authentication and secure communication are supported in conjunction with a proxy server like nginx. AirSane has been reverse-engineered from Apple's AirScanScanner client communication protocol and offers a range of installation and configuration options for different operating systems.

ScreenAgent is a project focused on creating an environment for Visual Language Model agents (VLM Agent) to interact with real computer screens. The project includes designing an automatic control process for agents to interact with the environment and complete multi-step tasks. It also involves building the ScreenAgent dataset, which collects screenshots and action sequences for various daily computer tasks. The project provides a controller client code, configuration files, and model training code to enable users to control a desktop with a large model.

Nerve is a tool that allows creating stateful agents with any LLM of your choice without writing code. It provides a framework of functionalities for planning, saving, or recalling memories by dynamically adapting the prompt. Nerve is experimental and subject to changes. It is valuable for learning and experimenting but not recommended for production environments. The tool aims to instrument smart agents without code, inspired by projects like Dreadnode's Rigging framework.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

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Guides on outdoor activities, with an informative and adventure-oriented tone.

Non-interactive, silent GPT.

Monitoring tools expert with brief responses and guiding hints.