Best AI tools for< Expose Printers To Ios Devices >

DataLang is a tool that allows you to chat with your databases, expose a specific set of data (using SQL) to train GPT, and then chat with it in natural language. You can also use DataLang to automatically make your SQL views available via API, share it with your privately users, or make it public.

iCAD is an AI-powered application designed for cancer detection, specifically focusing on breast cancer. The platform offers a suite of solutions including Detection, Density Assessment, and Risk Evaluation, all backed by science, clinical evidence, and proven patient outcomes. iCAD's AI-powered solutions aim to expose the hiding place of cancer, providing certainty and peace of mind, ultimately improving patient outcomes and saving more lives.

OpenBuckets is a web application designed to help users find and secure open buckets in cloud storage systems. It provides a user-friendly interface for scanning and identifying publicly accessible buckets, allowing users to take necessary actions to secure their data. With OpenBuckets, users can easily detect misconfigured buckets and prevent potential data breaches. The application offers a simple yet effective solution for enhancing cloud security and protecting sensitive information stored in cloud storage platforms.

CensysGPT Beta is a tool that simplifies building queries and empowers users to conduct efficient and effective reconnaissance operations. It enables users to quickly and easily gain insights into hosts on the internet, streamlining the process and allowing for more proactive threat hunting and exposure management.

Junbi.ai is an AI-powered insights platform designed for YouTube advertisers. It offers AI-powered creative insights for YouTube ads, allowing users to benchmark their ads, predict performance, and test quickly and easily with fully AI-powered technology. The platform also includes expoze.io API for attention prediction on images or videos, with scientifically valid results and developer-friendly features for easy integration into software applications.

Sacred is a tool to configure, organize, log and reproduce computational experiments. It is designed to introduce only minimal overhead, while encouraging modularity and configurability of experiments. The ability to conveniently make experiments configurable is at the heart of Sacred. If the parameters of an experiment are exposed in this way, it will help you to: keep track of all the parameters of your experiment easily run your experiment for different settings save configurations for individual runs in files or a database reproduce your results In Sacred we achieve this through the following main mechanisms: Config Scopes are functions with a @ex.config decorator, that turn all local variables into configuration entries. This helps to set up your configuration really easily. Those entries can then be used in captured functions via dependency injection. That way the system takes care of passing parameters around for you, which makes using your config values really easy. The command-line interface can be used to change the parameters, which makes it really easy to run your experiment with modified parameters. Observers log every information about your experiment and the configuration you used, and saves them for example to a Database. This helps to keep track of all your experiments. Automatic seeding helps controlling the randomness in your experiments, such that they stay reproducible.

Schwarzthal Tech's Wunderschild is an AI-driven platform for financial crime intelligence that revolutionizes compliance and investigation techniques. It provides intelligence solutions based on network assessment, data linkage, flow aggregation, and machine learning. The platform offers expertise in identifying risks related to Politically Exposed Persons, Serious Organised Crime, Terrorism Financing, and more. Wunderschild's capabilities include compliance enhancement through semi-supervised learning techniques, deep-dive investigations into transnational crime cases, and global companies' beneficiaries network analysis.

This repository provides a Docker image that acts as an AirPrint bridge for local printers, allowing them to be exposed to iOS/macOS devices. It runs a container with CUPS and Avahi to facilitate this functionality. Users must have CUPS drivers available for their printers. The tool requires a Linux host and a dedicated IP for the container to avoid interference with other services. It supports setting up printers through environment variables and offers options for automated configuration via command line, web interface, or files. The repository includes detailed instructions on setting up and testing the AirPrint bridge.

Sales & Dungeons is a tool that utilizes thermal printers for creating customizable handouts, quick references, and more for Dungeons and Dragons sessions. It offers extensive templating and random generation systems, supports various connection methods, and allows importing/exporting templates and data sources. Users can access external data sources like Open5e, import data from CSV and other formats, and utilize AI prompt generation and translation. The tool supports cloud sync and is compatible with multiple operating systems and devices.

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.

This repository extends the LLVM framework to generate code for use with AMD/Xilinx AI Engine processors. AI Engine processors are in-order, exposed-pipeline VLIW processors focused on application acceleration for AI, Machine Learning, and DSP applications. The repository adds LLVM support for specific features like non-power of 2 pointers, operand latencies, resource conflicts, negative operand latencies, slot assignment, relocations, code alignment restrictions, and register allocation. It includes support for Clang, LLD, binutils, Compiler-RT, and LLVM-LIBC.

RAFT (Reusable Accelerated Functions and Tools) is a C++ header-only template library with an optional shared library that contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

LangChain is a framework for developing Elixir applications powered by language models. It enables applications to connect language models to other data sources and interact with the environment. The library provides components for working with language models and off-the-shelf chains for specific tasks. It aims to assist in building applications that combine large language models with other sources of computation or knowledge. LangChain is written in Elixir and is not aimed for parity with the JavaScript and Python versions due to differences in programming paradigms and design choices. The library is designed to make it easy to integrate language models into applications and expose features, data, and functionality to the models.

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.

ByteChef is an open-source, low-code, extendable API integration and workflow automation platform. It provides an intuitive UI Workflow Editor, event-driven & scheduled workflows, multiple flow controls, built-in code editor supporting Java, JavaScript, Python, and Ruby, rich component ecosystem, extendable with custom connectors, AI-ready with built-in AI components, developer-ready to expose workflows as APIs, version control friendly, self-hosted, scalable, and resilient. It allows users to build and visualize workflows, automate tasks across SaaS apps, internal APIs, and databases, and handle millions of workflows with high availability and fault tolerance.

This repository contains code and results for jailbreaking leading safety-aligned LLMs with simple adaptive attacks. We show that even the most recent safety-aligned LLMs are not robust to simple adaptive jailbreaking attacks. We demonstrate how to successfully leverage access to logprobs for jailbreaking: we initially design an adversarial prompt template (sometimes adapted to the target LLM), and then we apply random search on a suffix to maximize the target logprob (e.g., of the token ``Sure''), potentially with multiple restarts. In this way, we achieve nearly 100% attack success rate---according to GPT-4 as a judge---on GPT-3.5/4, Llama-2-Chat-7B/13B/70B, Gemma-7B, and R2D2 from HarmBench that was adversarially trained against the GCG attack. We also show how to jailbreak all Claude models---that do not expose logprobs---via either a transfer or prefilling attack with 100% success rate. In addition, we show how to use random search on a restricted set of tokens for finding trojan strings in poisoned models---a task that shares many similarities with jailbreaking---which is the algorithm that brought us the first place in the SaTML'24 Trojan Detection Competition. The common theme behind these attacks is that adaptivity is crucial: different models are vulnerable to different prompting templates (e.g., R2D2 is very sensitive to in-context learning prompts), some models have unique vulnerabilities based on their APIs (e.g., prefilling for Claude), and in some settings it is crucial to restrict the token search space based on prior knowledge (e.g., for trojan detection).

Ollama Operator is a Kubernetes operator designed to facilitate running large language models on Kubernetes clusters. It simplifies the process of deploying and managing multiple models on the same cluster, providing an easy-to-use interface for users. With support for various Kubernetes environments and seamless integration with Ollama models, APIs, and CLI, Ollama Operator streamlines the deployment and management of language models. By leveraging the capabilities of lama.cpp, Ollama Operator eliminates the need to worry about Python environments and CUDA drivers, making it a reliable tool for running large language models on Kubernetes.

Sparkle is a tool that streamlines the process of building AI-driven features in applications using Large Language Models (LLMs). It guides users through creating and managing agents, defining tools, and interacting with LLM providers like OpenAI. Sparkle allows customization of LLM provider settings, model configurations, and provides a seamless integration with Sparkle Server for exposing agents via an OpenAI-compatible chat API endpoint.

xef.ai is a one-stop library designed to bring the power of modern AI to applications and services. It offers integration with Large Language Models (LLM), image generation, and other AI services. The library is packaged in two layers: core libraries for basic AI services integration and integrations with other libraries. xef.ai aims to simplify the transition to modern AI for developers by providing an idiomatic interface, currently supporting Kotlin. Inspired by LangChain and Hugging Face, xef.ai may transmit source code and user input data to third-party services, so users should review privacy policies and take precautions. Libraries are available in Maven Central under the `com.xebia` group, with `xef-core` as the core library. Developers can add these libraries to their projects and explore examples to understand usage.

The 'airwin2rack' repository is a collection of Airwindows audio plugins presented in various formats, including as a static library, a module for VCV Rack, and as CLAP/VST3/AU/LV2/Standalone plugins for DAWs. Users can access these plugins through different methods and interfaces, such as a uniform registry and access pattern, making it easy to integrate Airwindows plugins into their audio projects. The repository also provides instructions for updating the Airwindows sub-library and information on licensing, ensuring that users can utilize the plugins in both open and closed source environments.

This repository, llamafile-docker, automates the process of checking for new releases of Mozilla-Ocho/llamafile, building a Docker image with the latest version, and pushing it to Docker Hub. Users can download a pre-trained model in gguf format and use the Docker image to interact with the model via a server or CLI version. Contributions are welcome under the Apache 2.0 license.

Ollama GUI is a web interface for ollama.ai, a tool that enables running Large Language Models (LLMs) on your local machine. It provides a user-friendly platform for chatting with LLMs and accessing various models for text generation. Users can easily interact with different models, manage chat history, and explore available models through the web interface. The tool is built with Vue.js, Vite, and Tailwind CSS, offering a modern and responsive design for seamless user experience.

Maige is a tool designed to simplify repository maintenance by automating the handling of issue labels. Users can quickly set up Maige to let AI manage their issue labels effortlessly. The tool provides guidance on self-hosting, GitHub app integration, environment variables setup, and offers commands for streamlined issue management. Maige aims to streamline the process of managing issues in a repository, making it easier for users to handle tasks related to labeling and tracking issues.

OpenAIKit is a Swift package designed to facilitate communication with the OpenAI API. It provides methods to interact with various OpenAI services such as chat, models, completions, edits, images, embeddings, files, moderations, and speech to text. The package encourages the use of environment variables to securely inject the OpenAI API key and organization details. It also offers error handling for API requests through the `OpenAIKit.APIErrorResponse`.

Nvidia GPU exporter for prometheus, using `nvidia-smi` binary to gather metrics.

FastTrackML is an experiment tracking server focused on speed and scalability, fully compatible with MLFlow. It provides a user-friendly interface to track and visualize your machine learning experiments, making it easy to compare different models and identify the best performing ones. FastTrackML is open source and can be easily installed and run with pip or Docker. It is also compatible with the MLFlow Python package, making it easy to integrate with your existing MLFlow workflows.

Agnaistic is an AI roleplay chat tool that allows users to interact with personalized characters using their favorite AI services. It supports multiple AI services, persona schema formats, and features such as group conversations, user authentication, and memory/lore books. Agnaistic can be self-hosted or run using Docker, and it provides a range of customization options through its settings.json file. The tool is designed to be user-friendly and accessible, making it suitable for both casual users and developers.

An unyielding champion against predatory financial practices, adept at analyzing and exposing complex financial mechanisms, and relentless in advocating for consumer rights and transparency.

You want to know secrets from the world of the beautiful and rich, you are interested in the truth about what is really happening in the world. Then just ask Secret Revealer. Secret Revealer has answers to the most explosive questions that will change your life. Start today before it's too late.

Unraveling the real conspiracy behind everything