Best AI tools for< settle up with friends >

SplitMyExpenses is a web application that simplifies shared expenses among friends. It eliminates the need for spreadsheets and manual calculations, enabling users to create groups and split bills quickly and easily. The application provides a variety of split types, including equal, by amount, percentage, shares, adjustments, and by itemization. It also offers AI-powered features such as automatic receipt itemization and friend data powered by payment apps. SplitMyExpenses supports over 150 currencies and ensures secure, fast, and private transactions without selling user data.

EvenUp is a legal technology company that provides AI-powered demand packages for injury lawyers. The company's software leverages 250K+ public verdicts and private settlements to improve the accuracy of its analysis. EvenUp's team of injury experts, including former defense counsel, paralegals, case managers, and technologists, has prepared thousands of demands. The company's services are tailored to each firm's needs.

Opinionate is an AI-powered platform designed to enhance decision-making and strengthen arguments through steelmanning techniques. Users can engage in debates, generate topics, and challenge ideas with the help of artificial intelligence. The platform aims to facilitate constructive discussions and improve critical thinking skills by providing automated support in formulating well-structured arguments.

AI Judge is an innovative online platform that utilizes artificial intelligence technology to generate verdicts and resolve disputes between two parties. It provides a convenient and efficient way to settle disagreements without the need for lengthy and costly legal proceedings. AI Judge's platform is designed to be impartial and unbiased, ensuring that both parties have an equal opportunity to present their cases and receive a fair verdict. The AI algorithms carefully analyze the arguments, evidence, and legal principles presented by each party to determine a just and reasonable outcome. AI Judge's verdicts are not legally binding but serve as an additional perspective for the contending parties to consider in their dispute resolution process. Additionally, users have the option to have a qualified legal professional review the AI-generated verdict for an extra layer of scrutiny and confidence. AI Judge is constantly striving to improve its AI algorithms and ensure that its platform adheres to ethical standards. It values user feedback and continuously works to refine its processes, ensuring that it remains a reliable tool for dispute resolution.

Built In Seattle is an online community for startups and tech companies. It provides a platform for job seekers to find tech jobs in Seattle and for employers to post job openings. Built In Seattle also offers news, events, and resources for the Seattle tech community.

BrowseGPT is a free Chrome extension that uses artificial intelligence to automate your browser. You can give BrowseGPT instructions like "Find a place to stay in Seattle on February 22nd" or "buy a children's book on Amazon", and it will use OpenAI's GPT-3 model to process web pages and issue commands like CLICK, ENTER_TEXT, or NAVIGATE to complete the task for you.

AIS-catcher: A multi-platform AIS Receiver

Lego AI Parser is an open-source application that uses OpenAI to parse visible text of HTML elements. It is built on top of FastAPI, ready to set up as a server, and make calls from any language. It supports preset parsers for Google Local Results, Amazon Listings, Etsy Listings, Wayfair Listings, BestBuy Listings, Costco Listings, Macy's Listings, and Nordstrom Listings. Users can also design custom parsers by providing prompts, examples, and details about the OpenAI model under the classifier key.

This repository contains Python scripts that enable two-way voice conversations with Anthropic Claude, utilizing ElevenLabs for text-to-speech, Faster-Whisper for speech-to-text, and Pygame for audio playback. The tool operates by transcribing human audio using Faster-Whisper, sending the transcription to Anthropic Claude for response generation, and converting the LLM's response into audio using ElevenLabs. The audio is then played back through Pygame, allowing for a seamless and interactive conversation between the user and the AI. The repository includes variations of the main script to support different operating systems and configurations, such as using CPU transcription on Linux or employing the AssemblyAI API instead of Faster-Whisper.

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".

BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

This plugin extends and creates `a`/`i` textobjects in Neovim. It enhances some builtin textobjects (like `a(`, `a)`, `a'`, and more), creates new ones (like `a*`, `a`, `af`, `a?`, and more), and allows the user to create their own (like based on treesitter, and more). It supports dot-repeat, `v:count`, different search methods, consecutive application, and customization via Lua patterns or functions. It has builtins for brackets, quotes, function call, argument, tag, user prompt, and any punctuation/digit/whitespace character.

LLM-baselines is a modular codebase to experiment with transformers, inspired from NanoGPT. It provides a quick and easy way to train and evaluate transformer models on a variety of datasets. The codebase is well-documented and easy to use, making it a great resource for researchers and practitioners alike.

I’m here to help refugees settle down in their new home, and to support organizations who help them.

A fun game of CHARACTER versus CHARACTER. Get the conversation and debates going!

Your guide to Seattle Nightlife