AI tools for twitter reply online free
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LivingInbox
LivingInbox is a tool that helps you stay on top of your prospect's interactions across channels. It surfaces semantically relevant content and provides AI assistance so you can engage with prospects at the right time. With LivingInbox, you can: - Get a centralized view of all your prospect interactions across channels - Set custom alerts to be notified of important messages - Reply to messages with AI assistance - Take specific actions right from LivingInbox, such as connecting on LinkedIn or reposting a Twitter post
Hot Reach AI
Hot Reach AI is an AI-powered tool that helps you generate personalized first lines for cold outreach emails. It takes care of the intro, so you can focus on your offer. According to Woodpecker data, the average response rate for a personalized cold email is 17%, but it drops to 7% without it. Including a prospect's name, company, or pain points in your subject line or copy can massively increase your chances of a reply.
Create Next App Chat With the Algorithm
The website 'Create Next App Chat With the Algorithm' is an AI tool that allows users to generate chat applications using algorithms. It is a work in progress with the latest algorithm code updated on April 14, 2023. Users can leverage this tool to quickly create chat applications with the help of advanced algorithms.
Startup Mentor
Your startup mentor backed by Elon Musk, Sam Altman, Paul Graham, Steve Jobs, and Bill Gates. Author: twitter.com/HeySophiaHong
SpintaxGPT
I add spintax to emails for Instantly.ai. For more cold email tips, follow me on Twitter/𝕏 at @kenautoup
free-for-life
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
OpenDAN-Personal-AI-OS
OpenDAN is an open source Personal AI OS that consolidates various AI modules for personal use. It empowers users to create powerful AI agents like assistants, tutors, and companions. The OS allows agents to collaborate, integrate with services, and control smart devices. OpenDAN offers features like rapid installation, AI agent customization, connectivity via Telegram/Email, building a local knowledge base, distributed AI computing, and more. It aims to simplify life by putting AI in users' hands. The project is in early stages with ongoing development and future plans for user and kernel mode separation, home IoT device control, and an official OpenDAN SDK release.
AIlice
AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.
chatgpt-universe
ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher
awesome-ai
Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.
nlp-llms-resources
The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.
DB-GPT
DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.
companion-vscode
Quack Companion is a VSCode extension that provides smart linting, code chat, and coding guideline curation for developers. It aims to enhance the coding experience by offering a new tab with features like curating software insights with the team, code chat similar to ChatGPT, smart linting, and upcoming code completion. The extension focuses on creating a smooth contribution experience for developers by turning contribution guidelines into a live pair coding experience, helping developers find starter contribution opportunities, and ensuring alignment between contribution goals and project priorities. Quack collects limited telemetry data to improve its services and products for developers, with options for anonymization and disabling telemetry available to users.
qdrant
Qdrant is a vector similarity search engine and vector database. It is written in Rust, which makes it fast and reliable even under high load. Qdrant can be used for a variety of applications, including: * Semantic search * Image search * Product recommendations * Chatbots * Anomaly detection Qdrant offers a variety of features, including: * Payload storage and filtering * Hybrid search with sparse vectors * Vector quantization and on-disk storage * Distributed deployment * Highlighted features such as query planning, payload indexes, SIMD hardware acceleration, async I/O, and write-ahead logging Qdrant is available as a fully managed cloud service or as an open-source software that can be deployed on-premises.
rl
TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.
Awesome-AITools
This repo collects AI-related utilities. ## All Categories * All Categories * ChatGPT and other closed-source LLMs * AI Search engine * Open Source LLMs * GPT/LLMs Applications * LLM training platform * Applications that integrate multiple LLMs * AI Agent * Writing * Programming Development * Translation * AI Conversation or AI Voice Conversation * Image Creation * Speech Recognition * Text To Speech * Voice Processing * AI generated music or sound effects * Speech translation * Video Creation * Video Content Summary * OCR(Optical Character Recognition)
MedLLMsPracticalGuide
This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.
llm-continual-learning-survey
This repository is an updating survey for Continual Learning of Large Language Models (CL-LLMs), providing a comprehensive overview of various aspects related to the continual learning of large language models. It covers topics such as continual pre-training, domain-adaptive pre-training, continual fine-tuning, model refinement, model alignment, multimodal LLMs, and miscellaneous aspects. The survey includes a collection of relevant papers, each focusing on different areas within the field of continual learning of large language models.