Best AI tools for< Augment Interaction Graphs >

Ideator is an AI-powered tool that helps designers and innovators generate creative ideas. It allows users to input a feature or interaction and then generates different variations of how it could be used, while keeping its main job the same. Ideator is still under development, but it has the potential to be a valuable tool for designers and innovators who are looking for new and creative ways to solve problems.

Swivl is an automation platform designed for self-storage businesses, offering intelligent automation solutions to streamline operations and enhance customer interactions. The platform leverages conversational AI technology to automate conversations with tenants, drive revenue, and augment workforce capabilities. Swivl aims to simplify the rental process, save costs, and increase revenue for self-storage operators while maintaining brand integrity. The platform is trusted by self-storage leaders for its ability to automate customer touchpoints, provide automated customer support and sales assistance, and enhance team productivity. With features like digital assistants, online self-service automation, inventory recommendations, call center deflection, and omni-channel experiences, Swivl is a comprehensive solution for self-storage businesses.

Encounter AI is an automated ordering assistant designed specifically for restaurants and retail establishments. It aims to increase staff capacity and productivity by providing a robust voice solution to enhance the drive-thru experience. The AI technology enables operators to optimize existing resources, such as human capital or technology assets, to improve profitability. Encounter AI is 'kaizen' in nature, continuously learning through machine learning to stay updated on menu items and ordering preferences, ultimately enhancing the customer experience.

Botsy is an AI chatbot builder designed for WhatsApp, enabling users to create conversational AI chatbots without the need for coding. It allows for natural conversations, brand customization, audience management, user data analysis, and knowledge augmentation. Botsy offers usage-based pricing with discounts for larger message bundles, along with hands-on training and tech support for customers. The platform aims to leverage AI for social impact by providing personalized AI services to communities in need.

The Human-Centred Artificial Intelligence Lab (Holzinger Group) is a research group focused on developing AI solutions that are explainable, trustworthy, and aligned with human values, ethical principles, and legal requirements. The lab works on projects related to machine learning, digital pathology, interactive machine learning, and more. Their mission is to combine human and computer intelligence to address pressing problems in various domains such as forestry, health informatics, and cyber-physical systems. The lab emphasizes the importance of explainable AI, human-in-the-loop interactions, and the synergy between human and machine intelligence.

QuData is an AI and ML solutions provider that helps businesses enhance their value through AI/ML implementation, product design, QA, and consultancy services. They offer a range of services including ChatGPT integration, speech synthesis, speech recognition, image analysis, text analysis, predictive analytics, big data analysis, innovative research, and DevOps solutions. QuData has extensive experience in machine learning and artificial intelligence, enabling them to create high-quality solutions for specific industries, helping customers save development costs and achieve their business goals.

Karla is an AI tool designed for journalists to enhance their writing process by utilizing Large Language Models (LLMs). It helps journalists transform news information into well-structured articles efficiently, augment their sources, customize stories seamlessly, enjoy a sleek editing experience, and export their completed stories easily. Karla acts as a wrapper around the LLM of choice, providing dynamic prompts and integration into a text editor and workflow, allowing journalists to focus on writing without manual prompt crafting. It offers benefits over traditional LLM chat apps by providing efficient prompt crafting, seamless integration, enhanced outcomes, faster performance, model flexibility, and relevant content tailored for journalism.

Augment is a personal AI assistant that helps you remember anything, type less, and read faster. It works inside all the apps you know and love, so you can stay focused on the task at hand. Augment is designed for macOS and is trusted by professionals from all walks of life.

Tome is an AI assistant for sales, designed to enhance sales teams' productivity and efficiency. It offers a new way to research accounts, providing a 360° view of every account, personalized outreach capabilities, and meeting preparation assistance. Tome is used by over 10,000 teams and is engineered to be a second brain for sales professionals, trained on value frameworks and sales data to gather strategic initiatives and understand customers in the Ideal Customer Profile (ICP). It leverages public web and internal data sources to extract valuable insights for sales teams.

Sana is an AI company transforming how organizations learn and access knowledge. Its AI-first learning platform and knowledge assistant are designed for people teams that want to do learning differently. The platform offers integrations, solutions for employee onboarding, sales enablement, compliance training, leadership development, and external training. The knowledge assistant helps everyone work faster, think bigger, and achieve more. Sana's products are trusted by the world's most pioneering companies.

Aide is an AI platform designed to enhance customer support operations. It offers a range of features to help businesses gain insights into customer needs, automate support processes, improve agent efficiency, and train AI chatbots. Aide's key capabilities include customer insights, workflow automation, agent assist, and AI chatbots. With Aide, businesses can analyze customer conversations, identify pain points, and automate repetitive tasks to streamline support operations and improve customer satisfaction.

syntheticAIdata is a platform that provides synthetic data for training vision AI models. Synthetic data is generated artificially, and it can be used to augment existing real-world datasets or to create new datasets from scratch. syntheticAIdata's platform is easy to use, and it can be integrated with leading cloud platforms. The company's mission is to make synthetic data accessible to everyone, and to help businesses overcome the challenges of acquiring high-quality data for training their vision AI models.

Prompt Engineering is a discipline focused on developing and optimizing prompts to efficiently utilize language models (LMs) for various applications and research topics. It involves skills to understand the capabilities and limitations of large language models, improving their performance on tasks like question answering and arithmetic reasoning. Prompt engineering is essential for designing robust prompting techniques that interact with LLMs and other tools, enhancing safety and building new capabilities by augmenting LLMs with domain knowledge and external tools.

Giotto.ai is a Swiss-based company focused on building Artificial General Intelligence by combining Modern Machine Learning with Topological and Algebraic methods. They offer AI Strategy Consulting, AI Application Development, AI Model Integrations, AI R&D Services, and on-demand AI & Tech Talent Solutions. The company provides services to various industries such as Insurance, Finance, Logistics, Healthcare, Education, Retail, Manufacturing, and Defence. Giotto.ai aims to automate complex processes with a high level of robustness and explainability, driving innovation in the technological space.

Dreamwave is an AI research lab developing new ways to augment human creativity with artificial intelligence. Its products include AI headshots, team headshots, and custom photo studios. AI headshots can be generated in minutes, and team headshots can be generated consistently to scale with growing companies. Custom photo studios allow users to generate new photos of themselves with any scene, outfit, or hair. Dreamwave is committed to empowering human creativity, safe and unbiased representation, and secure and private data.

Crowdynews is an AI-powered user-generated content curation tool designed for digital publishers. It helps publishers augment their stories with trusted social media content, increasing engagement and conversion rates. The platform combines multiple social media sources, offers intelligent filters for content control, and provides easy-to-use experiences for publishers to drive audience engagement. Crowdynews is trusted by publishers and brands worldwide to enhance the social experience on their websites.

NextGenAI is an AI application focused on the financial services industry. It aims to challenge the current perception of AI and its role in banking and financial institutions. The platform explores innovative ways to augment human intelligence and propel the financial sector into the next generation of AI. Through a combination of keynotes, panels, demos, and workshops, NextGenAI facilitates discussions on AI regulations, industry best practices, and collaboration opportunities.

Beat Shaper is a generative AI tool for musicians that helps them create beats, basslines, melodies, and VST synthesizer presets. It is designed to augment human creativity and help artists overcome writer's block. Beat Shaper is currently in beta testing, but you can apply for early access on their website.

PandasAI is an open-source AI tool designed for conversational data analysis. It allows users to ask questions in natural language to their enterprise data and receive real-time data insights. The tool is integrated with various data sources and offers enhanced analytics, actionable insights, detailed reports, and visual data representation. PandasAI aims to democratize data analysis for better decision-making, offering enterprise solutions for stable and scalable internal data analysis. Users can also fine-tune models, ingest universal data, structure data automatically, augment datasets, extract data from websites, and forecast trends using AI.

Veritone is a leading provider of artificial intelligence (AI) solutions for businesses. Its flagship product, aiWARE, is an enterprise AI platform that provides access to hundreds of cognitive engines through one common software infrastructure. Veritone's AI solutions are used by businesses in a variety of industries, including media and entertainment, recruitment, government, legal and compliance, and sports. Veritone's mission is to augment the human workforce by transforming use-case concepts into tangible, industry-leading applications and solutions.

LLMRec is a PyTorch implementation for the WSDM 2024 paper 'Large Language Models with Graph Augmentation for Recommendation'. It is a novel framework that enhances recommenders by applying LLM-based graph augmentation strategies to recommendation systems. The tool aims to make the most of content within online platforms to augment interaction graphs by reinforcing u-i interactive edges, enhancing item node attributes, and conducting user node profiling from a natural language perspective.

This repository contains the source code and datasets for Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs accepted to ACL 2024. It proposes a framework called Graph Chain-of-thought (Graph-CoT) to enable Language Models to traverse graphs step-by-step for reasoning, interaction, and execution. The motivation is to alleviate hallucination issues in Language Models by augmenting them with structured knowledge sources represented as graphs.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

LLM Datasets is a repository containing high-quality datasets, tools, and concepts for LLM fine-tuning. It provides datasets with characteristics like accuracy, diversity, and complexity to train large language models for various tasks. The repository includes datasets for general-purpose, math & logic, code, conversation & role-play, and agent & function calling domains. It also offers guidance on creating high-quality datasets through data deduplication, data quality assessment, data exploration, and data generation techniques.

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