Best AI tools for< Quantify Human Emotions >

Entropik is an AI-powered integrated market research company that specializes in real-time measurement and optimization of customer experience (CX), user experience (UX), and market/consumer research (MR). The platform offers a range of capabilities such as Insights AI, Emotion AI, Generative AI, Predictive AI, and Behavior AI to provide actionable insights from human interactions and data analysis. Entropik caters to various industries including market research agencies, consumer brands, BFSI, gaming, digital first brands, media & entertainment, fintech, healthcare, e-commerce, telecom, and retail, helping them optimize their products and services through AI-driven insights.

LogRocket is a session replay, product analytics, and issue detection platform that helps software teams deliver the best web and mobile experiences. With LogRocket, you can see exactly what users experienced on your app, as well as DOM playback, console and network logs, errors, and performance data. You can also surface the most impactful user issues with JavaScript errors, network errors, stack traces, automatic triaging, and alerting. LogRocket also provides product analytics to help you understand how users are interacting with your app, and UX analytics to help you visualize how users experience your app at both the individual and aggregate level.

Connecterra is an intelligent data platform designed specifically for the dairy industry. It provides farmers, advisors, and enterprises with a comprehensive suite of tools to collect, analyze, and visualize their farm data. With advanced AI capabilities, Connecterra helps users identify trends, make informed decisions, and improve their overall operational efficiency.

Connecterra is an intelligent data platform designed specifically for the dairy industry. It provides farmers, advisors, and enterprises with a comprehensive suite of tools to collect, analyze, and visualize their farm data. With advanced AI capabilities, Connecterra helps users identify trends, optimize decision-making, and improve overall farm performance.

Cleerly is a digital healthcare company transforming the way clinicians approach the treatment of heart disease. Our clinically-proven, AI-based digital care platform works with coronary computed tomography angiography (CCTA) imaging to help clinicians precisely identify and define atherosclerosis earlier, so they can provide personalized, life-saving treatment plans for all patients throughout their care continuum. We measure atherosclerosis - plaque build-up in the heart's arteries - not indirect markers such as risk factors and symptoms of disease. Our AI-enabled digital care pathway offers simpler, faster, more accurate heart disease evaluation and reporting that's tailored to each stakeholder, improving overall clinical and financial outcomes.

CustomerIQ is an AI platform designed to drive revenue and retention by automating administrative tasks and extracting actionable insights for sales teams, customer success, marketing, and product departments. It seamlessly integrates with CRM, help desk, and messaging apps to capture and sync CRM fields, automate research, meeting briefs, and handoffs, and quantify insights for product, marketing, and customer experience. CustomerIQ prioritizes enterprise-grade security and scalability, ensuring data privacy and encryption. The platform aims to empower teams with automation and insights, allowing them to focus on building rapport while the AI handles the rest.

Komodo Health is a healthcare technology company that provides software applications to enable users to deliver exceptional value to their customers, colleagues, and patients. The company's Healthcare Map is the industry's most precise view of the U.S. healthcare system, and it combines the world's most comprehensive view of patient-encounters with innovative algorithms and decades of clinical expertise. Komodo Health's software applications are used by life sciences companies, payers, providers, and consultancies to improve the certainty of pre-launch plans, calculate Rx-based ROI for digital marketing, find patients with complicated or rare conditions, and more.

This website is an AI tool that helps senior developers analyze AI tech debt. AI tech debt is the technical debt that accumulates when AI systems are developed and deployed. It can be difficult to identify and quantify AI tech debt, but it can have a significant impact on the performance and reliability of AI systems. This tool uses a variety of techniques to analyze AI tech debt, including static analysis, dynamic analysis, and machine learning. It can help senior developers to identify and quantify AI tech debt, and to develop strategies to reduce it.

Epoch AI is a research institute dedicated to investigating key trends and questions that will shape the trajectory and governance of AI. They provide essential insights for policymakers, conduct rigorous analysis of trends in AI and machine learning, and produce reports, papers, models, and visualizations to advance evidence-based discussions about AI. Epoch AI collaborates with stakeholders and collects key data on machine learning models to analyze historical and contemporary progress in AI. They are known for their thoughtful and best-researched survey work in the industry.

Ignition is an AI-powered roadmapping suite designed to help businesses connect roadmaps to revenue. It enables users to identify and prioritize feature gaps based on revenue impact, generate roadmaps, and align them with sales effortlessly. The tool automates the process of extracting deal-blocking feature gaps, prioritizing revenue-based roadmaps, and notifying sales reps when features ship. By leveraging AI analysis, Ignition empowers users to quantify product impact on revenue, surface key themes from customer conversations, and close deals effectively. With features like competitive intelligence analysis, customizable roadmaps, GTM planning, feature voting boards, and AI feedback summarization, Ignition streamlines product operations and drives better adoption and revenue impact.

Lilac is an AI tool designed to enhance data quality and exploration for AI applications. It offers features such as data search, quantification, editing, clustering, semantic search, field comparison, and fuzzy-concept search. Lilac enables users to accelerate dataset computations and transformations, making it a valuable asset for data scientists and AI practitioners. The tool is trusted by Alignment Lab and is recommended for working with LLM datasets.

Cybertiks is an AI-powered platform that specializes in harnessing the power of satellite imagery to provide valuable insights for agriculture fields worldwide. By integrating advanced AI models trained on thousands of fields, Cybertiks offers bespoke solutions for remote sensing of industrial requirements. Users can monitor field metrics, historical insights, and field status changes, with results delivered every 7 days. The platform also integrates various sources of information, provides certifications, synchronizes data, and offers data integration for a comprehensive and strategic vision.

Luna.ai is a sales automation tool that uses artificial intelligence (AI) to help businesses find and engage with potential customers. The tool offers a range of features, including lead generation, email marketing, and customer relationship management (CRM). Luna.ai is designed to help businesses improve their sales performance by automating tasks and providing insights into customer behavior.

Beam AI is the #1 end-to-end automated takeoff software designed for General Contractors, Subcontractors, and Suppliers in the construction industry. It leverages cutting-edge Artificial Intelligence technology to provide accurate and fast quantity takeoffs for various trades, saving up to 90% of the time typically spent on manual takeoffs. With Beam AI, users can streamline their bidding process, send out more estimates, and focus on value engineering to build competitive estimates. The software offers features such as cloud-based collaboration, 100% done-for-you quantity takeoffs, auto-detection of spec details, and the ability to process multiple takeoffs in parallel.

TestFit is a real estate feasibility platform that helps users maximize site potential and get the right deals done faster. It uses real-time AI for rapid iterations, allowing users to evaluate deals in hours instead of weeks. TestFit also integrates with other software, such as Revit and Enscape, to streamline the design and documentation process.

AutoSEO is an AI-powered tool designed to transform the content creation process on WordPress websites. By utilizing advanced artificial intelligence technology, AutoSEO automates and accelerates the production of SEO-optimized web content, enabling users to generate a large quantity of high-quality articles efficiently. The tool integrates seamlessly with WordPress and leverages OpenAI's technology to create content in multiple languages, making it a versatile solution for global content creation.

CloseFactor is an AI-powered GTM Operating System that helps sales teams close more deals by providing tailored opportunities with potential buyers who are ready to make a purchase. The platform utilizes machine learning and data analysis to identify the best-fit accounts, research their buying readiness in real-time, recommend contact engagements based on past successful deals, and automatically generate customized messages using generative AI. CloseFactor also assists in identifying the Ideal Customer Profile (ICP) by analyzing common characteristics of closed-won deals, enabling users to target the right accounts effectively. The tool has shown to increase the quality and quantity of pipeline from target accounts, improve marketing spend optimization, and enhance personalized outreach for better sales outcomes.

AI Tool Kart is a curated directory of top AI tools across various categories such as SEO, Email Marketing, Dropshipping, Image Generation, Video Editing, and more. With a focus on quality over quantity, the platform features only the best 11 tools per niche, ensuring users have access to trusted and tested solutions. The website also offers insightful blogs and the latest AI news for businesses, aiming to keep users informed and at the forefront of innovation.

Upwork Proposals Generator is an AI tool designed to help freelancers on Upwork create unique and personalized proposals quickly and efficiently. Unlike traditional tools, it uses AI technology to tailor proposals based on the freelancer's profile and the client's requirements. The tool focuses on speed, quality, and quantity of proposals to increase the freelancer's chances of winning contracts on Upwork. With features like local references, greetings in the client's language, and customizable styles, the tool aims to streamline the proposal writing process and make freelancers stand out in the competitive Upwork marketplace.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

Aligner is a model-agnostic alignment tool that learns correctional residuals between preferred and dispreferred answers using a small model. It can be directly applied to various open-source and API-based models with only one-off training, suitable for rapid iteration and improving model performance. Aligner has shown significant improvements in helpfulness, harmlessness, and honesty dimensions across different large language models.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

Cherry Data Selection project introduces a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, minimizing manual curation and cost for instruction tuning. The project focuses on selecting impactful training samples ('cherry data') to enhance LLM instruction tuning by estimating instruction-following difficulty. The method involves phases like 'Learning from Brief Experience', 'Evaluating Based on Experience', and 'Retraining from Self-Guided Experience' to improve LLM performance.

Tools4AI is a Java-based Agentic Framework for building AI agents to integrate with enterprise Java applications. It enables the conversion of natural language prompts into actionable behaviors, streamlining user interactions with complex systems. By leveraging AI capabilities, it enhances productivity and innovation across diverse applications. The framework allows for seamless integration of AI with various systems, such as customer service applications, to interpret user requests, trigger actions, and streamline workflows. Prompt prediction anticipates user actions based on input prompts, enhancing user experience by proactively suggesting relevant actions or services based on context.

Ragas is a framework that helps you evaluate your Retrieval Augmented Generation (RAG) pipelines. RAG denotes a class of LLM applications that use external data to augment the LLM’s context. There are existing tools and frameworks that help you build these pipelines but evaluating it and quantifying your pipeline performance can be hard. This is where Ragas (RAG Assessment) comes in. Ragas provides you with the tools based on the latest research for evaluating LLM-generated text to give you insights about your RAG pipeline. Ragas can be integrated with your CI/CD to provide continuous checks to ensure performance.

Turtle Benchmark is a novel and cheat-proof benchmark test used to evaluate large language models (LLMs). It is based on the Turtle Soup game, focusing on logical reasoning and context understanding abilities. The benchmark does not require background knowledge or model memory, providing all necessary information for judgment from stories under 200 words. The results are objective and unbiased, quantifiable as correct/incorrect/unknown, and impossible to cheat due to using real user-generated questions and dynamic data generation during online gameplay.

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.

Acte is a framework designed to build GUI-like tools for AI Agents. It aims to address the issues of cognitive load and freedom degrees when interacting with multiple APIs in complex scenarios. By providing a graphical user interface (GUI) for Agents, Acte helps reduce cognitive load and constraints interaction, similar to how humans interact with computers through GUIs. The tool offers APIs for starting new sessions, executing actions, and displaying screens, accessible via HTTP requests or the SessionManager class.

MathPile is a generative AI tool designed for math, offering a diverse and high-quality math-centric corpus comprising about 9.5 billion tokens. It draws from various sources such as textbooks, arXiv, Wikipedia, ProofWiki, StackExchange, and web pages, catering to different educational levels and math competitions. The corpus is meticulously processed to ensure data quality, with extensive documentation and data contamination detection. MathPile aims to enhance mathematical reasoning abilities of language models.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

FeedGen is an open-source tool that uses Google Cloud's state-of-the-art Large Language Models (LLMs) to improve product titles, generate more comprehensive descriptions, and fill missing attributes in product feeds. It helps merchants and advertisers surface and fix quality issues in their feeds using Generative AI in a simple and configurable way. The tool relies on GCP's Vertex AI API to provide both zero-shot and few-shot inference capabilities on GCP's foundational LLMs. With few-shot prompting, users can customize the model's responses towards their own data, achieving higher quality and more consistent output. FeedGen is an Apps Script based application that runs as an HTML sidebar in Google Sheets, allowing users to optimize their feeds with ease.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

MachineSoM is a code repository for the paper 'Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View'. It focuses on the emergence of intelligence from collaborative and communicative computational modules, enabling effective completion of complex tasks. The repository includes code for societies of LLM agents with different traits, collaboration processes such as debate and self-reflection, and interaction strategies for determining when and with whom to interact. It provides a coding framework compatible with various inference services like Replicate, OpenAI, Dashscope, and Anyscale, supporting models like Qwen and GPT. Users can run experiments, evaluate results, and draw figures based on the paper's content, with available datasets for MMLU, Math, and Chess Move Validity.

Assists with biological image processing tools.

I assist biological image analysis, including ImageJ macro and Python coding.

Expert in all aspects of spectral flow cytometry.

Your AI MEP Estimator Co-pilot

Provides concise GC troubleshooting and method development advice that is easy to implement.

Extract the essence of the novel story according to the quantity requirements and generate corresponding images. The images can be used directly to create novel videos.小说推文图片自动批量生成,可自动生成风格一致性图片

Extract from receipts to CSV: Date of Purchase, Item Purchased, Quantity Purchased, Units

A precise and informative estimator for various calculations and quantities.

Expert in Greater Bay Area cost estimations

Sicro e SINAPI

I organize my thoughts using ontology matrices, for detailed CWP advice.

A construction materials calculator for various projects.