Best AI tools for< Align Llms >

Labelbox is a data factory platform that empowers AI teams to manage data labeling, train models, and create better data with internet scale RLHF platform. It offers an all-in-one solution comprising tooling and services powered by a global community of domain experts. Labelbox operates a global data labeling infrastructure and operations for AI workloads, providing expert human network for data labeling in various domains. The platform also includes AI-assisted alignment for maximum efficiency, data curation, model training, and labeling services. Customers achieve breakthroughs with high-quality data through Labelbox.

Korl is a cloud-based product management tool that helps teams create and share product roadmaps, presentations, and updates. It integrates with tools like Jira, Google Drive, and Figma to sync data and auto-generate content. Korl uses AI to analyze project data and generate tailored presentations for different audiences, such as customers, executives, and stakeholders. It also provides real-time updates and allows for collaboration among team members.

Whimsical is an iterative workspace designed for product teams to collaborate effectively. It offers a range of tools such as flowcharts, wireframes, mind maps, and documentation features to help teams visualize ideas, streamline processes, and create a shared understanding. With Whimsical, users can generate diagrams quickly, brainstorm and organize ideas visually, and build wireframes with ease. The platform promotes clarity, collaboration, and efficiency in product development projects.

Crusoe is a cloud computing platform that offers scalable, climate-aligned digital infrastructure optimized for high-performance computing and artificial intelligence. It provides cost-effective solutions by utilizing wasted, stranded, or clean energy sources to power computing resources. The platform supports AI workloads, computational biology, graphics rendering, and more, while reducing greenhouse gas emissions and maximizing resource efficiency.

CustomerIQ is an AI platform that automatically discovers and quantifies themes across customer feedback channels like calls, surveys, tickets, and transcripts. It aggregates customer feedback, extracts and categorizes feature requests, pain points, preferences, and highlights related to customers. The platform helps align teams, prioritize work, and build a customer-obsessed culture. CustomerIQ accelerates development by scoping project requirements faster and providing actionable insights backed with context.

The AI in Business Podcast is a platform designed for non-technical business leaders seeking AI opportunities, aligning AI capabilities with strategy, and achieving ROI. The podcast features interviews with top AI executives from Fortune 500 firms and unicorn startups, exploring trends, use-cases, and best practices for practical AI adoption.

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.

Lattice is an AI-powered people platform designed to help companies achieve operational excellence by transforming company leaders and HR teams into stewards of high performance, data-driven decision making, and meaningful work for every employee. It offers features such as team analytics, 1:1 meetings with auto-suggested agendas, engagement surveys, OKRs & goals tracking, and AI-enhancements. Lattice simplifies HR operations, reduces administrative time, and enables better data-driven decisions based on real-time insights on workforce performance and engagement.

QRCode AI is an online generator of unique and artistic AI-powered QR codes. It offers a wide range of features, including over 100 design templates, improved scan rates, rapid generation, customizable themes, and seamless integrations. QRCode AI's use cases span various industries, including brand promotion, digital ad campaigns, event invitations, product packaging, business cards, online advertising, museum exhibits, webinars, e-commerce, educational resources, music album covers, travel and tourism, corporate events, customer reviews, restaurant menus, and link trees.

AI QR Codes is an online generator that allows users to create artistic and customizable QR codes using AI technology. With a simple prompt, users can generate unique QR codes that reflect their brand or personal style. These QR codes can be used for various purposes, including marketing campaigns, digital content access, and social media connections.

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.

FinanceRants is an AI-powered financial companion that helps individuals understand their financial personality and make informed decisions to achieve financial well-being. By analyzing users' spending, saving, and investing habits, the platform provides personalized insights and actionable strategies to empower users in managing their money and mindset. With a focus on combating financial stress and promoting financial stability, FinanceRants aims to break the cycle of living paycheck to paycheck and guide users towards a more secure financial future.

Quack AI is a software tool designed to assist software development teams in aligning their expectations and improving their contribution flow. It offers a VSCode extension that helps in shaping and maintaining consistency within developer teams. The tool provides guideline curation, contribution assistance, and failure analysis & iteration to streamline the development process. Quack AI is developed by Quack Labs, Inc., aiming to simplify the review process and enhance project management for software teams.

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.

Compliance.ai is a regulatory compliance and risk management solution that leverages purpose-built machine learning models to automatically monitor regulatory updates and align them with internal policies, procedures, and controls. The platform ensures timely tracking, reaction, and reporting on impactful regulations and requirements, helping organizations mitigate risks, reduce costs, and increase confidence in compliance status. Compliance.ai offers a comprehensive suite of features and capabilities to streamline regulatory intelligence, impact analysis, change management, audit reporting, enforcement actions management, and more.

InsightFace is an open-source deep face analysis library that provides a rich variety of state-of-the-art algorithms for face recognition, detection, and alignment. It is designed to be efficient for both training and deployment, making it suitable for research institutions and industrial organizations. InsightFace has achieved top rankings in various challenges and competitions, including the ECCV 2022 WCPA Challenge, NIST-FRVT 1:1 VISA, and WIDER Face Detection Challenge 2019.

Attention is an AI-powered platform that transforms call recordings into valuable insights and actions for sales teams. It offers features such as generating follow-up emails, updating Salesforce, alerting stakeholders of churn risk, creating coaching scorecards, and more. The platform helps sales teams analyze calls, identify coaching priorities, onboard new team members quickly, align sales messaging, and automate follow-up emails with AI. Attention aims to revolutionize sales workflows by providing real-time actionable intelligence and enhancing productivity.

HiredScore is an AI-powered talent orchestration platform that leverages responsible AI, safe automation, and deep integrations to deliver proactive insights to HR stakeholders. The platform helps in talent acquisition, internal mobility, diversity & inclusion, talent rediscovery, contingent hiring, and hiring manager productivity. With a focus on fair AI practices, global capabilities, and full-service HR transformations, HiredScore aims to revolutionize the HR industry by providing innovative solutions for workforce planning and talent management.

Tability is an AI-driven platform designed to help individuals and teams set, track, work, and report on their goals and objectives effectively. It offers AI-assisted goal editing, OKR tracking, reporting on-demand, full-company view of goals, task tracking, and daily standups. The platform aims to bring transparency to OKRs, KPIs, and strategic initiatives, enabling users to move from setting goals to achieving them with ease.

Wonderway is an AI Sales Coach and Sales Training Platform that uses AI to provide automated sales coaching on every call. It helps sales teams train, upskill, and certify their members, leading to increased conversion rates and reduced ramp time. The platform offers personalized training, aligns teams faster, and improves sales onboarding. Wonderway's AI technology understands where sales teams need help and provides recommendations for improvement, making it a valuable tool for sales professionals.

This repository compiles a list of academic papers that evaluate, align, simulate, and provide surveys or perspectives on the use of Large Language Models (LLMs) in the field of Social Science. The papers cover various aspects of LLM research, including assessing their alignment with human values, evaluating their capabilities in tasks such as opinion formation and moral reasoning, and exploring their potential for simulating social interactions and addressing issues in diverse fields of Social Science. The repository aims to provide a comprehensive resource for researchers and practitioners interested in the intersection of LLMs and Social Science.

Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

LMOps is a research initiative focusing on fundamental research and technology for building AI products with foundation models, particularly enabling AI capabilities with Large Language Models (LLMs) and Generative AI models. The project explores various aspects such as prompt optimization, longer context handling, LLM alignment, acceleration of LLMs, LLM customization, and understanding in-context learning. It also includes tools like Promptist for automatic prompt optimization, Structured Prompting for efficient long-sequence prompts consumption, and X-Prompt for extensible prompts beyond natural language. Additionally, LLMA accelerators are developed to speed up LLM inference by referencing and copying text spans from documents. The project aims to advance technologies that facilitate prompting language models and enhance the performance of LLMs in various scenarios.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

StarCoder2-Instruct is an open-source pipeline that introduces StarCoder2-15B-Instruct-v0.1, a self-aligned code Large Language Model (LLM) trained with a fully permissive and transparent pipeline. It generates instruction-response pairs to fine-tune StarCoder-15B without human annotations or data from proprietary LLMs. The tool is primarily finetuned for Python code generation tasks that can be verified through execution, with potential biases and limitations. Users can provide response prefixes or one-shot examples to guide the model's output. The model may have limitations with other programming languages and out-of-domain coding tasks.

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.

Welcome to the ultimate hub for on-device Large Language Models (LLMs)! This repository is your go-to resource for all things related to LLMs designed for on-device deployment. Whether you're a seasoned researcher, an innovative developer, or an enthusiastic learner, this comprehensive collection of cutting-edge knowledge is your gateway to understanding, leveraging, and contributing to the exciting world of on-device LLMs.

This repository is a curated list of papers focused on the detection of Large Language Models (LLMs)-generated content. It includes the latest research papers covering detection methods, datasets, attacks, and more. The repository is regularly updated to include the most recent papers in the field.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

Foundations-of-LLMs is a comprehensive book aimed at readers interested in large language models, providing systematic explanations of foundational knowledge and introducing cutting-edge technologies. The book covers traditional language models, evolution of large language model architectures, prompt engineering, parameter-efficient fine-tuning, model editing, and retrieval-enhanced generation. Each chapter uses an animal as a theme to explain specific technologies, enhancing readability. The content is based on the author team's exploration and understanding of the field, with continuous monthly updates planned. The book includes a 'Paper List' for each chapter to track the latest advancements in related technologies.

rLLM (relationLLM) is a Pytorch library for Relational Table Learning (RTL) with LLMs. It breaks down state-of-the-art GNNs, LLMs, and TNNs as standardized modules and facilitates novel model building in a 'combine, align, and co-train' way using these modules. The library is LLM-friendly, processes various graphs as multiple tables linked by foreign keys, introduces new relational table datasets, and is supported by students and teachers from Shanghai Jiao Tong University and Tsinghua University.

Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, and exciting jailbreak methods on Large Language Models (LLMs). The repository contains papers, codes, datasets, evaluations, and analyses related to jailbreak attacks on LLMs. It serves as a comprehensive resource for researchers and practitioners interested in exploring various jailbreak techniques and defenses in the context of LLMs. Contributions such as additional jailbreak-related content, pull requests, and issue reports are welcome, and contributors are acknowledged. For any inquiries or issues, contact [email protected]. If you find this repository useful for your research or work, consider starring it to show appreciation.

LLM Blueprint is an official implementation of a paper that enables text-to-image generation with complex and detailed prompts. It leverages Large Language Models (LLMs) to extract critical components from text prompts, including bounding box coordinates for foreground objects, detailed textual descriptions for individual objects, and a succinct background context. The tool operates in two phases: Global Scene Generation creates an initial scene using object layouts and background context, and an Iterative Refinement Scheme refines box-level content to align with textual descriptions, ensuring consistency and improving recall compared to baseline diffusion models.

Align lessons to Common Core math standards

Align lessons to Next Generation Science Standards

Guides strategic workforce planning to align with organizational goals.

Align, organize, and enhance design assets effortlessly.

Helps UK firms align marketing content with the FCA's financial promotion rules and the CAP Code 📋

Rewrites resumes to align with targeted job postings.

Your go-to for understanding how current events align with generational cycles.

I'll help you revise your docs to align more closely with best practise.

"mySCRIPTGenius360 specializes in crafting SEO-friendly YouTube scripts that align with user preferences and search optimization goals. We maintain high content standards, prioritize originality, and provide tailored guidance for enhanced engagement."

I am a GPT specialized in providing bespoke recommendations for colognes and perfumes. My expertise extends to crafting unique fragrance creations, tailored to align with your individual preferences.

Insights on Diversity, Equality, and Inclusion - This AI chat provides info on DEI topics, but opinions may not align with all views. Use responsibly, consult experts, and promote respectful discussions.

Crea situaciones de aprendizaje de acuerdo a los Currículos de Educacion Secundaria y Bachillerato de Asturias en el marco de la LOMLOE, para la especialidad, curso y temática proporcionados

Your guide to aligning lesson plans with Common Core standards. Standards checked and updated daily.

根据《战略地图》回答问题

Sharpening Business Ideas is an AI-driven tool that refines business concepts and evaluates pitches. It aligns ideas with market trends and best practices, transforming them into market-ready proposals. Perfect for entrepreneurs and innovators, Your own Shark Tank for strategic guidance

Engaging and supportive AI for strategic OKR planning.

Conselheiro financeiro que combina Neville Goddard e Napoleon Hill para orientações práticas e alinhamento de crenças.

Guiding you from ambiguous ideas through structured and effective OKRs (Objectives and Key Results)

Creates measurable objectives from educational documents and suggests assessments based on those LO's. PDF's work best.

Encourages with positive, practical OKR guidance