Best AI tools for< Chain-of-thought Engineer >

RELEX Solutions is a market-leading supply chain and retail planning platform that leverages artificial intelligence to revolutionize supply chains. The platform offers end-to-end inventory planning, production scheduling, demand forecasting, merchandising, assortment planning, price optimization, promotion planning, and more. RELEX enables retailers and consumer goods companies to align their supply chain and retail operations with actual demand, driving profitability through increased sales and reduced costs while minimizing waste. The platform caters to various industries such as retail, convenience, electronics, grocery, health, beauty, pharmaceutical, and more, providing tailored solutions for each sector.

The Intelligent Logistics Platform, Raft, is an AI-powered workflow automation tool designed for freight forwarders and customs brokers. It streamlines various logistics processes such as finance, customs, and operations by leveraging AI technology to enhance efficiency, accuracy, and customer value throughout the shipment lifecycle. Raft combines cutting-edge AI advancements with a vast amount of supply-chain specific data to provide users with a comprehensive platform for managing logistics operations.

Cortex Labs is a decentralized world computer that enables AI and AI-powered decentralized applications (dApps) to run on the blockchain. It offers a Layer2 solution called ZkMatrix, which utilizes zkRollup technology to enhance transaction speed and reduce fees. Cortex Virtual Machine (CVM) supports on-chain AI inference using GPU, ensuring deterministic results across computing environments. Cortex also enables machine learning in smart contracts and dApps, fostering an open-source ecosystem for AI researchers and developers to share models. The platform aims to solve the challenge of on-chain machine learning execution efficiently and deterministically, providing tools and resources for developers to integrate AI into blockchain applications.

Supply Chain Intelligence is an AI application that offers a comprehensive suite of tools for supply chain management. It provides advanced demand forecasting capabilities, digitization guidance, AI forecast model creation, forecasting segmentation, and assessment of demand forecasting process maturity. The application aims to streamline supply chain operations, enhance decision-making, and optimize planning processes through the use of artificial intelligence technologies.

SENEX is an AI-powered Blockchain company that aims to create the world's finest Intelligent Chain. It combines Artificial Intelligence with Blockchain technology to provide a privacy-compliant and secure platform for digital users and businesses. SENEX's Intelligent Chain distributes data processing across the network while keeping information private and secure, giving users the benefits of anonymity. The company's AI-powered solutions address various challenges and problems in industries such as healthcare, finance, transportation, and education.

MetaMevs is an advanced AI-powered trading solution designed to maximize profits in the fast-paced world of decentralized finance (DeFi). The platform offers cutting-edge technology and customizable solutions to help traders stay ahead of the curve and capitalize on market opportunities. With features like Sandwich Mevbot, HFT Futures and Spot Bot, FlashLoan Arbitrage Bot, and MetaMev Sniper, MetaMevs provides unmatched performance, security, and reliability for users to optimize their trading strategies.

Nextpart.ai is an AI-powered tool that helps businesses automate their procurement processes. It uses machine learning to analyze spending data and identify opportunities for savings. Nextpart.ai also provides a marketplace where businesses can connect with suppliers and get quotes on products and services.

The Value Chain Generator® is an AI & Big Data platform for circular bioeconomy that helps companies, waste processors, and regions maximize the value and minimize the carbon footprint of by-products and waste. It uses global techno-economic and climate intelligence to identify circular opportunities, match with suitable partners and technologies, and create profitable and impactful solutions. The platform accelerates the circular transition by integrating local industries through technology, reducing waste, and increasing profits.

CommodityAI is a web-based platform that uses AI, automation, and collaboration tools to help businesses manage their commodity shipments and supply chains more efficiently. The platform offers a range of features, including shipment management automation, intelligent document processing, stakeholder collaboration, and supply-chain automation. CommodityAI can help businesses improve data accuracy, eliminate manual processes, and streamline communication and collaboration. The platform is designed for the commodities industry and offers commodity-specific automations, ERP integration, and AI-powered insights.

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Kinaxis is an AI-powered platform that offers end-to-end supply chain orchestration solutions for businesses. It helps companies respond with agility by coordinating all parts of the supply chain using artificial intelligence. With features like transparency, collaboration, adaptability, and intelligence, Kinaxis enables users to make faster, smarter, and more confident decisions. The platform offers solutions for supply chain control tower, S&OP, demand planning, inventory management, scheduling, order management, transportation, and returns management. Kinaxis is designed to streamline operations, improve efficiency, and drive sustainable supply chain practices.

Greenbids is an AI application designed to minimize inefficiencies and enhance media performance in digital advertising, contributing to decarbonization efforts. By utilizing Machine Learning, Greenbids saves 1000 tons of CO2 every month and drives sustainable media effectiveness across the advertising ecosystem. The platform offers a unique solution to decrease ads' carbon footprint, with an average carbon intensity reduction of 36% and a 27% increase in media effectiveness. Greenbids aims to address the environmental impact of programmatic advertising by providing a more sustainable and efficient alternative.

BluePond GenAI PaaS is an automation and insights powerhouse tailored for Property and Casualty Insurance. It offers end-to-end execution support from GenAI data scientists, engineers & human-in-the-loop processing. The platform provides automated intake extraction, classification enrichment, validation, complex document analysis, workflow automation, and decisioning. Users benefit from rapid deployment, complete control of data & IP, and pre-trained P&C domain library. BluePond GenAI PaaS aims to energize and expedite GenAI initiatives throughout the insurance value chain.

ChainGPT is a cutting-edge AI infrastructure focused on developing AI-enhanced solutions for the Web3, Blockchain, and Cryptocurrency sectors. It aims to make the decentralized digital space more accessible and efficient for users and startups by offering a suite of AI-powered tools and applications tailored for the evolving digital landscape.

Transmetrics is an AI-powered logistics planning platform that helps businesses optimize their supply chain and logistics operations. It provides a range of features, including data analytics, forecasting, optimization, and asset management. Transmetrics helps businesses improve their capacity utilization, reduce costs, and increase efficiency.

Mazaal AI is an end-to-end no-code AI platform that empowers businesses to boost their workforce with AI automation. The platform allows users to transform data into powerful AI solutions without the need for coding. With a focus on pre-trained models and seamless integration, Mazaal AI helps businesses optimize production, manage inventory effectively, predict future demand accurately, and enhance customer satisfaction.

Automaited is an AI application that offers Ada - an AI Agent for automating order processing. Ada handles orders from receipt to ERP entry, extracting, validating, and transferring data to ensure accuracy and efficiency. The application utilizes state-of-the-art AI technology to streamline order processing, saving time, reducing errors, and enabling users to focus on customer satisfaction. With seamless automation, Ada integrates into ERP systems, making order processing effortless, quick, and cost-efficient. Automaited provides tailored automations to make operational processes up to 70% more efficient, enhancing performance and reducing error rates.

ToolsGroup is an AI-powered supply chain and retail planning application that helps retailers, distributors, and manufacturers enhance the resilience and performance of their operations. Leveraging AI and real-time data, ToolsGroup offers probabilistic planning solutions for demand forecasting, inventory optimization, replenishment, assortment planning, and more. The application automates manual tasks, guides smarter decisions with AI, and delivers outstanding customer experiences with real-time visibility across the enterprise.

Sensei AI is a real-time interview copilot application designed to provide assistance during live interviews. It offers instant answers to questions, personalized responses, and aims to help users land their dream job. The application uses advanced AI insights to understand the true intent behind interview questions, tailoring responses based on tone, word choices, keywords, timing, formality level, and context. Sensei AI also offers a hands-free experience, robust privacy features, and a personalized interview experience by tailoring answers to the user's job role, resume, and personal stories.

Web3 Summary is an AI-powered platform that simplifies on-chain research across multiple chains and protocols, helping users find trading alpha in the DeFi and NFT space. It offers a range of products including a trading terminal, wallet study tool, Discord bot, mobile app, and Chrome extension. The platform aims to streamline the process of understanding complex crypto projects and tokenomics using AI and ChatGPT technology.

EdgeChains is an open-source chain-of-thought engineering framework tailored for Large Language Models (LLMs)- like OpenAI GPT, LLama2, Falcon, etc. - With a focus on enterprise-grade deployability and scalability. EdgeChains is specifically designed to **orchestrate** such applications. At EdgeChains, we take a unique approach to Generative AI - we think Generative AI is a deployment and configuration management challenge rather than a UI and library design pattern challenge. We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

Project Miyagi showcases Microsoft's Copilot Stack in an envisioning workshop aimed at designing, developing, and deploying enterprise-grade intelligent apps. By exploring both generative and traditional ML use cases, Miyagi offers an experiential approach to developing AI-infused product experiences that enhance productivity and enable hyper-personalization. Additionally, the workshop introduces traditional software engineers to emerging design patterns in prompt engineering, such as chain-of-thought and retrieval-augmentation, as well as to techniques like vectorization for long-term memory, fine-tuning of OSS models, agent-like orchestration, and plugins or tools for augmenting and grounding LLMs.

Repository for training and deploying Generative AI models, including text-text, text-to-image generation, prompt engineering playground and chain of thought examples using SageMaker Studio. The tool provides a platform for users to experiment with generative AI techniques, enabling them to create text and image outputs based on input data. It offers a range of functionalities for training and deploying models, as well as exploring different generative AI applications.

Awesome GPT Prompt Engineering is a curated list of resources, tools, and shiny things for GPT prompt engineering. It includes roadmaps, guides, techniques, prompt collections, papers, books, communities, prompt generators, Auto-GPT related tools, prompt injection information, ChatGPT plug-ins, prompt engineering job offers, and AI links directories. The repository aims to provide a comprehensive guide for prompt engineering enthusiasts, covering various aspects of working with GPT models and improving communication with AI tools.

MMLU-Pro is an enhanced benchmark designed to evaluate language understanding models across broader and more challenging tasks. It integrates more challenging, reasoning-focused questions and increases answer choices per question, significantly raising difficulty. The dataset comprises over 12,000 questions from academic exams and textbooks across 14 diverse domains. Experimental results show a significant drop in accuracy compared to the original MMLU, with greater stability under varying prompts. Models utilizing Chain of Thought reasoning achieved better performance on MMLU-Pro.

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features include: * Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 70+ datasets with about 400,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. * Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. * Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue-type prompt templates, to easily stimulate the maximum performance of various models. * Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! * Experiment management and reporting mechanism: Use config files to fully record each experiment, and support real-time reporting of results.

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.

BIG-Bench Mistake is a dataset of chain-of-thought (CoT) outputs annotated with the location of the first logical mistake. It was released as part of a research paper focusing on benchmarking LLMs in terms of their mistake-finding ability. The dataset includes CoT traces for tasks like Word Sorting, Tracking Shuffled Objects, Logical Deduction, Multistep Arithmetic, and Dyck Languages. Human annotators were recruited to identify mistake steps in these tasks, with automated annotation for Dyck Languages. Each JSONL file contains input questions, steps in the chain of thoughts, model's answer, correct answer, and the index of the first logical mistake.

LLMClient is a JavaScript/TypeScript library that simplifies working with large language models (LLMs) by providing an easy-to-use interface for building and composing efficient prompts using prompt signatures. These signatures enable the automatic generation of typed prompts, allowing developers to leverage advanced capabilities like reasoning, function calling, RAG, ReAcT, and Chain of Thought. The library supports various LLMs and vector databases, making it a versatile tool for a wide range of applications.

MathVerse is an all-around visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving. It collects high-quality math problems with diagrams to assess how well MLLMs can understand visual diagrams for mathematical reasoning. The benchmark includes 2,612 problems transformed into six versions each, contributing to 15K test samples. It also introduces a Chain-of-Thought (CoT) Evaluation strategy for fine-grained assessment of output answers.

gollm is a Go package designed to simplify interactions with Large Language Models (LLMs) for AI engineers and developers. It offers a unified API for multiple LLM providers, easy provider and model switching, flexible configuration options, advanced prompt engineering, prompt optimization, memory retention, structured output and validation, provider comparison tools, high-level AI functions, robust error handling and retries, and extensible architecture. The package enables users to create AI-powered golems for tasks like content creation workflows, complex reasoning tasks, structured data generation, model performance analysis, prompt optimization, and creating a mixture of agents.

An Open-Source Engineering Guide for Prompt-in-context-learning from EgoAlpha Lab. 📝 Papers | ⚡️ Playground | 🛠 Prompt Engineering | 🌍 ChatGPT Prompt | ⛳ LLMs Usage Guide > **⭐️ Shining ⭐️:** This is fresh, daily-updated resources for in-context learning and prompt engineering. As Artificial General Intelligence (AGI) is approaching, let’s take action and become a super learner so as to position ourselves at the forefront of this exciting era and strive for personal and professional greatness. The resources include: _🎉Papers🎉_: The latest papers about _In-Context Learning_ , _Prompt Engineering_ , _Agent_ , and _Foundation Models_. _🎉Playground🎉_: Large language models（LLMs）that enable prompt experimentation. _🎉Prompt Engineering🎉_: Prompt techniques for leveraging large language models. _🎉ChatGPT Prompt🎉_: Prompt examples that can be applied in our work and daily lives. _🎉LLMs Usage Guide🎉_: The method for quickly getting started with large language models by using LangChain. In the future, there will likely be two types of people on Earth (perhaps even on Mars, but that's a question for Musk): - Those who enhance their abilities through the use of AIGC; - Those whose jobs are replaced by AI automation. 💎EgoAlpha: Hello! human👤, are you ready?

ICE-Score is a tool designed to instruct large language models to evaluate code. It provides a minimum viable product (MVP) for evaluating generated code snippets using inputs such as problem, output, task, aspect, and model. Users can also evaluate with reference code and enable zero-shot chain-of-thought evaluation. The tool is built on codegen-metrics and code-bert-score repositories and includes datasets like CoNaLa and HumanEval. ICE-Score has been accepted to EACL 2024.

LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

This repository contains course materials for T81 559: Applications of Generative Artificial Intelligence at Washington University in St. Louis. The course covers practical applications of Large Language Models (LLMs) and text-to-image networks using Python. Students learn about generative AI principles, LangChain, Retrieval-Augmented Generation (RAG) model, image generation techniques, fine-tuning neural networks, and prompt engineering. Ideal for students, researchers, and professionals in computer science, the course offers a transformative learning experience in the realm of Generative AI.

Awesome-AGI is a curated list of resources related to Artificial General Intelligence (AGI), including models, pipelines, applications, and concepts. It provides a comprehensive overview of the current state of AGI research and development, covering various aspects such as model training, fine-tuning, deployment, and applications in different domains. The repository also includes resources on prompt engineering, RLHF, LLM vocabulary expansion, long text generation, hallucination mitigation, controllability and safety, and text detection. It serves as a valuable resource for researchers, practitioners, and anyone interested in the field of AGI.

This repository contains the training and inference code needed to replicate the winning solution to the AI Mathematical Olympiad - Progress Prize 1. It consists of fine-tuning DeepSeekMath-Base 7B, high-quality training datasets, a self-consistency decoding algorithm, and carefully chosen validation sets. The training methodology involves Chain of Thought (CoT) and Tool Integrated Reasoning (TIR) training stages. Two datasets, NuminaMath-CoT and NuminaMath-TIR, were used to fine-tune the models. The models were trained using open-source libraries like TRL, PyTorch, vLLM, and DeepSpeed. Post-training quantization to 8-bit precision was done to improve performance on Kaggle's T4 GPUs. The project structure includes scripts for training, quantization, and inference, along with necessary installation instructions and hardware/software specifications.

Notes on AI state of the art, with a focus on generative and large language models. These are the "raw materials" for the https://lspace.swyx.io/ newsletter. This repo used to be called https://github.com/sw-yx/prompt-eng, but was renamed because Prompt Engineering is Overhyped. This is now an AI Engineering notes repo.

LLMBox is a comprehensive library designed for implementing Large Language Models (LLMs) with a focus on a unified training pipeline and comprehensive model evaluation. It serves as a one-stop solution for training and utilizing LLMs, offering flexibility and efficiency in both training and utilization stages. The library supports diverse training strategies, comprehensive datasets, tokenizer vocabulary merging, data construction strategies, parameter efficient fine-tuning, and efficient training methods. For utilization, LLMBox provides comprehensive evaluation on various datasets, in-context learning strategies, chain-of-thought evaluation, evaluation methods, prefix caching for faster inference, support for specific LLM models like vLLM and Flash Attention, and quantization options. The tool is suitable for researchers and developers working with LLMs for natural language processing tasks.

Guides you through detailed reasoning to find well-supported answers.

Solve math and logic with Smart GPT. Use Tree and Chain of thoughts to organize and find answers.

I'm a GPT that plays Word Chain, responding with words starting with your word's last letter.

This prompt is structured to provide an effective methodology in generating progressively more detailed and specific summaries, focused on key entities.

Given a set of Parameters, Provides a set of Order Recommendations

PLM Body of Knowledge

Your go-to guide for everything in the World of Procurement .

A knowledgeable and patient teacher in logistics, offering insights and guidance.

A futuristic computer translating Japanese to simple English.

Marie Chan loves tidy bedrooms and playrooms. With her help, kids and grown ups will learn the joy of staying well organized.

Join as the Third Chair guest with Destin Sandlin and Matt Whitman in a new podcast episode of ‎ ‎ ‎ 🧮𝗡𝗗𝗤✝️ - Game

Helper for Wardley Map value chain analysis

your real time expert while you negotiate

I calculate and recommend tire chain sizes based on your tire specs.

Innovative, expert supply chain insights on demand. Bring all your operational challenges to us while you focus on growing your business.

An AI assistant for CCA, a supply chain technology company that focuses on providing digital drayage platform and TMS solution to our importer customers and carrier partners

Chat-driven supply chain wisdom powered by live data and trained on news, tutorials and resources.

Guide for clear, ethical supply chain solutions

On-chain analysis educator for financial pros.

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