Best AI tools for< Research Code Structures >

Synthace is a digital experiment platform designed for R&D teams in the life science industry. It allows users to design and run powerful experiments in the lab, automatically build structured data, and gain insights without the need for coding. The platform centralizes bioprocess data, reduces human error, and enables confident protocol reproducibility.

Papers With Code is an AI tool that provides access to the latest research papers in the field of Machine Learning, along with corresponding code implementations. It offers a platform for researchers and enthusiasts to stay updated on state-of-the-art datasets, methods, and trends in the ML domain. Users can explore a wide range of topics such as language modeling, image generation, virtual try-on, and more through the collection of papers and code available on the website.

Google Colab is a free Jupyter notebook environment that runs in the cloud. It allows you to write and execute Python code without having to install any software or set up a local environment. Colab notebooks are shareable, so you can easily collaborate with others on projects.

Beebzi.AI is an all-in-one AI content creation platform that offers a wide array of tools for generating various types of content such as articles, blogs, emails, images, voiceovers, and more. The platform utilizes advanced AI technology and behavioral science to empower businesses and individuals in their marketing and sales endeavors. With features like AI Article Wizard, AI Room Designer, AI Landing Page Generator, and AI Code Generation, Beebzi.AI revolutionizes content creation by providing customizable templates, multiple language support, and real-time data insights. The platform also offers various subscription plans tailored for individual entrepreneurs, teams, and businesses, with flexible pricing models based on word count allocations. Beebzi.AI aims to streamline content creation processes, enhance productivity, and drive organic traffic through SEO-optimized content.

Anthropic is an AI safety and research company based in San Francisco. Our interdisciplinary team has experience across ML, physics, policy, and product. Together, we generate research and create reliable, beneficial AI systems.

JADBio is an automated machine learning (AutoML) platform designed to accelerate biomarker discovery and drug development processes. It offers a no-code solution that automates the discovery of biomarkers and interprets their role based on research needs. JADBio can parse multi-omics data, including genomics, transcriptome, metagenome, proteome, metabolome, phenotype/clinical data, and images, enabling users to efficiently discover valuable insights. The platform is purpose-built for various conditions such as cancer, immune, endocrine, metabolic system, chronic diseases, aging, infectious diseases, and mental health, offering solutions for early biomarker discovery, drug repurposing, lead identification, compound optimization, trial monitoring, and response to treatment. JADBio is trusted by partners in precision health & medicine and is continuously evolving to disrupt drug discovery times and costs at all stages.

UpCodes is a searchable platform designed for architects, engineers, and construction professionals to easily access building codes, assemblies, and building products. It provides a user-friendly interface for quick and efficient navigation through complex regulations and standards, streamlining the design and construction process. With UpCodes, users can search, compare, and analyze building codes and products, ensuring compliance and quality in their projects.

Glog is an AI application focused on making software more secure by providing remediation advice for security vulnerabilities in software code based on context. It is capable of automatically fixing vulnerabilities, thus reducing security risks and protecting against cyber attacks. The platform utilizes machine learning and AI to enhance software security and agility, ensuring system reliability, integrity, and safety.

Domino Data Lab is an enterprise AI platform that enables data scientists and IT leaders to build, deploy, and manage AI models at scale. It provides a unified platform for accessing data, tools, compute, models, and projects across any environment. Domino also fosters collaboration, establishes best practices, and tracks models in production to accelerate and scale AI while ensuring governance and reducing costs.

Merlin AI is an AI Chrome Extension and web app that serves as an AI-powered assistant, offering top AI models like ChatGPT, GPT 4, Claude, Opus, Llama, Mistral, and more. It enables users to generate AI responses on Google search, summarize YouTube videos, blogs, and documents, write posts and replies on social media platforms, and translate into over twenty-five languages. Merlin is designed to save time and money by providing a range of AI functionalities for various tasks across different industries.

GPT Assistant is an advanced AI chatbot designed for seamless conversations and helpful assistance. It offers fast and authentic AI responses, advanced natural language processing, and intelligent assistance with PDFs. The application integrates directly into Discord, providing users with convenient access to its powerful AI capabilities. Users can maximize productivity, streamline workflows, and engage in interactive and collaborative conversations effortlessly. GPT Assistant simplifies tasks such as summarizing PDF documents, enhancing coding experiences, and fostering community interactions through AI integration.

Domino Data Lab is an enterprise AI platform that enables users to build, deploy, and manage AI models across any environment. It fosters collaboration, establishes best practices, and ensures governance while reducing costs. The platform provides access to a broad ecosystem of open source and commercial tools, and infrastructure, allowing users to accelerate and scale AI impact. Domino serves as a central hub for AI operations and knowledge, offering integrated workflows, automation, and hybrid multicloud capabilities. It helps users optimize compute utilization, enforce compliance, and centralize knowledge across teams.

Powerdrill is a platform that provides swift insights from knowledge and data. It offers a range of features such as discovering datasets, creating BI dashboards, accessing various apps, resources, blogs, documentation, and changelogs. The platform is available in English and fosters a community through its affiliate program. Users can sign up for a basic plan to start utilizing the tools and services offered by Powerdrill.

Bionl is a no-code bioinformatics platform designed to streamline biomedical research for researchers and scientists. It offers a full workspace with features such as bioinformatics pipelines customization, GenAI for data analysis, AI-powered literature search, PDF analysis, and access to public datasets. Bionl aims to automate cloud, file system, data, and workflow management for efficient and precise analyses. The platform caters to Pharma and Biotech companies, academic researchers, and bioinformatics CROs, providing powerful tools for genetic analysis and speeding up research processes.

Kombai is an AI tool designed to code email and web designs like humans. It uses deep learning and heuristics models to interpret UI designs and generate high-quality HTML, CSS, or React code with human-like names for classes and components. Kombai aims to help developers save time by automating the process of writing UI code based on design files without the need for tagging, naming, or grouping elements. The tool is currently in 'public research preview' and is free for individual developers to use.

CompFox is an AI-enhanced legal research tool designed for workers' compensation professionals in California. It streamlines legal research by providing access to a comprehensive database of workers' compensation case law and statutory codes. With features like AI-driven search, chat for case-specific analysis, intelligent case file analysis, collaborative research folders, and one-stop statutory code search, CompFox helps attorneys and insurance adjusters save time, reduce stress, and improve case outcomes.

Speak Ai is an AI-powered software that helps businesses and individuals transcribe, analyze, and visualize unstructured language data. With Speak Ai, users can automatically transcribe audio and video recordings, analyze text data, and generate insights from qualitative research. Speak Ai also offers a range of features to help users manage and share their data, including embeddable recorders, integrations with popular applications, and secure data storage.

mypapers.ai is an AI tool designed to assist users in managing and analyzing academic papers efficiently. The tool offers features such as exploring papers and authors, toggling between papers and authors, and tracking the journey of research. Users can also access the code on GitHub to further enhance their research capabilities.

TailorTask is an AI-powered automation tool designed to help users automate repetitive tasks efficiently. It offers a user-friendly interface that allows non-technical individuals to easily interact with the AI. The tool integrates with various platforms and tools, enabling seamless automation processes. TailorTask prioritizes data privacy and security, ensuring that users have full control over the AI's actions. With features like custom workflows, task scheduling, and detailed instructions, TailorTask aims to save users time and effort by automating tasks across different domains.

AiPlus is an AI tool designed to serve as a cost-efficient model gateway. It offers users a platform to access and utilize various AI models for their projects and tasks. With AiPlus, users can easily integrate AI capabilities into their applications without the need for extensive development or resources. The tool aims to streamline the process of leveraging AI technology, making it accessible to a wider audience.

RA.Aid is an AI software development agent powered by `aider` and advanced reasoning models like `o1`. It combines `aider`'s code editing capabilities with LangChain's agent-based task execution framework to provide an intelligent assistant for research, planning, and implementation of multi-step development tasks. It handles complex programming tasks by breaking them down into manageable steps, running shell commands automatically, and leveraging expert reasoning models like OpenAI's o1. RA.Aid is designed for everyday software development, offering features such as multi-step task planning, automated command execution, and the ability to handle complex programming tasks beyond single-shot code edits.

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)

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

A curated list of Generative AI projects, tools, artworks, and models

MetaGPT is a multi-agent framework that enables GPT to work in a software company, collaborating to tackle more complex tasks. It assigns different roles to GPTs to form a collaborative entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories, competitive analysis, requirements, data structures, APIs, documents, etc. Internally, MetaGPT includes product managers, architects, project managers, and engineers. It provides the entire process of a software company along with carefully orchestrated SOPs. MetaGPT's core philosophy is "Code = SOP(Team)", materializing SOP and applying it to teams composed of LLMs.

AI2BMD is a program for efficiently simulating protein molecular dynamics with ab initio accuracy. The repository contains datasets, simulation programs, and public materials related to AI2BMD. It provides a Docker image for easy deployment and a standalone launcher program. Users can run simulations by downloading the launcher script and specifying simulation parameters. The repository also includes ready-to-use protein structures for testing. AI2BMD is designed for x86-64 GNU/Linux systems with recommended hardware specifications. The related research includes model architectures like ViSNet, Geoformer, and fine-grained force metrics for MLFF. Citation information and contact details for the AI2BMD Team are provided.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

TaskWeaver is a code-first agent framework designed for planning and executing data analytics tasks. It interprets user requests through code snippets, coordinates various plugins to execute tasks in a stateful manner, and preserves both chat history and code execution history. It supports rich data structures, customized algorithms, domain-specific knowledge incorporation, stateful execution, code verification, easy debugging, security considerations, and easy extension. TaskWeaver is easy to use with CLI and WebUI support, and it can be integrated as a library. It offers detailed documentation, demo examples, and citation guidelines.

Awesome Mamba is a curated collection of groundbreaking research papers and articles on Mamba Architecture, a pioneering framework in deep learning known for its selective state spaces and efficiency in processing complex data structures. The repository offers a comprehensive exploration of Mamba architecture through categorized research papers covering various domains like visual recognition, speech processing, remote sensing, video processing, activity recognition, image enhancement, medical imaging, reinforcement learning, natural language processing, 3D recognition, multi-modal understanding, time series analysis, graph neural networks, point cloud analysis, and tabular data handling.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

This repository contains the code for the paper Fine-Tuned Language Models Generate Stable Inorganic Materials as Text. It demonstrates how finetuned LLMs can be used to generate stable materials, match or exceed the performance of domain specific models, mutate existing materials, and sample crystal structures conditioned on text descriptions. The method is distinct from CrystaLLM, which trains language models from scratch on CIF-formatted crystals.

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.

The 'awesome-AI4MolConformation-MD' repository focuses on protein conformations and molecular dynamics using generative artificial intelligence and deep learning. It provides resources, reviews, datasets, packages, and tools related to AI-driven molecular dynamics simulations. The repository covers a wide range of topics such as neural networks potentials, force fields, AI engines/frameworks, trajectory analysis, visualization tools, and various AI-based models for protein conformational sampling. It serves as a comprehensive guide for researchers and practitioners interested in leveraging AI for studying molecular structures and dynamics.

LLM4Decompile is an open-source large language model dedicated to decompilation of Linux x86_64 binaries, supporting GCC's O0 to O3 optimization levels. It focuses on assessing re-executability of decompiled code through HumanEval-Decompile benchmark. The tool includes models with sizes ranging from 1.3 billion to 33 billion parameters, available on Hugging Face. Users can preprocess C code into binary and assembly instructions, then decompile assembly instructions into C using LLM4Decompile. Ongoing efforts aim to expand capabilities to support more architectures and configurations, integrate with decompilation tools like Ghidra and Rizin, and enhance performance with larger training datasets.

RD-Agent is a tool designed to automate critical aspects of industrial R&D processes, focusing on data-driven scenarios to streamline model and data development. It aims to propose new ideas ('R') and implement them ('D') automatically, leading to solutions of significant industrial value. The tool supports scenarios like Automated Quantitative Trading, Data Mining Agent, Research Copilot, and more, with a framework to push the boundaries of research in data science. Users can create a Conda environment, install the RDAgent package from PyPI, configure GPT model, and run various applications for tasks like quantitative trading, model evolution, medical prediction, and more. The tool is intended to enhance R&D processes and boost productivity in industrial settings.

HuggingFists is a low-code data flow tool that enables convenient use of LLM and HuggingFace models. It provides functionalities similar to Langchain, allowing users to design, debug, and manage data processing workflows, create and schedule workflow jobs, manage resources environment, and handle various data artifact resources. The tool also offers account management for users, allowing centralized management of data source accounts and API accounts. Users can access Hugging Face models through the Inference API or locally deployed models, as well as datasets on Hugging Face. HuggingFists supports breakpoint debugging, branch selection, function calls, workflow variables, and more to assist users in developing complex data processing workflows.

Forust is a lightweight package for building gradient boosted decision tree ensembles. The algorithm code is written in Rust with a Python wrapper. It implements the same algorithm as XGBoost and provides nearly identical results. The package was developed to better understand XGBoost, as a fun project in Rust, and to experiment with adding new features to the algorithm in a simpler codebase. Forust allows training gradient boosted decision tree ensembles with multiple objective functions, predicting on datasets, inspecting model structures, calculating feature importance, and saving/loading trained boosters.

Awesome-LLM-Interpretability is a curated list of materials related to LLM (Large Language Models) interpretability, covering tutorials, code libraries, surveys, videos, papers, and blogs. It includes resources on transformer mechanistic interpretability, visualization, interventions, probing, fine-tuning, feature representation, learning dynamics, knowledge editing, hallucination detection, and redundancy analysis. The repository aims to provide a comprehensive overview of tools, techniques, and methods for understanding and interpreting the inner workings of large language models.

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