Best AI tools for< Predicting Molecular Properties >

Allchemy is a resource-aware AI platform for drug discovery. It combines state-of-the-art computational synthesis with AI algorithms to predict molecular properties. Within minutes, Allchemy creates thousands of synthesizable lead candidates meeting user-defined profiles of drug-likeness, affinity towards specific proteins, toxicity, and a range of other physical-chemical measures. Allchemy encompasses the entire resource-to-drug design process and has been used in academic, corporate and classified environments worldwide to: Design synthesizable leads targeting specific proteins Evolve scaffolds similar to desired drugs Design “circular” drug syntheses from renewable materials Interface with and instruct automated synthesis platforms and optimize pilot-scale processes Operate “iterative synthesis” schemes Predict side reactions and create forensic “synthetic signatures” of hazardous/toxic molecules Design synthetic degradation and recovery cycles for various types of feedstocks and functional target molecules

HUAWEI Cloud Pangu is an AI tool designed for accelerating drug discovery by optimizing drug molecules. It offers features such as Molecule Search, Molecule Optimizer, and Pocket Molecule Design. Users can submit molecules for optimization and view historical optimization results. The tool is based on the MindSpore framework and has been visited over 300,000 times since August 23, 2021.

Lavo Life Sciences is an AI-accelerated crystal structure prediction application that aims to accelerate drug development processes. The platform provides solutions for de-risking pipelines, optimizing solid-state formulations, and avoiding late-stage surprises using AI technology. Lavo Life Sciences combines the expertise of chemists and engineers in AI and computational chemistry to offer innovative solutions for drug development teams.

赤ちゃんAC is an AI application that predicts the face of a baby by using AI technology called StyleGAN. Users can upload two images of parents' faces, and the AI analyzes and generates a high-resolution image of a baby's face with features resembling the parents. The application is user-friendly and offers the service of predicting baby faces from infancy to adulthood in six stages. It ensures security by deleting all image data within 24 hours. 赤ちゃんAC prohibits certain uses, such as using the generated images for profile icons, creating misleading representations, or engaging in adult content.

BetSense.ai is an AI sports predicting tool that leverages cutting-edge AI technology to help users make informed decisions in sports betting. The tool provides data-driven predictions based on historical and recent data inputs, covering top soccer leagues and offering daily AI predictions. With a focus on increasing productivity, BetSense.ai offers insights, machine learning capabilities, and access to an extended range of computer predictions. Users can subscribe to monthly or yearly plans for different levels of access and insights.

FutureGPT is an AI tool that leverages the power of GPT-4 to provide advanced predictive capabilities. Users can enhance their outcomes by utilizing paid predictions through this application. By enabling JavaScript, users can access the predictive features and settings to improve their decision-making processes.

Obviously AI is a no-code AI tool that allows users to build and deploy machine learning models without writing any code. It is designed to be easy to use, even for those with no data science experience. Obviously AI offers a variety of features, including model building, model deployment, model monitoring, and integration with other tools. It also provides expert support from a dedicated data scientist.

Lotto Chart is a highly accurate AI-powered chart for predicting lottery numbers. It harnesses the power of artificial intelligence, statistical analysis, and probability to generate winning combinations for various lotteries. The application processes billions of data points, utilizes 7 powerful prediction models, and provides advanced data-driven predictions to help users increase their chances of winning. Lotto Chart also offers support for seeded predictions, daily updated insights and reports, and tools to easily identify patterns and trends in lottery numbers.

Hook is an AI-powered platform designed to help businesses grow their revenue by accurately predicting high-value customers, reducing churn, increasing expansion revenue, and actively managing accounts. The platform uses AI to analyze usage patterns and third-party data to prioritize customers for revenue growth and upsells. With a focus on data-driven decision-making, Hook empowers revenue teams to make informed choices and drive business growth.

SynPlan is an AI solution designed to optimize healthcare workforce planning by predicting sick-leave absence and budget expenses. By utilizing advanced AI technology, SynPlan assists healthcare organizations in creating efficient plans, controlling budgets, and ensuring compliance with regulations. The application streamlines the staff planning process, enhances employee involvement, and increases continuity for patients. SynPlan is a product from Chiron Predictive Technologies AS, offering a comprehensive solution for workforce optimization in the healthcare sector.

Onoco is a comprehensive parenting app that combines tracking, predicting, and sharing care for babies. It offers a smart, simple, safe, and easy-to-share platform for parents to monitor their baby's development milestones, daily routines, and growth. Onoco empowers parents with expert knowledge on essential topics such as baby sleep, nutrition, and postpartum health. The app allows users to create personalized routines, monitor important milestones, share updates with caregivers, and receive brain-building tips tailored to their child's age. Onoco also facilitates communication between parents and caregivers, ensuring transparency and trust in childcare arrangements.

Setlist Predictor is an AI tool designed to help music enthusiasts and concert-goers stay ahead by predicting the setlist of their favorite artists. By leveraging the latest data and AI technology, users can easily access the expected songs to be performed at upcoming concerts. The tool aims to enhance the concert experience by providing valuable insights and eliminating the uncertainty of not knowing the setlist in advance.

Cursor is an AI code editor designed to enhance productivity by leveraging artificial intelligence. It allows developers to code more efficiently by predicting edits, writing code using natural language instructions, and providing quick access to codebase information. Cursor prioritizes privacy and security, ensuring that no code is stored by the platform. It is trusted by engineers worldwide and offers a seamless coding experience with regular updates and new features.

BabyFaceGenerator is an AI-based tool that analyzes up to 70 facial features of two partners to generate the face of a future baby. While it provides entertainment by predicting what a baby might look like, it is important to note that genetics are much more complex than the tool can accurately represent. The tool is available in multiple languages and offers a fun way for users to visualize potential offspring.

Keepme is an AI-powered platform designed for gyms to boost sales, predict and prevent attrition, and enhance member retention. It offers features such as Keepme Score™ for predicting attrition, smart lead scoring, gym tours & trials scheduler, NPS surveys, smart campaigns & automations, smart content production, and WhatsApp integration. The platform provides personalized training and world-class support through Keepme Academy and customer success team. Keepme is trusted by over 450 fitness clubs globally and offers valuable AI resources to empower users with knowledge.

Nudify.me is an AI-powered application that utilizes DeepNude technology to generate nudified images from uploaded photos. The app offers a simple and secure way to view individuals in the nude by predicting their appearance with high accuracy. Users can upload photos, select a generation mode, and receive the nudified result within seconds. Nudify.me also provides options for privacy settings and profit-sharing from public galleries. The application offers transparent pricing plans tailored to different user needs, with no hidden fees or long-term contracts.

Gradient AI is a leading provider of artificial intelligence solutions for the insurance industry. Their solutions improve loss ratios and profitability by predicting underwriting and claims risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation.

Gradient AI is a leading provider of artificial intelligence solutions for the insurance industry. Its solutions improve loss ratios and profitability by predicting underwriting and claims risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation.

Medcol.io is a clinical AI assistant designed to support healthcare professionals in making informed decisions by providing evidence-based recommendations and insights. The platform leverages advanced algorithms and medical data analysis to assist in diagnosing diseases, suggesting treatment plans, and predicting patient outcomes. With a user-friendly interface and real-time updates, Medcol.io aims to streamline the clinical decision-making process and improve patient care.

moderation.dev is an AI tool that offers domain-specific guardrails to help organizations identify and manage risks efficiently. By leveraging AI technology, the tool provides custom guardrail models in just one click. It specializes in predicting risks associated with AI chatbots and creating models to intercept queries that a traditional chatbot might struggle to answer accurately.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

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.

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.

NoLabs is an open-source biolab that provides easy access to state-of-the-art models for bio research. It supports various tasks, including drug discovery, protein analysis, and small molecule design. NoLabs aims to accelerate bio research by making inference models accessible to everyone.

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.

ADMET-AI is a platform for ADMET prediction using Chemprop-RDKit models trained on ADMET datasets from the Therapeutics Data Commons. It offers command line, Python API, and web server interfaces for making ADMET predictions on new molecules. The platform can be easily installed using pip and supports GPU acceleration. It also provides options for processing TDC data, plotting results, and hosting a web server. ADMET-AI is a machine learning platform for evaluating large-scale chemical libraries.

A public repository collecting links to state-of-the-art training sets, QA, benchmarks and other evaluations for various ML and LLM applications in materials science and chemistry. It includes datasets related to chemistry, materials, multimodal data, and knowledge graphs in the field. The repository aims to provide resources for training and evaluating machine learning models in the materials science and chemistry domains.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

The Ersilia Model Hub is a unified platform of pre-trained AI/ML models dedicated to infectious and neglected disease research. It offers an open-source, low-code solution that provides seamless access to AI/ML models for drug discovery. Models housed in the hub come from two sources: published models from literature (with due third-party acknowledgment) and custom models developed by the Ersilia team or contributors.

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.

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.

Everything appears coincidental, yet is fated: Predicting the Future with the I Ching

一款基于深度神经网络预测给出中国A股股票买入建议的智能投资顾问 An intelligent investment advisor based on deep neural network for predicting buy recommendations for Chinese A-share stocks.

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