Best AI tools for< building data-intensive applications >

Convex is a fullstack TypeScript development platform that provides a flexible, 100% ACID compliant database. It allows developers to build real-time, reactive applications with ease. Convex also offers a variety of features such as actions, jobs, and webhooks that make it easy to integrate with third-party services. Additionally, Convex provides a variety of resources to help developers get started, including documentation, tutorials, and a community forum.

Hex is a collaborative data workspace that provides a variety of tools for working with data, including queries, notebooks, reports, data apps, and AI. It is designed to be easy to use for people of all technical skill levels, and it integrates with a variety of other tools and services. Hex is a powerful tool for data exploration, analysis, and visualization.

Snaplet is a data management tool for developers that provides AI-generated dummy data for local development, end-to-end testing, and debugging. It uses a real programming language (TypeScript) to define and edit data, ensuring type safety and auto-completion. Snaplet understands database structures and relationships, automatically transforming personally identifiable information and seeding data accordingly. It integrates seamlessly into development workflows, providing data where it's needed most: on local machines, for CI/CD testing, and preview environments.

Streamlit is a web application framework that allows users to create interactive web applications with Python. It simplifies the process of building data-driven apps by providing a simple and intuitive way to create user interfaces. With Streamlit, users can easily turn data scripts into shareable web apps, making it ideal for data scientists, machine learning engineers, and developers. The platform is known for its ease of use, fast prototyping capabilities, and seamless integration with popular data science libraries like Pandas, Matplotlib, and TensorFlow.

Latitude is an open-source framework for building interactive data apps using code. It provides a workspace for data analysts to streamline their workflow, connect to various data sources, perform data transformations, create visualizations, and collaborate with others. Latitude aims to simplify the data analysis process by offering features such as data snapshots, a data profiler, a built-in AI assistant, and tight integration with dbt.

Qubinets is a cloud data environment solutions platform that provides building blocks for building big data, AI, web, and mobile environments. It is an open-source, no lock-in, secured, and private platform that can be used on any cloud, including AWS, Digital Ocean, Google Cloud, and Microsoft Azure. Qubinets makes it easy to plan, build, and run data environments, and it streamlines and saves time and money by reducing the grunt work in setup and provisioning.

ThoughtSpot is an AI-powered analytics platform that enables users to deliver insights 10x faster for their employees. It offers AI-powered search capabilities, natural language search, live querying of data, building search data models, balancing self-service with enterprise-scale control, visualizing business data, operationalizing data sync to business apps, and mobile access. The platform also provides features for creating visualizations from spreadsheets, staying up to date with product news, embedding analytics into apps, building ThoughtSpot apps and API services, and generating more revenue with embedded analytics. ThoughtSpot is designed to provide fast, actionable insights with a focus on user experience and self-service analytics.

Evervault provides developers with world-class infrastructure to solve complex data security and compliance problems in days, not months. It offers four simple primitives: Relay, Functions, UI Components, and Enclaves. These primitives can be used to build a variety of data security and compliance solutions, such as PCI DSS compliance, HIPAA compliance, and GDPR compliance. Evervault is secure by default, fundamentally configurable, and ultra-low latency. It is also compliant with PCI DSS, HIPAA, GDPR, and SOC2.

OSS Insight is a website that provides deep insight into developers and repositories on GitHub, offering information about stars, pull requests, issues, pushes, comments, and reviews. The platform ranks repositories based on various scores and provides insights about trending repositories in different programming languages and technical fields. Users can explore curated repository lists, hot collections, and game engines, among other features. Additionally, OSS Insight offers tutorials and workshops on analyzing GitHub events using TiDB Cloud.

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.

Granica AI is a Training Data Platform that focuses on making data safe for use with AI while keeping it cost-efficient. It offers state-of-the-art accuracy, cost-efficient data optimization, and data visibility solutions. The platform helps AI teams achieve big results while minimizing privacy risks by protecting data privacy, optimizing data costs, and gaining data visibility. Granica AI is trusted by category-defining companies for its unique offerings in the market.

Omdena is an AI platform that focuses on building AI solutions for real-world problems through global collaboration. They offer services ranging from local AI development to enterprise-level products, fostering talent development, and enabling AI professionals to make a positive impact. Omdena runs AI innovation challenges, deployment & product engineering, enterprise AI solutions, and grassroots AI initiatives. The platform empowers learners with quality education in machine learning and artificial intelligence, removing financial and geographic barriers. Omdena has successfully developed over 650 solutions, worked with 250+ organizations, and is trusted by impact-driven organizations worldwide.

SuperAnnotate is an AI data platform that simplifies and accelerates model-building by unifying the AI pipeline. It enables users to create, curate, and evaluate datasets efficiently, leading to the development of better models faster. The platform offers features like connecting any data source, building customizable UIs, creating high-quality datasets, evaluating models, and deploying models seamlessly. SuperAnnotate ensures global security and privacy measures for data protection.

Objective is an AI-native search platform designed for developers to build modern search experiences for web and mobile applications. It offers a multimodal search API that understands human language, images, and text relationships. The platform integrates various search techniques to provide natural and relevant search results, even with inconsistent data. Objective is trusted by great companies and accelerates data science roadmaps through its efficient search capabilities.

STELLARWITS is an AI solutions and software platform that empowers users to explore cutting-edge technology and innovation. The platform offers AI models with versatile capabilities, ranging from content generation to data analysis to problem-solving. Users can engage directly with the technology, experiencing its power in real-time. With a focus on transforming ideas into technology, STELLARWITS provides tailored solutions in software and AI development, delivering intelligent systems and machine learning models for innovative and efficient solutions. The platform also features a download hub with a curated selection of solutions to enhance the digital experience. Through blogs and company information, users can delve deeper into the narrative of STELLARWITS, exploring its mission, vision, and commitment to reshaping the tech landscape.

Stride is an AI-driven software application that offers two main tools - Scanner and List Builder. The Scanner tool allows users to collect unlimited emails from new followers in real-time, while the List Builder retrieves emails of current followers. The application uses advanced AI software to ensure high-quality and fresh email lists at an affordable price. Users can leverage the email lists for various purposes like boosting ecommerce sales, newsletter campaigns, event planning, affiliate marketing, and more. Stride also provides dedicated support and valuable resources through its blog for effective email marketing strategies.

Cartesia Sonic Team Blog Research Playground is an AI application that offers real-time multimodal intelligence for every device. The application aims to build the next generation of AI by providing ubiquitous, interactive intelligence that can run on any device. It features the fastest, ultra-realistic generative voice API and is backed by research on simple linear attention language models and state-space models. The founding team, who met at the Stanford AI Lab, has invented State Space Models (SSMs) and scaled it up to achieve state-of-the-art results in various modalities such as text, audio, video, images, and time-series data.

Hugging Face is an AI community platform that facilitates collaboration on models, datasets, and applications within the machine learning community. It offers a wide range of tools and resources for developers and researchers to create, discover, and share machine learning projects. The platform aims to accelerate the development of AI technologies and foster innovation in the field of artificial intelligence.

PwC is a global network of professional services firms that provides assurance, tax, and consulting services to businesses and individuals. The company has a strong focus on artificial intelligence (AI) and its potential to transform the way businesses operate. PwC's AI-powered solutions help clients improve efficiency, reduce costs, and make better decisions.

LlamaIndex is a framework for building context-augmented Large Language Model (LLM) applications. It provides tools to ingest and process data, implement complex query workflows, and build applications like question-answering chatbots, document understanding systems, and autonomous agents. LlamaIndex enables context augmentation by combining LLMs with private or domain-specific data, offering tools for data connectors, data indexes, engines for natural language access, chat engines, agents, and observability/evaluation integrations. It caters to users of all levels, from beginners to advanced developers, and is available in Python and Typescript.

agentUniverse is a framework for developing applications powered by multi-agent based on large language model. It provides essential components for building single agent and multi-agent collaboration mechanism for customizing collaboration patterns. Developers can easily construct multi-agent applications and share pattern practices from different fields. The framework includes pre-installed collaboration patterns like PEER and DOE for complex task breakdown and data-intensive tasks.

Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

The LLM RAG Workshop repository provides a workshop on using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate and understand text in a human-like manner. It includes instructions on setting up the environment, indexing Zoomcamp FAQ documents, creating a Q&A system, and using OpenAI for generation based on retrieved information. The repository focuses on enhancing language model responses with retrieved information from external sources, such as document databases or search engines, to improve factual accuracy and relevance of generated text.

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This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

Resonance is a framework designed to facilitate interoperability and messaging between services in your infrastructure and beyond. It provides AI capabilities and takes full advantage of asynchronous PHP, built on top of Swoole. With Resonance, you can: * Chat with Open-Source LLMs: Create prompt controllers to directly answer user's prompts. LLM takes care of determining user's intention, so you can focus on taking appropriate action. * Asynchronous Where it Matters: Respond asynchronously to incoming RPC or WebSocket messages (or both combined) with little overhead. You can set up all the asynchronous features using attributes. No elaborate configuration is needed. * Simple Things Remain Simple: Writing HTTP controllers is similar to how it's done in the synchronous code. Controllers have new exciting features that take advantage of the asynchronous environment. * Consistency is Key: You can keep the same approach to writing software no matter the size of your project. There are no growing central configuration files or service dependencies registries. Every relation between code modules is local to those modules. * Promises in PHP: Resonance provides a partial implementation of Promise/A+ spec to handle various asynchronous tasks. * GraphQL Out of the Box: You can build elaborate GraphQL schemas by using just the PHP attributes. Resonance takes care of reusing SQL queries and optimizing the resources' usage. All fields can be resolved asynchronously.

LLM4IR-Survey is a collection of papers related to large language models for information retrieval, organized according to the survey paper 'Large Language Models for Information Retrieval: A Survey'. It covers various aspects such as query rewriting, retrievers, rerankers, readers, search agents, and more, providing insights into the integration of large language models with information retrieval systems.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

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

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