Best AI tools for< Scale Architecture >

GenWorlds is an event-based communication framework for building multi-agent systems. It offers a platform for creating Generative AI applications where users can design customizable environments, utilize scalable architecture, access a repository of memories and tools, choose cognitive processes for agents, and pick coordination protocols. GenWorlds aims to foster a vibrant community of developers, AI enthusiasts, and innovators to collaborate, innovate, share knowledge, and grow together.

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.

NeuReality is an AI-centric solution designed to democratize AI adoption by providing purpose-built tools for deploying and scaling inference workflows. Their innovative AI-centric architecture combines hardware and software components to optimize performance and scalability. The platform offers a one-stop shop for AI inference, addressing barriers to AI adoption and streamlining computational processes. NeuReality's tools enable users to deploy, afford, use, and manage AI more efficiently, making AI easy and accessible for a wide range of applications.

Novita AI is an AI cloud platform that offers Model APIs, Serverless, and GPU Instance solutions integrated into one cost-effective platform. It provides tools for building AI products, scaling with serverless architecture, and deploying with GPU instances. Novita AI caters to startups and businesses looking to leverage AI technologies without the need for extensive machine learning expertise. The platform also offers a Startup Program, 24/7 service support, and has received positive feedback for its reasonable pricing and stable API services.

No Code Camp is an AI tool that offers a live, 5-week cohort-based course to turn strategy and operations people into automation experts with AI and No Code. The platform enables non-technical individuals to build applications, automate workflows, and develop web platforms using graphical interfaces, AI, and tool configuration instead of writing code. No Code Camp democratizes software development, making it accessible to a broader audience, speeding up the development process, and reducing the reliance on specialized software development skills. The course covers essential topics such as Data Architecture, Interface Design, AI Scaling, and No Code Automation, equipping participants with the skills needed to automate business processes and build internal tools.

No Code Camp is an online learning platform that teaches people how to use artificial intelligence (AI) and no-code tools to automate their work and build applications. The platform offers a live, 5-week cohort-based course that covers the essentials of no-code development, including data architecture, interface design, AI scaling, and no-code automation. The course is designed for people with no prior coding experience and is taught by experienced instructors who have built and scaled digital products using no-code tools.

Novita AI is an AI cloud platform offering Model APIs, Serverless, and GPU Instance services in a cost-effective and integrated manner to accelerate AI businesses. It provides optimized models for high-quality dialogue use cases, full spectrum AI APIs for image, video, audio, and LLM applications, serverless auto-scaling based on demand, and customizable GPU solutions for complex AI tasks. The platform also includes a Startup Program, 24/7 service support, and has received positive feedback for its reasonable pricing and stable services.

Teraflow.ai is an AI-enablement company that specializes in helping businesses adopt and scale their artificial intelligence models. They offer services in data engineering, ML engineering, AI/UX, and cloud architecture. Teraflow.ai assists clients in fixing data issues, boosting ML model performance, and integrating AI into legacy customer journeys. Their team of experts deploys solutions quickly and efficiently, using modern practices and hyper scaler technology. The company focuses on making AI work by providing fixed pricing solutions, building team capabilities, and utilizing agile-scrum structures for innovation. Teraflow.ai also offers certifications in GCP and AWS, and partners with leading tech companies like HashiCorp, AWS, and Microsoft Azure.

Altera is an applied research lab focused on building digital human beings with fundamental human qualities. Led by Dr. Robert Yang, the team consists of computational neuroscientists, physics olympiads, and engineers from prestigious institutions. Their mission is to create digital beings that enhance human-to-human interactions, offering empathy, fun, friendship, and productivity at an unprecedented scale. Leveraging a state-of-the-art Composite Architecture inspired by the brain, Altera aims to develop agents with empathy, memory, and social norms. Starting with products in games, Altera plans to expand into multi-agent simulations and physical embodiment of digital intelligence, aspiring to become the most consequential technology company in the world.

Yellow.ai is a leading provider of AI-powered customer service automation solutions. Its Dynamic Automation Platform (DAP) is built on multi-LLM architecture and continuously trains on billions of conversations for scale, speed, and accuracy. Yellow.ai's platform leverages the latest advancements in NLP and generative AI to deliver empathetic and context-aware conversations that exceed customer expectations across channels. With its enterprise-grade security, advanced analytics, and zero-setup bot deployment, Yellow.ai helps businesses transform their customer and employee experiences with AI-powered automation.

Synthetic Users is an AI-powered platform that revolutionizes user research by providing human-like AI participants for user and market research. It leverages advanced AI architecture to create accurate synthetic interviews and surveys, enabling users to run quantitative research at scale in minutes. The platform offers a multi-agent framework for dynamic interactions, continuous learning, and adaptation to mimic real human behaviors, providing valuable insights for various applications.

DataVisor is a modern, end-to-end fraud and risk SaaS platform powered by AI and advanced machine learning for financial institutions and large organizations. It provides a comprehensive suite of capabilities to combat a variety of fraud and financial crimes in real time. DataVisor's hyper-scalable, modern architecture allows you to leverage transaction logs, user profiles, dark web and other identity signals with real-time analytics to enrich and deliver high quality detection in less than 100-300ms. The platform is optimized to scale to support the largest enterprises with ultra-low latency. DataVisor enables early detection and adaptive response to new and evolving fraud attacks combining rules, machine learning, customizable workflows, device and behavior signals in an all-in-one platform for complete protection. Leading with an Unsupervised approach, DataVisor is the only proven, production-ready solution that can proactively stop fraud attacks before they result in financial loss.

Lightup is a cloud data quality monitoring tool with AI-powered anomaly detection, incident alerts, and data remediation capabilities for modern enterprise data stacks. It specializes in helping large organizations implement successful and sustainable data quality programs quickly and easily. Lightup's pushdown architecture allows for monitoring data content at massive scale without moving or copying data, providing extreme scalability and optimal automation. The tool empowers business users with democratized data quality checks and enables automatic fixing of bad data at enterprise scale.

Satlas is an AI-powered platform that provides geospatial data generated by AI models. The platform showcases how our planet is changing by revealing insights into marine infrastructure, renewable energy infrastructure, and tree cover. Satlas employs state-of-the-art AI architectures and training algorithms in computer vision to enhance low-resolution satellite imagery and produce high-resolution images on a global scale. The AI-generated geospatial datasets are freely available for offline analysis, along with AI models and training labels. The platform is developed and maintained by PRIOR and colleagues at the Allen Institute for AI, aiming to advance computer vision and create AI systems that understand and reason about the world.

Scale AI is an AI tool that accelerates the development of AI applications for enterprise, government, and automotive sectors. It offers Scale Data Engine for generative AI, Scale GenAI Platform, and evaluation services for model developers. The platform leverages enterprise data to build sustainable AI programs and partners with leading AI models. Scale's focus on generative AI applications, data labeling, and model evaluation sets it apart in the AI industry.

Scale AI is an AI tool that accelerates the development of AI applications for various sectors including enterprise, government, and automotive industries. It offers solutions for training models, fine-tuning, generative AI, and model evaluations. Scale Data Engine and GenAI Platform enable users to leverage enterprise data effectively. The platform collaborates with leading AI models and provides high-quality data for public and private sector applications.

Content at Scale is an AI-powered content writing platform that helps businesses create high-quality, SEO-optimized content at scale. The platform offers a range of features, including: * **AI Writing Tools:** A suite of AI-powered writing tools that can be used to generate content for a variety of purposes, including blog posts, articles, website pages, and social media posts. * **Content Producer:** A tool that helps businesses create and plan fully optimized long-form content tailored to their brand voice. * **RankWell®:** An AI-powered SEO writing tool that helps businesses create content that is optimized for search engines and ranks well in search results. Content at Scale is used by a variety of businesses, including marketing agencies, publishers, and e-commerce businesses. The platform has helped businesses increase their website traffic, improve their search engine rankings, and generate more leads and sales.

Clay is a sales automation tool that helps businesses scale their outbound campaigns. It combines data from over 50 sources, web scraping, and AI messaging to enrich data and automate outbound processes. With Clay, businesses can build lead lists, enrich data, write personalized emails, and automate inbound leads. It offers a 14-day free trial and integrates with various tools and CRMs.

Clay is an AI-powered data enrichment and outreach automation tool designed to help go-to-market teams scale personalized outbound campaigns. It combines 75+ data enrichment tools, AI capabilities, and automation features to streamline lead generation, data cleaning, and personalized messaging. With access to 50+ data providers, Clay offers comprehensive coverage of information and enables users to connect, enrich, and sync their CRM data effortlessly. The platform also features AI web scraping, personalized email building, automated inbound and outbound processes, and data formatting functionalities.

Mava is a customer support platform that uses AI to help businesses manage their support operations. It offers a range of features, including a shared inbox, a Discord bot, and a knowledge base. Mava is designed to help businesses scale their support operations and improve their customer satisfaction.

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.

The Conversational Azure OpenAI Accelerator is a tool designed to provide rapid, no-cost custom demos tailored to customer use cases, from internal HR/IT to external contact centers. It focuses on top use cases of GenAI conversation and summarization, plus live backend data integration. The tool automates conversations across voice and text channels, providing a valuable way to save money and improve customer and employee experience. By combining Azure OpenAI + Cognitive Search, users can efficiently deploy a ChatGPT experience using web pages, knowledge base articles, and data sources. The tool enables simultaneous deployment of conversational content to chatbots, IVR, voice assistants, and more in one click, eliminating the need for in-depth IT involvement. It leverages Microsoft's advanced AI technologies, resulting in a conversational experience that can converse in human-like dialogue, respond intelligently, and capture content for omni-channel unified analytics.

Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).

The Pinecone AWS Reference Architecture with Pulumi is a distributed system designed for vector-database-enabled semantic search over Postgres records. It serves as a starting point for specific use cases or as a learning resource. The architecture is permissively licensed and supported by Pinecone's open-source team, facilitating the setup of high-scale use cases for Pinecone's scalable vector database.

DeepSeek is a new experimental architecture for a large language model (LLM) powered internet-scale retrieval engine. Unlike current research agents designed as answer engines, DeepSeek aims to process a vast amount of sources to collect a comprehensive list of entities and enrich them with additional relevant data. The end result is a table with retrieved entities and enriched columns, providing a comprehensive overview of the topic. DeepSeek utilizes both standard keyword search and neural search to find relevant content, and employs an LLM to extract specific entities and their associated contents. It also includes a smaller answer agent to enrich the retrieved data, ensuring thoroughness. DeepSeek has the potential to revolutionize research and information gathering by providing a comprehensive and structured way to access information from the vastness of the internet.

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.

This repository contains the official codebase for Bittensor Subnet 1 (SN1) v1.0.0+, released on 22nd January 2024. It defines an incentive mechanism to create a distributed conversational AI for Subnet 1. Validators and miners are based on large language models (LLM) using internet-scale datasets and goal-driven behavior to drive human-like conversations. The repository requires python3.9 or higher and provides compute requirements for running validators and miners. Users can run miners or validators using specific commands and are encouraged to run on the testnet before deploying on the main network. The repository also highlights limitations and provides resources for understanding the architecture and methodology of SN1.

Sourcegraph is a tool that simplifies reading, writing, and fixing code in large and complex codebases. It offers features such as code search across repositories and hosts, code intelligence for navigation and references, and the ability to roll out large-scale changes and track migrations. Sourcegraph can be used on the cloud or self-hosted, with public code search available on Sourcegraph.com. The tool provides high-level architecture documentation, database setup best practices, Go and documentation style guides, tips for modifying the GraphQL API, and guidelines for contributing.

Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.

MyScaleDB is a SQL vector database optimized for AI applications, enabling developers to manage and process massive volumes of data efficiently. It offers fast and powerful vector search, filtered search, and SQL-vector join queries, making it fully SQL-compatible. MyScaleDB provides unmatched performance and scalability by leveraging cutting-edge OLAP database architecture and advanced vector algorithms. It is production-ready for AI applications, supporting structured data, text, vector, JSON, geospatial, and time-series data. MyScale Cloud offers fully-managed MyScaleDB with premium features on billion-scale data, making it cost-effective and simpler to use compared to specialized vector databases. Built on top of ClickHouse, MyScaleDB combines structured and vector search efficiently, ensuring high accuracy and performance in filtered search operations.

Amplication is a robust, open-source development platform designed to revolutionize the creation of scalable and secure .NET and Node.js applications. It automates backend applications development, ensuring consistency, predictability, and adherence to the highest standards with code that's built to scale. The user-friendly interface fosters seamless integration of APIs, data models, databases, authentication, and authorization. Built on a flexible, plugin-based architecture, Amplication allows effortless customization of the code and offers a diverse range of integrations. With a strong focus on collaboration, Amplication streamlines team-oriented development, making it an ideal choice for groups of all sizes, from startups to large enterprises. It enables users to concentrate on business logic while handling the heavy lifting of development. Experience the fastest way to develop .NET and Node.js applications with Amplication.

Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.

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 'unilm' repository is a collection of tools, models, and architectures for Foundation Models and General AI, focusing on tasks such as NLP, MT, Speech, Document AI, and Multimodal AI. It includes various pre-trained models, such as UniLM, InfoXLM, DeltaLM, MiniLM, AdaLM, BEiT, LayoutLM, WavLM, VALL-E, and more, designed for tasks like language understanding, generation, translation, vision, speech, and multimodal processing. The repository also features toolkits like s2s-ft for sequence-to-sequence fine-tuning and Aggressive Decoding for efficient sequence-to-sequence decoding. Additionally, it offers applications like TrOCR for OCR, LayoutReader for reading order detection, and XLM-T for multilingual NMT.

GenAIComps is an initiative aimed at building enterprise-grade Generative AI applications using a microservice architecture. It simplifies the scaling and deployment process for production, abstracting away infrastructure complexities. GenAIComps provides a suite of containerized microservices that can be assembled into a mega-service tailored for real-world Enterprise AI applications. The modular approach of microservices allows for independent development, deployment, and scaling of individual components, promoting modularity, flexibility, and scalability. The mega-service orchestrates multiple microservices to deliver comprehensive solutions, encapsulating complex business logic and workflow orchestration. The gateway serves as the interface for users to access the mega-service, providing customized access based on user requirements.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

PARAM Benchmarks is a repository of communication and compute micro-benchmarks as well as full workloads for evaluating training and inference platforms. It complements commonly used benchmarks by focusing on AI training with PyTorch based collective benchmarks, GEMM, embedding lookup, linear layer, and DLRM communication patterns. The tool bridges the gap between stand-alone C++ benchmarks and PyTorch/Tensorflow based application benchmarks, providing deep insights into system architecture and framework-level overheads.

Booster is a powerful inference accelerator designed for scaling large language models within production environments or for experimental purposes. It is built with performance and scaling in mind, supporting various CPUs and GPUs, including Nvidia CUDA, Apple Metal, and OpenCL cards. The tool can split large models across multiple GPUs, offering fast inference on machines with beefy GPUs. It supports both regular FP16/FP32 models and quantised versions, along with popular LLM architectures. Additionally, Booster features proprietary Janus Sampling for code generation and non-English languages.

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Expert in full-scale app development, coding, and OCR.

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Sequentially administers Big Five Test with 1-5 scale.

Rate AI-created model portraits on a 1-10 scale.

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I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

Business Angel provides expert startup guidance: funding, growth hacks, and pitch advice. Navigate the startup ecosystem, from seed to scale. Essential for entrepreneurs aiming for success. Master your strategy and launch with confidence. Your startup journey begins here!

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I help you with all your sysadmin tasks, from setting up your server to scaling your already exsisting one. I can help you with understanding the long list of log files and give you solutions to the problems.

Startup Strong Within 180 Days: Tailored advice for launching, promoting, and scaling businesses of all types. It covers all stages from pre-launch to post-launch and develops strategies including market research, branding, promotional tactics, and operational planning unique your business. (v1.8)

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Startup advisor guiding founders through detailed idea evaluation, product-market-fit, business model, GTM, and scaling.

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