Best AI tools for< Ai Accelerator Design Engineer >

Move 37 is an AI product studio that has been designing, building, and shipping AI products since 2017. They specialize in designing, developing, and managing AI products, tools, and workflows to help users unlock new levels of insight, productivity, and efficiency. By reimagining how work gets done collaboratively, they aim to bring teams, executives, and organizations together to realize better work futures and products. Move 37 offers services such as generative reporting, research and insights, product development, customer service, and content generation.

SyBridge Technologies is an AI-powered platform that bridges the gap between innovation and mass production. It offers a wide range of capabilities including design & engineering, rapid prototyping, tooling, advanced manufacturing, and supportive injection molding. The platform provides on-demand manufacturing solutions across the product lifecycle, combining cutting-edge digital technologies with expertise in tooling, engineering, and design to accelerate success. SyBridge Technologies caters to industries such as life sciences, health & beauty, consumer products, aerospace, and mobility & industrial.

Global Nodes is a global leader in innovative solutions, specializing in Artificial Intelligence, Data Engineering, Cloud Services, Software Development, and Mobile App Development. They integrate advanced AI to accelerate product development and provide custom, secure, and scalable solutions. With a focus on cutting-edge technology and visionary thinking, Global Nodes offers services ranging from ideation and design to precision execution, transforming concepts into market-ready products. Their team has extensive experience in delivering top-notch AI, cloud, and data engineering services, making them a trusted partner for businesses worldwide.

Strong Analytics is a data science consulting and machine learning engineering company that specializes in building bespoke data science, machine learning, and artificial intelligence solutions for various industries. They offer end-to-end services to design, engineer, and deploy custom AI products and solutions, leveraging a team of full-stack data scientists and engineers with cross-industry experience. Strong Analytics is known for its expertise in accelerating innovation, deploying state-of-the-art techniques, and empowering enterprises to unlock the transformative value of AI.

Builder.io is an AI-powered visual development platform that accelerates digital teams by providing design-to-code solutions. With Visual Copilot, users can transform Figma designs into production-ready code quickly and efficiently. The platform offers features like AI-powered design-to-code conversion, visual editing, and enterprise CMS integration. Builder.io enables users to streamline their development process and bring ideas to production in seconds.

Hermae Solutions offers an AI Assistant for Enterprise Design Systems, providing onboarding acceleration, contractor efficiency, design system adoption support, knowledge distribution, and various AI documentation and Storybook assistants. The platform enables users to train custom AI assistants, embed them into documentation sites, and communicate instantly with the knowledge base. Hermae's process simplifies efficiency improvements by gathering information sources, processing data for AI supplementation, customizing integration, and supporting integration success. The AI assistant helps reduce engineering costs and increase development efficiency across the board.

NVIDIA is a world leader in artificial intelligence computing, providing hardware and software solutions for gaming, entertainment, data centers, edge computing, and more. Their platforms like Jetson and Isaac enable the development and deployment of AI-powered autonomous machines. NVIDIA's AI applications span various industries, from healthcare to manufacturing, and their technology is transforming the world's largest industries and impacting society profoundly.

CodeSpell is an AI-powered code completion tool designed to streamline the software development life cycle (SDLC). It assists developers in generating code, documenting it, fixing errors, building APIs, automating tests, and setting up infrastructure directly within their integrated development environment (IDE). CodeSpell's unique feature, Design Studio, automates project setup by generating scaffolding, APIs, and infrastructure scripts tailored to the user's stack, reducing manual coding effort and accelerating development. The tool is compatible with popular IDEs and supports code generation in any language. CodeSpell aims to transition the software industry from AI-assisted code generation to an AI-driven landscape.

Goptimise is a no-code AI-powered scalable backend builder that helps developers craft scalable, seamless, powerful, and intuitive backend solutions. It offers a solid foundation with robust and scalable infrastructure, including dedicated infrastructure, security, and scalability. Goptimise simplifies software rollouts with one-click deployment, automating the process and amplifying productivity. It also provides smart API suggestions, leveraging AI algorithms to offer intelligent recommendations for API design and accelerating development with automated recommendations tailored to each project. Goptimise's intuitive visual interface and effortless integration make it easy to use, and its customizable workspaces allow for dynamic data management and a personalized development experience.

Serenity Star is a Generative AI deployment service that offers Models As A Service to help businesses increase productivity and design tailored solutions. The platform provides access to over 100 LLMs, an ecosystem with agents, co-pilots, and plugins, and features low code and no code solutions for quick market release. Serenity Star aims to simplify the implementation of Generative AI in enterprises by offering tools, support, and resources for process optimization, innovation, revenue maximization, and informed decision-making.

HatchWorks is an AI development partner that specializes in building AI-native solutions and using AI to enhance software development processes. The company offers services such as Gen AI Product Development, Data & AI/ML Software Development, Product Strategy, and UX & UI Design. HatchWorks leverages cutting-edge technologies like Generative AI, Machine Learning, and AI-Powered Software Development to deliver custom software solutions efficiently. The company's proprietary Generative-Driven Development™ methodology enables faster software development, increased productivity, and cost-effectiveness. HatchWorks is trusted by leading brands for delivering exceptional AI-driven outcomes and impactful solutions.

Maven is an AI-powered platform offering live, online courses for professionals in various fields such as product design, engineering, marketing, business, leadership, and investing. The platform provides interactive cohorts with high student engagement, hands-on projects, and up-to-date case studies to help professionals acquire practical skills for immediate application in their jobs. Maven's curated frameworks and expert feedback aim to accelerate career growth by condensing years of operating experience into weeks. With a focus on AI-related courses, Maven offers certifications and training programs to help individuals confidently build AI products and lead AI organizations.

Rhino.ai is a SaaS application company that offers an all-in-one AI platform for transforming legacy systems or building new applications. The platform helps organizations execute large transformations, accelerate legacy migrations, re-engineer applications, and develop applications faster with AI-driven modeling and automation. Rhino.ai empowers businesses to modernize their systems, reduce technical debt, avoid vendor lock-in, and gain leverage in product licensing negotiations. The platform provides a unified solution for discovery, design, coding, and deployment, enabling faster decision-making and streamlined modernization processes.

Neural Concept is an end-to-end platform for high-performance engineering teams, powered by a leading proprietary 3D AI core. It accelerates product development and innovation with industry-leading 3D deep-learning and simulation capabilities. The platform works with various CAE and CAD softwares, offering 3D visual feedback, collaborative environment, and LLM guidance to boost engineers' impact. Neural Concept is used by engineering companies to design and deliver better products faster, bringing AI-designed products to market up to 75% faster.

Appian Platform is an AI-powered tool for process automation that offers low-code design, process mining, and data fabric capabilities. It enables businesses to design, automate, and optimize their processes efficiently. With features like Robotic Process Automation (RPA), Intelligent Document Processing (IDP), and API integrations, Appian provides end-to-end process automation solutions. The platform also includes Total Experience features for creating exceptional user experiences through mobile apps and web portals. Appian offers solutions for various industries, including financial services, insurance, government, and life sciences, to accelerate business processes and improve efficiency.

Altair is a global leader in computational intelligence, offering software and cloud solutions in simulation, HPC, data analytics, and AI. The platform provides advanced technology for accelerating AI adoption, powering engineering processes, and enabling sustainability solutions across various industries. Altair's products and platforms cater to diverse sectors such as aerospace, automotive, healthcare, and more, with a focus on digital twin technology, generative AI, and cloud computing. The company also hosts events, webinars, and training programs to support users in leveraging their tools effectively.

BenevolentAI is a leader in applying advanced AI to accelerate biopharma drug discovery blending science and technology with a focus on finding solutions for complex diseases. We empower both biopharmaceutical companies and our internal scientists to harness the full potential of data and AI to accelerate the next generation of scientific advances. We have built our AI-enabled drug discovery engine to drive a revolution in drug discovery. The Benevolent Platform™ unlocks the power of a vast biomedical data landscape to provide a multidimensional representation of human biology across all diseases. We believe this approach will improve the probability of clinical success, and help us deliver life-changing treatments to patients – because it matters.

Fermat is an AI toolmaker that allows users to build their own AI workflows and accelerate their creative process. It is trusted by professionals in fashion design, product design, interior design, and brainstorming. Fermat's unique features include the ability to blend AI models into tools that fit the way users work, embed processes in reusable tools, keep teams on the same page, and embed users' own style to get coherent results. With Fermat, users can visualize their sketches, change colors and materials, create photo shoots, turn images into vectors, and more. Fermat offers a free Starter plan for individuals and a Pro plan for teams and professionals.

Innovation Acceleration is an AI-powered platform that empowers organizations to unlock their creative potential through the integration of advanced AI technologies and structured innovation frameworks. The platform offers a systematic and repeatable approach to creative thinking using Systematic Inventive Thinking (SIT) and Natural Language Processing (NLP) tools such as Large Language Models (LLMs) and generative AI (GenAI). Innovation Acceleration aims to accelerate the innovation process by guiding users through creating customized, industry-leading products, processes, strategies, and marketing innovations.

Recaily.ai is an AI-powered tool that helps you get the most out of your videos. With Recaily.ai, you can automatically generate summaries, transcripts, and chapters for your videos, making it easy to find the information you need quickly and easily. Recaily.ai also integrates with a variety of other tools, making it easy to share your videos and collaborate with others.

LLM4EDA is a repository dedicated to showcasing the emerging progress in utilizing Large Language Models for Electronic Design Automation. The repository includes resources, papers, and tools that leverage LLMs to solve problems in EDA. It covers a wide range of applications such as knowledge acquisition, code generation, code analysis, verification, and large circuit models. The goal is to provide a comprehensive understanding of how LLMs can revolutionize the EDA industry by offering innovative solutions and new interaction paradigms.

ztachip is a RISCV accelerator designed for vision and AI edge applications, offering up to 20-50x acceleration compared to non-accelerated RISCV implementations. It features an innovative tensor processor hardware to accelerate various vision tasks and TensorFlow AI models. ztachip introduces a new tensor programming paradigm for massive processing/data parallelism. The repository includes technical documentation, code structure, build procedures, and reference design examples for running vision/AI applications on FPGA devices. Users can build ztachip as a standalone executable or a micropython port, and run various AI/vision applications like image classification, object detection, edge detection, motion detection, and multi-tasking on supported hardware.

LLM4EC is an interdisciplinary research repository focusing on the intersection of Large Language Models (LLM) and Evolutionary Computation (EC). It provides a comprehensive collection of papers and resources exploring various applications, enhancements, and synergies between LLM and EC. The repository covers topics such as LLM-assisted optimization, EA-based LLM architecture search, and applications in code generation, software engineering, neural architecture search, and other generative tasks. The goal is to facilitate research and development in leveraging LLM and EC for innovative solutions in diverse domains.

Intel® Neural Compressor is an open-source Python library that supports popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet. It provides key features, typical examples, and open collaborations, including support for a wide range of Intel hardware, validation of popular LLMs, and collaboration with cloud marketplaces, software platforms, and open AI ecosystems.

This repository contains the source code for a GEMM & deep learning hardware accelerator system used to validate proposed systolic array hardware architectures implementing efficient matrix multiplication algorithms to increase performance-per-area limits of GEMM & AI accelerators. Achieved results include up to 3× faster CNN inference, >2× higher mults/multiplier/clock cycle, and low area with high clock frequency. The system is specialized for inference of non-sparse DNN models with fixed-point/quantized inputs, fully accelerating all DNN layers in hardware, and highly optimizing GEMM acceleration.

Efficient Foundation Model Survey is a comprehensive analysis of resource-efficient large language models (LLMs) and multimodal foundation models. The survey covers algorithmic and systemic innovations to support the growth of large models in a scalable and environmentally sustainable way. It explores cutting-edge model architectures, training/serving algorithms, and practical system designs. The goal is to provide insights on tackling resource challenges posed by large foundation models and inspire future breakthroughs in the field.

The 'awesome-ai4db-paper' repository is a curated paper list focusing on AI for database (AI4DB) theory, frameworks, resources, and tools for data engineers. It includes a collection of research papers related to learning-based query optimization, training data set preparation, cardinality estimation, query-driven approaches, data-driven techniques, hybrid methods, pretraining models, plan hints, cost models, SQL embedding, join order optimization, query rewriting, end-to-end systems, text-to-SQL conversion, traditional database technologies, storage solutions, learning-based index design, and a learning-based configuration advisor. The repository aims to provide a comprehensive resource for individuals interested in AI applications in the field of database management.

This repository serves as a hub for Microsoft Official Build & Modernize AI Applications reference solutions and content. It provides access to projects demonstrating how to build Generative AI applications using Azure services like Azure OpenAI, Azure Container Apps, Azure Kubernetes, and Azure Cosmos DB. The solutions include Vector Search & AI Assistant, Real-Time Payment and Transaction Processing, and Medical Claims Processing. Additionally, there are workshops like the Intelligent App Workshop for Microsoft Copilot Stack, focusing on infusing intelligence into traditional software systems using foundation models and design thinking.

GLaDOS Personality Core is a project dedicated to building a real-life version of GLaDOS, an aware, interactive, and embodied AI system. The project aims to train GLaDOS voice generator, create a 'Personality Core,' develop medium- and long-term memory, provide vision capabilities, design 3D-printable parts, and build an animatronics system. The software architecture focuses on low-latency voice interactions and minimal dependencies. The hardware system includes servo- and stepper-motors, 3D printable parts for GLaDOS's body, animations for expression, and a vision system for tracking and interaction. Installation instructions involve setting up a local LLM server, installing drivers, and running GLaDOS on different operating systems.

The AI-Gateway repository explores the AI Gateway pattern through a series of experimental labs, focusing on Azure API Management for handling AI services APIs. The labs provide step-by-step instructions using Jupyter notebooks with Python scripts, Bicep files, and APIM policies. The goal is to accelerate experimentation of advanced use cases and pave the way for further innovation in the rapidly evolving field of AI. The repository also includes a Mock Server to mimic the behavior of the OpenAI API for testing and development purposes.

Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It implements dataset abstraction, scalable cache runtime, automated data operations, elasticity and scheduling, and is runtime platform agnostic. Key concepts include Dataset and Runtime. Prerequisites include Kubernetes version > 1.16, Golang 1.18+, and Helm 3. The tool offers features like accelerating remote file accessing, machine learning, accelerating PVC, preloading dataset, and on-the-fly dataset cache scaling. Contributions are welcomed, and the project is under the Apache 2.0 license with a vendor-neutral approach.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

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.

A curated list of high-quality papers on resource-efficient Large Language Models (LLMs) with a focus on various aspects such as architecture design, pre-training, fine-tuning, inference, system design, and evaluation metrics. The repository covers topics like efficient transformer architectures, non-transformer architectures, memory efficiency, data efficiency, model compression, dynamic acceleration, deployment optimization, support infrastructure, and other related systems. It also provides detailed information on computation metrics, memory metrics, energy metrics, financial cost metrics, network communication metrics, and other metrics relevant to resource-efficient LLMs. The repository includes benchmarks for evaluating the efficiency of NLP models and references for further reading.

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.

Awesome LLM Resources is a curated collection of resources for Large Language Models (LLMs) covering various aspects such as serverless hosting, accessing off-the-shelf models via API, local inference, LLM serving frameworks, open-source LLM web chat UIs, renting GPUs for fine-tuning, fine-tuning with no-code UI, fine-tuning frameworks, OS agentic/AI workflow, AI agents, co-pilots, voice API, open-source TTS models, OS RAG frameworks, research papers on chain-of-thought prompting, CoT implementations, CoT fine-tuned models & datasets, and more.

This project aims to create a real-life version of GLaDOS, an aware, interactive, and embodied AI entity. It involves training a voice generator, developing a 'Personality Core,' implementing a memory system, providing vision capabilities, creating 3D-printable parts, and designing an animatronics system. The software architecture focuses on low-latency voice interactions, utilizing a circular buffer for data recording, text streaming for quick transcription, and a text-to-speech system. The project also emphasizes minimal dependencies for running on constrained hardware. The hardware system includes servo- and stepper-motors, 3D-printable parts for GLaDOS's body, animations for expression, and a vision system for tracking and interaction. Installation instructions cover setting up the TTS engine, required Python packages, compiling llama.cpp, installing an inference backend, and voice recognition setup. GLaDOS can be run using 'python glados.py' and tested using 'demo.ipynb'.

HugeSCM is a cloud-based version control system designed to address R&D repository size issues. It effectively manages large repositories and individual large files by separating data storage and utilizing advanced algorithms and data structures. It aims for optimal performance in handling version control operations of large-scale repositories, making it suitable for single large library R&D, AI model development, and game or driver development.

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