Best AI tools for< Hardware Engineers >

Bench is an AI tool designed to automate hardware documentation for Hardware Engineers. It helps users document less and create more by utilizing AI for documentation writing, management, and discoverability. The tool offers features such as adapting to specific use cases, AI documentation writing, single source of truth, data-rich asset pages, highlighting compliance gaps, automated reports, and physical asset logging. Bench is advantageous for increasing productivity, improving documentation accuracy, streamlining workflows, enhancing compliance, and enabling seamless integrations. However, it may have limitations in customization options, initial learning curve, and potential dependency on AI accuracy. The tool is suitable for Hardware Engineers, Technical Writers, Documentation Specialists, Compliance Officers, and Quality Assurance Engineers. Users can find Bench using keywords like AI documentation, hardware documentation automation, AI writing tool, documentation management tool, and asset logging AI. Tasks users can perform with Bench include automate documentation, manage assets, write AI documentation, generate reports, and log physical assets.

Edge Impulse is a leading edge AI platform that enables users to build datasets, train models, and optimize libraries to run directly on any edge device. It offers sensor datasets, feature engineering, model optimization, algorithms, and NVIDIA integrations. The platform is designed for product leaders, AI practitioners, embedded engineers, and OEMs across various industries and applications. Edge Impulse helps users unlock sensor data value, build high-quality sensor datasets, advance algorithm development, optimize edge AI models, and achieve measurable results. It allows for future-proofing workflows by generating models and algorithms that perform efficiently on any edge hardware.

Quilter is an end-to-end PCB design platform that uses generative AI to automate the layout process. It can place components, route traces, define board stackups, and generate pours. Quilter is compatible with existing design tools and libraries, and it returns completed designs in the same file format they were submitted in. Quilter is currently in open beta and is free to use.

Cambricon is an AI technology company that specializes in developing intelligent acceleration cards and systems. They offer a range of products including cloud AI acceleration cards, edge AI chips, and intelligent processing units. Cambricon's advanced chiplet technology and MLUarch03 architecture provide high-performance AI solutions for training and inference tasks. The company is dedicated to advancing the AI industry through innovative hardware and software platforms.

Luxonis is a platform that offers robotic vision solutions through high-resolution cameras with depth vision and on-chip machine learning capabilities. Their products include OAK Cameras and Modules, providing features like Stereo Depth Sensing, Computer Vision, Artificial Intelligence, and Cloud Management. Luxonis enables the development of computer vision products and companies by offering performant and affordable hardware solutions. The platform caters to enterprises and hobbyists, empowering them to easily build embedded vision systems.

PC Builder AI is an artificial intelligence tool developed by AE Studio to assist users in building a customized PC based on their budget and preferences. The tool allows users to input their desired budget and PC specifications, and it provides real-time price updates to help users get the best value for their money. With a user-friendly interface, PC Builder AI simplifies the process of selecting components and building a PC tailored to individual needs. Whether you are a tech enthusiast or a novice, PC Builder AI can help you create a high-performance PC without the hassle of researching and comparing components.

The Code Generator for Arduino is an AI-powered tool that assists users in generating code for Arduino projects. It helps users by providing generated code based on the details of their project, such as the type of Arduino board, sensors, motors, and other components they want to use. The tool simplifies the coding process by breaking down complex prompts into smaller, more manageable pieces. Users can test and refine the generated code to ensure it meets their expectations. The tool utilizes GPT-3.5-turbo, OpenAI's large-scale language-generation model, to create the code. It is important to review the generated code before uploading it to any hardware devices. CJS Robotics, the creator of the tool, is not affiliated with Arduino but offers this service to assist Arduino enthusiasts in their projects.

PLEASEDONTCODE is an AI Code Generator specifically designed for Arduino and ESP32 embedded systems. It simplifies the coding process for users, helping them overcome common obstacles in programming such as compilation errors, syntax confusion, and logic issues. By automating code generation, the tool ensures error-free, syntactically correct, and logically sound code with clear comments for easy understanding. It aims to streamline project execution, increase productivity, and accelerate the development of prototype projects.

Wallaroo.AI is an AI inference platform that offers production-grade AI inference microservices optimized on OpenVINO for cloud and Edge AI application deployments on CPUs and GPUs. It provides hassle-free AI inferencing for any model, any hardware, anywhere, with ultrafast turnkey inference microservices. The platform enables users to deploy, manage, observe, and scale AI models effortlessly, reducing deployment costs and time-to-value significantly.

Duckietown is a platform for delivering cutting-edge robotics and AI learning experiences. It offers teaching resources to instructors, hands-on activities to learners, an accessible research platform to researchers, and a state-of-the-art ecosystem for professional training. Duckietown's mission is to make robotics and AI education state-of-the-art, hands-on, and accessible to all.

Groq is a fast AI inference tool that offers GroqCloud™ Platform and GroqRack™ Cluster for developers to build and deploy AI models with ultra-low-latency inference. It provides instant intelligence for openly-available models like Llama 3.1 and is known for its speed and compatibility with other AI providers. Groq powers leading openly-available AI models and has gained recognition in the AI chip industry. The tool has received significant funding and valuation, positioning itself as a strong challenger to established players like Nvidia.

SoundHound is a leading innovator of conversational intelligence and voice AI technologies. Our independent voice AI platform is built for more natural conversation, enabling businesses to create customized and scalable voice AI solutions for their specific industries and use cases. With SoundHound, you can build voice assistants, enhance smart devices, improve customer experiences, and drive business value.

Luminar is a leading developer of automotive lidar technology. The company's mission is to make roads safer by eliminating vehicle accidents. Luminar's lidar sensors provide cars with a detailed view of their surroundings, enabling them to make better decisions and avoid collisions. Luminar's technology is being used by a number of automakers, including Volvo, SAIC Motor, and Polestar.

OpenCV is the world's largest computer vision library. It's open source, contains over 2500 algorithms and is operated by the non-profit Open Source Vision Foundation.

Embedl is an AI tool that specializes in developing advanced solutions for efficient AI deployment in embedded systems. With a focus on deep learning optimization, Embedl offers a cost-effective solution that reduces energy consumption and accelerates product development cycles. The platform caters to industries such as automotive, aerospace, and IoT, providing cutting-edge AI products that drive innovation and competitive advantage.

VisionLabs is a leading provider of facial recognition technology that enhances digital identity experiences. Their Artificial Intelligence and Machine Learning technology, based on neural network algorithms, ensures a safer and more secure world, enabling seamless navigation in the digital realm. With applications in over 60 countries across various industries, VisionLabs aims to facilitate better and safer interactions through facial recognition technology.

Google Quantum AI is a leading platform dedicated to advancing the field of quantum computing. The platform offers educational resources, research publications, open-source tools like Cirq, and career opportunities. Google Quantum AI's mission is to build best-in-class quantum computing systems with error correction capabilities, enabling the solution of complex problems that are currently intractable for classical computers. The platform also hosts the XPRIZE Quantum Applications competition, collaborates with industry and academic partners to explore future applications of quantum computing, and shares research and blog posts on quantum algorithms and advancements.

Windows Central is a website that provides news, reviews, and help on Windows 10, Windows 11, Xbox, and more. It covers a wide range of topics, including hardware, software, gaming, and accessories. The website also has a forum where users can ask questions and discuss topics related to Windows and Xbox.

ONNX is an open standard for machine learning interoperability, providing a common format to represent machine learning models. It defines a set of operators and a file format for AI developers to use models across various frameworks, tools, runtimes, and compilers. ONNX promotes interoperability, hardware access, and community engagement.

Lobe is a machine learning application that provides an easy-to-use tool for training machine learning models and deploying them to any platform. It offers various features such as creating image-based datasets, working with Python toolsets, and bootstrapping machine learning models for iOS, Android, and web platforms. Lobe aims to simplify the process of developing machine learning models for individuals and organizations.

Awesome Mobile LLMs is a curated list of Large Language Models (LLMs) and related studies focused on mobile and embedded hardware. The repository includes information on various LLM models, deployment frameworks, benchmarking efforts, applications, multimodal LLMs, surveys on efficient LLMs, training LLMs on device, mobile-related use-cases, industry announcements, and related repositories. It aims to be a valuable resource for researchers, engineers, and practitioners interested in mobile LLMs.

This repository provides a comprehensive collection of methodologies, tools, and step-by-step instructions for successful training of large language models (LLMs) and multi-modal models. It is a technical resource suitable for LLM/VLM training engineers and operators, containing numerous scripts and copy-n-paste commands to facilitate quick problem-solving. The repository is an ongoing compilation of the author's experiences training BLOOM-176B and IDEFICS-80B models, and currently focuses on the development and training of Retrieval Augmented Generation (RAG) models at Contextual.AI. The content is organized into six parts: Insights, Hardware, Orchestration, Training, Development, and Miscellaneous. It includes key comparison tables for high-end accelerators and networks, as well as shortcuts to frequently needed tools and guides. The repository is open to contributions and discussions, and is licensed under Attribution-ShareAlike 4.0 International.

MaixPy is a Python SDK that enables users to easily create AI vision projects on edge devices. It provides a user-friendly API for accessing NPU, making it suitable for AI Algorithm Engineers, STEM teachers, Makers, Engineers, Students, Enterprises, and Contestants. The tool supports Python programming, MaixVision Workstation, AI vision, video streaming, voice recognition, and peripheral usage. It also offers an online AI training platform called MaixHub. MaixPy is designed for new hardware platforms like MaixCAM, offering improved performance and features compared to older versions. The ecosystem includes hardware, software, tools, documentation, and a cloud platform.

The NVIDIA AI Blueprint for Vulnerability Analysis for Container Security showcases accelerated analysis on common vulnerabilities and exposures (CVE) at an enterprise scale, reducing mitigation time from days to seconds. It enables security analysts to determine software package vulnerabilities using large language models (LLMs) and retrieval-augmented generation (RAG). The blueprint is designed for security analysts, IT engineers, and AI practitioners in cybersecurity. It requires NVAIE developer license and API keys for vulnerability databases, search engines, and LLM model services. Hardware requirements include L40 GPU for pipeline operation and optional LLM NIM and Embedding NIM. The workflow involves LLM pipeline for CVE impact analysis, utilizing LLM planner, agent, and summarization nodes. The blueprint uses NVIDIA NIM microservices and Morpheus Cybersecurity AI SDK for vulnerability analysis.

The 'jobs' repository by comma.ai focuses on solving self-driving cars by building a robotics stack that includes state-of-the-art machine learning models, operating system design, hardware development, and manufacturing. The company aims to deliver constant incremental progress in self-driving technology to users, with a focus on practical solutions rather than hype. Job opportunities at comma.ai include technical challenges, phone screenings, and paid micro-internships, with perks such as chef-prepared meals, on-site gym access, and health insurance. The teams at comma.ai are organized into web, systems, infrastructure, product, design, and electrical engineering, with specific challenges for each team. The repository also offers opportunities for non-job seekers to participate in challenges and win prizes.

MARS5 is a novel English speech model (TTS) developed by CAMB.AI, featuring a two-stage AR-NAR pipeline with a unique NAR component. The model can generate speech for various scenarios like sports commentary and anime with just 5 seconds of audio and a text snippet. It allows steering prosody using punctuation and capitalization in the transcript. Speaker identity is specified using an audio reference file, enabling 'deep clone' for improved quality. The model can be used via torch.hub or HuggingFace, supporting both shallow and deep cloning for inference. Checkpoints are provided for AR and NAR models, with hardware requirements of 750M+450M params on GPU. Contributions to improve model stability, performance, and reference audio selection are welcome.

This open-source course teaches how to build an advanced RAG and LLM system using LLMOps and ML systems best practices. It helps you create an AI assistant that leverages your personal knowledge base to answer questions, summarize documents, and provide insights. The course covers topics such as LLM system architecture, pipeline orchestration, large-scale web crawling, model fine-tuning, and advanced RAG features. It is suitable for ML/AI engineers and data/software engineers & data scientists looking to level up to production AI systems. The course is free, with minimal costs for tools like OpenAI's API and Hugging Face's Dedicated Endpoints. Participants will build two separate Python applications for offline ML pipelines and online inference pipeline.

Awesome-LLMOps is a curated list of the best LLMOps tools, providing a comprehensive collection of frameworks and tools for building, deploying, and managing large language models (LLMs) and AI agents. The repository includes a wide range of tools for tasks such as building multimodal AI agents, fine-tuning models, orchestrating applications, evaluating models, and serving models for inference. It covers various aspects of the machine learning operations (MLOps) lifecycle, from training to deployment and observability. The tools listed in this repository cater to the needs of developers, data scientists, and machine learning engineers working with large language models and AI applications.

This repository contains an MLIR-based toolchain for AI Engine-enabled devices, such as AMD Ryzen™ AI and Versal™. This repository can be used to generate low-level configurations for the AI Engine portion of these devices. AI Engines are organized as a spatial array of tiles, where each tile contains AI Engine cores and/or memories. The spatial array is connected by stream switches that can be configured to route data between AI Engine tiles scheduled by their programmable Data Movement Accelerators (DMAs). This repository contains MLIR representations, with multiple levels of abstraction, to target AI Engine devices. This enables compilers and developers to program AI Engine cores, as well as describe data movements and array connectivity. A Python API is made available as a convenient interface for generating MLIR design descriptions. Backend code generation is also included, targeting the aie-rt library. This toolchain uses the AI Engine compiler tool which is part of the AMD Vitis™ software installation: these tools require a free license for use from the Product Licensing Site.

Notes on AI state of the art, with a focus on generative and large language models. These are the "raw materials" for the https://lspace.swyx.io/ newsletter. This repo used to be called https://github.com/sw-yx/prompt-eng, but was renamed because Prompt Engineering is Overhyped. This is now an AI Engineering notes repo.

LitServe is a high-throughput serving engine for deploying AI models at scale. It generates an API endpoint for a model, handles batching, streaming, autoscaling across CPU/GPUs, and more. Built for enterprise scale, it supports every framework like PyTorch, JAX, Tensorflow, and more. LitServe is designed to let users focus on model performance, not the serving boilerplate. It is like PyTorch Lightning for model serving but with broader framework support and scalability.

Lobe Chat is an open-source, modern-design ChatGPT/LLMs UI/Framework. Supports speech-synthesis, multi-modal, and extensible ([function call][docs-functionc-call]) plugin system. One-click **FREE** deployment of your private OpenAI ChatGPT/Claude/Gemini/Groq/Ollama chat application.

The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.

The Universal Numbers Library is a header-only C++ template library designed for universal number arithmetic, offering alternatives to native integer and floating-point for mixed-precision algorithm development and optimization. It tailors arithmetic types to the application's precision and dynamic range, enabling improved application performance and energy efficiency. The library provides fast implementations of special IEEE-754 formats like quarter precision, half-precision, and quad precision, as well as vendor-specific extensions. It supports static and elastic integers, decimals, fixed-points, rationals, linear floats, tapered floats, logarithmic, interval, and adaptive-precision integers, rationals, and floats. The library is suitable for AI, DSP, HPC, and HFT algorithms.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

AITemplate (AIT) is a Python framework that transforms deep neural networks into CUDA (NVIDIA GPU) / HIP (AMD GPU) C++ code for lightning-fast inference serving. It offers high performance close to roofline fp16 TensorCore (NVIDIA GPU) / MatrixCore (AMD GPU) performance on major models. AITemplate is unified, open, and flexible, supporting a comprehensive range of fusions for both GPU platforms. It provides excellent backward capability, horizontal fusion, vertical fusion, memory fusion, and works with or without PyTorch. FX2AIT is a tool that converts PyTorch models into AIT for fast inference serving, offering easy conversion and expanded support for models with unsupported operators.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

Awesome Embodied AI Job is a curated list of resources related to jobs in the field of Embodied Artificial Intelligence. It includes job boards, companies hiring, and resources for job seekers interested in roles such as robotics engineer, computer vision specialist, AI researcher, machine learning engineer, and data scientist.

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.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

ZX Spectrum expert in programming, game dev, and hardware troubleshooting.

AI Hardware Engineer

Valuating custom computer hardware. Copyright (C) 2023, Sourceduty - All Rights Reserved.

An advanced virtual assistant specializing in RaspBerry Pi Pico's and Micropython. Designed to offer expert advice, troubleshoot code, and provide detailed guidance.

Magically transform your design sketches and images into software, HDL code, and more!

AI Expert on Electronics and Embedded Systems.

Expert in Raspberry Pi and related tech

Checks through Embedded System Datasheet and Suggest Source Codes

专注于单片机设计和代码问题解答

This GPT will build app & answer questions for flipper zero.

Expert in MicroPython, C, and C++ for Raspberry Pi Pico and RP2040 and other microcontroller oriented applications.

Encouraging STM32 coding expert

Discover the versatile capabilities of the ESP32, the go-to board for IoT innovations. Easily create IoT applications leveraging its Wi-Fi and BLE functionalities.

Your digital design & verification guide. The conversation data will not be used for training.

Assists with Azure Quantum computing jobs, simulates API requests.

A Beginners Guide to Quantum Magic

Aid for quantum information experts.

Finds optimal PC parts based on user criteria

Leading Quantum Computing Expert and Assistant, powered by OpenAI.

A research assistant for neutral atom quantum computing.