Best AI tools for< Ai Hardware Engineer >

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.

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.

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 website is an AI tool that offers a wide range of AI, software, and tools for enterprise growth and automation. It provides solutions in areas such as AI hardware, automation, application security, CRM, cloud services, data management, generative AI, network monitoring, process intelligence, proxies, remote monitoring, surveys, sustainability, workload automation, and more. The platform aims to help businesses leverage AI technologies to enhance efficiency, security, and productivity across various industries.

Code Generator for Arduino is an AI-powered tool that allows users to generate code for Arduino projects effortlessly. The website uses GPT-3.5-turbo, OpenAI's large-scale language-generation model, to create Arduino code. Users can easily create code for their Arduino devices by simply inputting their project requirements. The generated code must be reviewed before being uploaded to any hardware devices. Code Generator for Arduino is not affiliated with Arduino SA but provides a convenient solution for Arduino enthusiasts to streamline their coding process.

Sighthound is an AI-powered video solutions provider that specializes in solving complex video AI problems at scale. Their products, such as Sighthound ALPR+ for Automatic License Plate Recognition and Sighthound Redactor for Video Redaction, leverage deep learning technology to unlock valuable user insights, reduce operational costs, and increase revenue in the privacy and vehicle recognition space. With a focus on simplicity and customer support, Sighthound offers easy integration of their AI products through simple-to-use APIs.

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.

Helsing is an AI tool designed to serve and protect democracies by leveraging artificial intelligence technology. The company focuses on developing software-first solutions that enhance defense capabilities and safeguard democratic values. Helsing collaborates with industry and governments to integrate advanced AI with hardware platforms, aiming to achieve technological leadership in the defense sector. The team at Helsing comprises experts with diverse backgrounds in software, defense, intelligence, and artificial intelligence, united by a shared commitment to upholding democratic principles.

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.

NVIDIA is a world leader in artificial intelligence computing. The company's products and services are used by businesses and governments around the world to develop and deploy AI applications. NVIDIA's AI platform includes hardware, software, and tools that make it easy to build and train AI models. The company also offers a range of cloud-based AI services that make it easy to deploy and manage AI applications. NVIDIA's AI platform is used in a wide variety of industries, including healthcare, manufacturing, retail, and transportation. The company's AI technology is helping to improve the efficiency and accuracy of a wide range of tasks, from medical diagnosis to product design.

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.

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.

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.

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.

ThirdAI is a production-ready AI platform designed for enterprise use, offering out-of-the-box solutions that work at scale and provide 10x better price performance. The platform features enterprise SSO, LLM guardrails, built-in models, a no-code interface, and implicit feedback & RLHF. It allows for turnkey deployment of complex AI ecosystems, enabling business leaders to solve critical needs quickly. With a focus on security, scalability, and performance, ThirdAI helps drive innovation and achieve business goals from day one.

Tensoic AI is an AI tool designed for custom Large Language Models (LLMs) fine-tuning and inference. It offers ultra-fast fine-tuning and inference capabilities for enterprise-grade LLMs, with a focus on use case-specific tasks. The tool is efficient, cost-effective, and easy to use, enabling users to outperform general-purpose LLMs using synthetic data. Tensoic AI generates small, powerful models that can run on consumer-grade hardware, making it ideal for a wide range of applications.

Earth AI is a high-performance explorer for clean energy minerals, utilizing artificial intelligence to discover untapped critical metal deposits at half the cost and in a fraction of the time. The company works with mineral resource companies to improve their odds of success while keeping costs low, offering accurate AI-driven prospect detection, modular hardware, and streamlined operations. Earth AI's revenue model is independent of service profits, and their process is four times faster than traditional methods. The company partners with explorers and development companies to bring discovered deposits into production.

Airship AI is a cutting-edge, artificial intelligence-driven video, sensor, and data management surveillance platform. Customers rely on their services to provide actionable intelligence in real-time, collected from a wide range of deployed sensors, utilizing the latest in edge and cloud-based analytics. These capabilities improve public safety and operational efficiency for both public sector and commercial clients. Founded in 2006, Airship AI is U.S. owned and operated, headquartered in Redmond, Washington. Airship's product suite is comprised of three core offerings: Acropolis, the enterprise software stack, Command, the family of viewing clients, and Outpost, edge hardware and software AI offerings.

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.

FlagPerf is an integrated AI hardware evaluation engine jointly built by the Institute of Intelligence and AI hardware manufacturers. It aims to establish an industry-oriented metric system to evaluate the actual capabilities of AI hardware under software stack combinations (model + framework + compiler). FlagPerf features a multidimensional evaluation metric system that goes beyond just measuring 'whether the chip can support specific model training.' It covers various scenarios and tasks, including computer vision, natural language processing, speech, multimodal, with support for multiple training frameworks and inference engines to connect AI hardware with software ecosystems. It also supports various testing environments to comprehensively assess the performance of domestic AI chips in different scenarios.

TurnkeyML is a tools framework that integrates models, toolchains, and hardware backends to simplify the evaluation and actuation of deep learning models. It supports use cases like exporting ONNX files, performance validation, functional coverage measurement, stress testing, and model insights analysis. The framework consists of analysis, build, runtime, reporting tools, and a models corpus, seamlessly integrated to provide comprehensive functionality with simple commands. Extensible through plugins, it offers support for various export and optimization tools and AI runtimes. The project is actively seeking collaborators and is licensed under Apache 2.0.

This repository contains the source code for the userspace level runtime driver for Coral devices. The software is distributed in binary form at coral.ai/software. Users can build the library using Docker + Bazel, Bazel, or Makefile methods. It supports building on Linux, macOS, and Windows. The library is used to enable the Edge TPU runtime, which may heat up during operation. Google does not accept responsibility for any loss or damage if the device is operated outside the recommended ambient temperature range.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

ESP32_AI_LLM is a project that uses ESP32 to connect to Xunfei Xinghuo, Dou Bao, and Tongyi Qianwen large models to achieve voice chat functions, supporting online voice wake-up, continuous conversation, music playback, and real-time display of conversation content on an external screen. The project requires specific hardware components and provides functionalities such as voice wake-up, voice conversation, convenient network configuration, music playback, volume adjustment, LED control, model switching, and screen display. Users can deploy the project by setting up Xunfei services, cloning the repository, configuring necessary parameters, installing drivers, compiling, and burning the code.

Dataflow-oriented robotic application (dora-rs) is a framework that makes creation of robotic applications fast and simple. Building a robotic application can be summed up as bringing together hardwares, algorithms, and AI models, and make them communicate with each others. At dora-rs, we try to: make integration of hardware and software easy by supporting Python, C, C++, and also ROS2. make communication low latency by using zero-copy Arrow messages. dora-rs is still experimental and you might experience bugs, but we're working very hard to make it stable as possible.

ByteMLPerf is an AI Accelerator Benchmark that focuses on evaluating AI Accelerators from a practical production perspective, including the ease of use and versatility of software and hardware. Byte MLPerf has the following characteristics: - Models and runtime environments are more closely aligned with practical business use cases. - For ASIC hardware evaluation, besides evaluate performance and accuracy, it also measure metrics like compiler usability and coverage. - Performance and accuracy results obtained from testing on the open Model Zoo serve as reference metrics for evaluating ASIC hardware integration.

The Frame Firmware & RTL Codebase is a comprehensive repository containing code for the Frame hardware system architecture. It includes sections for nRF52 Application, nRF52 Bootloader, and FPGA RTL. The nRF52 handles system operation, Lua scripting, Bluetooth networking, AI tasks, and power management, while the FPGA accelerates graphics and camera processing. The repository provides instructions for firmware development, debugging in VSCode, and FPGA development using tools like ARM GCC Toolchain, nRF Command Line Tools, Yosys, Project Oxide, and nextpnr. Users can build and flash projects for nRF52840 DK, modify FPGA RTL, and access pre-built accelerators bundled in the repo.

Workshops is a repository containing workshop subjects and materials for developers. It covers a wide range of topics including AI, AR/VR, hardware, security, software, and peer-to-peer technologies. The repository is designed to provide developers with resources and materials to enhance their skills and knowledge in various technology domains.

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'.

ChatGPT Smart Speaker is a project that enables speech recognition and text-to-speech functionalities using OpenAI and Google Speech Recognition. It provides scripts for running on PC/Mac and Raspberry Pi, allowing users to interact with a smart speaker setup. The project includes detailed instructions for setting up the required hardware and software dependencies, along with customization options for the OpenAI model engine, language settings, and response randomness control. The Raspberry Pi setup involves utilizing the ReSpeaker hardware for voice feedback and light shows. The project aims to offer an advanced smart speaker experience with features like wake word detection and response generation using AI models.

The IBM Analog Hardware Acceleration Kit is an open-source Python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence. It consists of two main components: Pytorch integration and Analog devices simulator. The Pytorch integration provides a series of primitives and features that allow using the toolkit within PyTorch, including analog neural network modules, analog training using torch training workflow, and analog inference using torch inference workflow. The Analog devices simulator is a high-performant (CUDA-capable) C++ simulator that allows for simulating a wide range of analog devices and crossbar configurations by using abstract functional models of material characteristics with adjustable parameters. Along with the two main components, the toolkit includes other functionalities such as a library of device presets, a module for executing high-level use cases, a utility to automatically convert a downloaded model to its equivalent Analog model, and integration with the AIHW Composer platform. The toolkit is currently in beta and under active development, and users are advised to be mindful of potential issues and keep an eye for improvements, new features, and bug fixes in upcoming versions.

EDA-AI is a repository containing implementations of cutting-edge research papers in the field of chip design. It includes DeepPlace, PRNet, HubRouter, and PreRoutGNN models for tasks such as placement, routing, timing prediction, and global routing. Researchers and practitioners can leverage these implementations to explore advanced techniques in chip design.

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Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

The neo is an open source robotics research platform powered by a OnePlus 3 smartphone and an STM32F205-based CAN interface board, housed in a 3d-printed casing with active cooling. It includes NEOS, a stripped down Android ROM, and offers a modern Linux environment for development. The platform leverages the high performance embedded processor and sensor capabilities of modern smartphones at a low cost. A detailed guide is available for easy construction, requiring online shopping and soldering skills. The total cost for building a neo is approximately $700.

RTL-Coder is a tool designed to outperform GPT-3.5 in RTL code generation by providing a fully open-source dataset and a lightweight solution. It targets Verilog code generation and offers an automated flow to generate a large labeled dataset with over 27,000 diverse Verilog design problems and answers. The tool addresses the data availability challenge in IC design-related tasks and can be used for various applications beyond LLMs. The tool includes four RTL code generation models available on the HuggingFace platform, each with specific features and performance characteristics. Additionally, RTL-Coder introduces a new LLM training scheme based on code quality feedback to further enhance model performance and reduce GPU memory consumption.

AIOsense is an all-in-one sensor that is modular, affordable, and easy to solder. It is designed to be an alternative to commercially available sensors and focuses on upgradeability. AIOsense is cheaper and better than most commercial sensors and supports a variety of sensors and modules, including: - (RGB)-LED - Barometer - Breath VOC equivalent - Buzzer / Beeper - CO² equivalent - Humidity sensor - Light / Illumination sensor - PIR motion sensor - Temperature sensor - mmWave / Radar sensor Upcoming features include full voice assistant support, microphone, and speaker. All supported sensors & modules are listed in the documentation. AIOsense has a low power consumption, with an idle power consumption of 0.45W / 0.09A on a fully equipped board. Without a mmWave sensor, the idle power consumption is around 0.11W / 0.02A. To get started with AIOsense, you can refer to the documentation. If you have any questions, you can open an issue.

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.

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