Professional supplier of AI and robot teaching equipment
Professional supplier of AI and robot teaching equipment
$10,000
Available on backorder
The Advanced AI Experiment Box is an upgraded solution designed for higher-level AI education and research. Building on the functionality of the standard version, it features significantly enhanced computing performance, enabling local deployment of AI models without reliance on cloud services. The system supports edge-side inference and training for machine learning and deep learning applications, meeting the requirements of more complex AI scenarios.
Based on a Linux operating system and supporting Python-based development, the advanced edition allows students to work with computer vision, speech recognition, multimodal interaction, intelligent control, and AI model optimization in a fully offline environment. With its expanded computing resources and open architecture, the platform is well suited for advanced courses such as deep learning, edge AI, intelligent robotics, multimodal AI systems, and large-model application development, effectively bridging the gap between theoretical learning and real-world AI deployment.
Notice:
The listed price is for standard product reference only.
It does not apply to institutional projects, tenders, system integration, training, installation, commissioning, or customized solutions.
For project-based requirements or bulk orders, please contact us for an official quotation.
Dimensions (in)
18.9×15×7.9
Weight (kg)
11
Communication Interface
USB, Wi-Fi, Bluetooth
Structure
Aluminum alloy, integrated design, includes keyboard, mouse, power adapter, and educational tools; plug-and-play
Display
17-inch IPS screen, ≥ 1920×1080 resolution
Integrated Components
Robotic arms, 2D vision, depth vision, two-axis gimbal, voice module, embedded sensors, etc.
Computing Unit
6-core NVIDIA Carmel ARM CPU, 8GB RAM, 128GB storage, NVIDIA Volta GPU with 8GB memory
Vision Systems
2D vision: ≥ 640×480 resolution, Depth camera: ≥ 640×400 resolution
Robot Arm
5-axis, 15cm gripping range, two-finger gripper, kinematic solver, one-button start/reset
Sensors
Ultrasonic, temperature, heart rate, pressure, Bluetooth, gyro, OLED display
Open-Source Software
Full software and source code for secondary development
The AI Experiment Box allows the experiment code to be executed in the Jupyter Notebook environment with the following features:
The robotic arm combines with the vision system for target sorting and smart stacking. It uses deep learning models for complex object recognition and real-world industry training.
Depth vision enables height, distance, and contour detection, ideal for obstacle detection, live object recognition, and target tracking experiments.
The microphone supports sound detection and recognition. Interaction with the AI processor guides the robotic arm to perform tasks based on voice commands.
Offers 12 types of sensors for experiments like facial recognition, voice control, and temperature control systems.
Freely add or remove devices as needed. Contact us for assistance.
Overview and Core Characteristics of Large Language Models
Real-World Applications of Large Models Across Industries
Data Collection and Preprocessing for Large Model Training
Fine-Tuning and Training Strategies for Large Models
Local Deployment and On-Device Inference of Large Models
Building Local Services and APIs for Large Models
Prompt Engineering and Prompt Design for Text-Based Models
Developing Intelligent Text-Based Question Answering Systems
Building Intelligent Voice-Based Conversational Systems
Deployment and Applications of Multimodal Large Models
Knowledge-Based Question Answering Systems Using Large Models
Intelligent Fruit and Vegetable Sorting Using Large Models
Intelligent Video Surveillance and Security Monitoring Applications
Smart Home Control Systems Powered by Large Models
Multimodal Applications Combining Vision and Language Models
Image Generation Applications Using Cloud-Based Large Models
Audio Generation Applications Using Cloud-Based Large Models
Contact us if you need a custom course.
The key differences lie mainly in software capabilities and computing performance, while the overall hardware structure remains largely the same.
The Basic AI Experiment Box focuses on foundational AI education and hands-on practice.
The Advanced AI Experiment Box is designed for higher-level AI courses, edge AI applications, and local AI model deployment.
Yes.
The Basic version supports foundational courses such as:
Python programming
Introduction to AI
Computer vision basics
Sensor data processing
The Advanced version includes additional course resources focused on:
Large model deployment and optimization
Edge AI and intelligent systems
Multimodal AI applications
AI engineering and system integration
This allows institutions to progress from basic teaching to advanced AI engineering training using the same platform.
The Basic AI Experiment Box is ideal for introductory AI courses and undergraduate teaching.
The Advanced AI Experiment Box is better suited for advanced undergraduate programs, graduate-level courses, applied AI majors, and AI engineering training.
Many institutions adopt a combined approach, using the Basic version for foundational education and the Advanced version for advanced experimentation and project-based learning.
Please submit your download request, and we will send the relevant information to your email within 2 business days.
