Learn how to use Copilot, your AI design assistant, to brainstorm and develop a new idea from concept to custom board design. Discuss requirements, generate architectures, research parts, and draw your schematic.

Learn how to design PCBs faster with generative AI in this 20 minute hands-on tutorial. You’ll learn how to use Flux Copilot, an AI-powered hardware design assistant, to research parts, review your design, and even connect components. https://youtu.be/FL7e0OXTLic

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Learn how to use Copilot, your AI design assistant, to brainstorm and develop a new idea from concept to custom board design. Discuss requirements, generate architectures, research parts, and draw your schematic.

Learn how to use Copilot, your AI design assistant, to brainstorm and develop a new idea from concept to custom board design. Discuss requirements, generate architectures, research parts, and draw your schematic.

Learn how to use Copilot, your AI design assistant, to brainstorm and develop a new idea from concept to custom board design. Discuss requirements, generate architectures, research parts, and draw your schematic.

Learn how to design PCBs faster with generative AI in this 20 minute hands-on tutorial. You’ll learn how to use Flux Copilot, an AI-powered hardware design assistant, to research parts, review your design, and even connect components. https://youtu.be/FL7e0OXTLic

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Product Type: Wearable AI pendant Primary Function: Records audio, generates transcripts, and organizes information about daily interactions User Interaction: Input: Activation button Output: RGB LED ring, Bluetooth link to phone Key Features: Audio Recording: Activated by button press Transcription: Converts audio to text Sentiment Analysis: Embedded AI evaluates sentiment Information Management: Filters essential information and action items Technical Specifications Form Factor: Wearable pendant Display: RGB LED ring around the edge Sensors: 2 Microphones 1 Button Connectivity: Bluetooth for phone linkage Wi-Fi USB-C for charging Wireless Protocol: Wi-Fi, Bluetooth Battery Type: LiPo 2000 mAh Battery Life: 6 hours of continuous use Charging Method: USB-C Operating Voltage: 3.3V Operating Conditions: Temperature Range: -10°C to 70°C Humidity: 10 to 90% Software: Python for AI and processing Compliance: RoHS, FCC, CE Reliability: 20,000 hrs Life Cycle Expectancy: 10 years AI Capabilities Speech to Text Recognition: Converts audio input to written text Embedded AI Sentiment Analysis: Evaluates the mood or sentiment expressed in the text Essential Information Filtering: Identifies and segregates crucial data and actionable items Power Consumption and Efficiency Power consumption must align with battery capacity to ensure 6 hours of continuous operational use.

Learn how to use Copilot, your AI design assistant, to brainstorm and develop a new idea from concept to custom board design. Discuss requirements, generate architectures, research parts, and draw your schematic.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

Learn how to use AI Auto Layout on this ESP32 Espresso Smart Scale! In one click you’ll see AI Auto Layout perform magic. Pay close attention to how we recommend creating rulesets, zones, and fanouts. By copying the setup in this example on your own project, you’ll have a fully routed board in no time!

Learn how to use AI Auto Layout on this ESP32 Espresso Smart Scale! In one click you’ll see AI Auto Layout perform magic. Pay close attention to how we recommend creating rulesets, zones, and fanouts. By copying the setup in this example on your own project, you’ll have a fully routed board in no time!

Learn how to use AI Auto Layout on this ESP32 Espresso Smart Scale! In one click you’ll see AI Auto Layout perform magic. Pay close attention to how we recommend creating rulesets, zones, and fanouts. By copying the setup in this example on your own project, you’ll have a fully routed board in no time!

Learn how to use AI Auto Layout on this ESP32 Espresso Smart Scale! In one click you’ll see AI Auto Layout perform magic. Pay close attention to how we recommend creating rulesets, zones, and fanouts. By copying the setup in this example on your own project, you’ll have a fully routed board in no time!

Learn how to use AI Auto Layout on this ESP32 Espresso Smart Scale! In one click you’ll see AI Auto Layout perform magic. Pay close attention to how we recommend creating rulesets, zones, and fanouts. By copying the setup in this example on your own project, you’ll have a fully routed board in no time!

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Learn how to use AI Auto Layout on this ESP32 Espresso Smart Scale! In one click you’ll see AI Auto Layout perform magic. Pay close attention to how we recommend creating rulesets, zones, and fanouts. By copying the setup in this example on your own project, you’ll have a fully routed board in no time!