Coretec Group Inc (CRTG)

[joanders]

A few places stuck out that were mentioned by Coretech on compatibilities with Core Optics when the merger was announced 3/14, LIDAR, military.

**On-sensor AI technology** is an exciting advancement that merges the capabilities of artificial intelligence (AI) with image sensors. Let's delve into the details:

1. **What Is On-Sensor AI Technology?**
- **Definition**: On-sensor AI technology involves embedding an **image sensor directly onto an AI chip**. Unlike traditional sensors that relay image information to the CPU for computation and inference, on-sensor AI technology processes data **directly at the sensor level**.
- **Purpose**: By integrating AI processing directly into the sensor, this technology enables real-time analysis and decision-making, making it ideal for applications where speed and efficiency matter.

2. **Why Is It Significant?**
- **Efficiency**: Traditional image sensors capture raw data, which then undergoes separate AI processing. On-sensor AI technology streamlines this process, reducing latency and enhancing efficiency.
- **Real-Time Insights**: With AI algorithms running directly on the sensor, systems can extract insights in near real time. This capability is crucial for applications like autonomous vehicles, surveillance, and smart devices.
- **Autonomous Systems**: By building intelligence around each sensor, we pave the way for intelligent and eventually autonomous systems. These systems can continuously learn and adapt based on sensor data.

3. **Use Cases**:
- **Smart Cameras**: On-sensor AI enhances image recognition, object tracking, and scene analysis in cameras.
- **Automotive**: In self-driving cars, on-sensor AI processes data from LiDAR, radar, and cameras to make split-second decisions.
- **Healthcare**: Medical imaging sensors can benefit from on-sensor AI for faster diagnosis and treatment planning.
- **Industrial Automation**: Sensors embedded with AI can monitor machinery health, predict failures, and optimize production processes.

4. **Challenges**:
- **Data Volume**: High-resolution data (sometimes down to nanosecond precision) is essential for real-time analytics. Balancing data volume with processing power is critical.
- **Integration**: Ensuring seamless integration of AI processing within the sensor design is a complex engineering task.

In summary, on-sensor AI technology represents a leap forward in making our world smarter, more connected, and responsive through the fusion of AI and sensor data¹².

Source: Conversation with Bing, 3/28/2024
(1) Turning Sensor Data Into Actionable Intelligence In The Era Of AI - Forbes. https://www.forbes.com/sites/forbestechcouncil/2024/03/26/turning-sensor-data-into-actionable-intelligence-in-the-era-of-ai/.
(2) Samsung aims to fuel ISOCELL Camera with On-sensor AI technology. https://bing.com/search?q=on-sensor+AI+technology.
(3) Samsung aims to fuel ISOCELL Camera with On-sensor AI technology. https://www.sammyfans.com/2023/12/29/samsung-aims-to-fuel-isocell-camera-with-on-sensor-ai-technology/.
(4) Intelligent Sensors - A section of Sensors - MDPI. https://www.mdpi.com/journal/sensors/sections/Intelligent_Sensors.
(5) In-sensor computing for machine vision - Nature. https://www.nature.com/articles/d41586-020-00592-6.