The startup develops a visual intelligence platform that employs artificial intelligence and signature-based representation structures with unsupervised learning to enhance autonomous driving applications. This technology aims to improve vehicle safety and reduce casualties on global roadways by optimizing advanced driver assistance systems and localization.
Funding
$150.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current autonomous driving systems struggle with unexpected, real-world driving scenarios, resulting in safety concerns and hindering widespread adoption. Existing AI solutions often fail to adequately address edge cases, require significant computational resources, and lack seamless integration between perception and decision-making processes.
Solution
Autobrains offers a visual intelligence platform powered by Liquid AI, a novel approach inspired by the human brain. This technology employs a network of specialized, narrow AI "skills" optimized for specific driving scenarios, enabling precise and efficient decision-making. Liquid AI's adaptive architecture dynamically adjusts to the driving context, activating only relevant modules to minimize computational demands. By utilizing self-learning signatures and perception fields, Autobrains' platform enhances edge-case detection, reduces costs, and improves overall system reliability for ADAS and autonomous driving applications.
Target Audience
The primary target audience includes automotive OEMs, Tier 1 suppliers, and technology companies developing ADAS and autonomous driving systems.
Features
- Liquid AI architecture with a network of specialized, narrow AI "skills" for specific driving scenarios
- Self-learning signatures for efficient processing of sensory information
- Perception Fields for determining the impact of road objects on vehicle behavior
- Adaptive architecture that dynamically adjusts to the driving context
- Hardware and SoC agnostic design for flexible implementation
- Low compute requirements (1-2 TOPS for Smart Camera solution)
- Compliant with GSR regulations and NCAP safety standards
- Air2Road centimeter-level accuracy localization by matching aerial and ground views