Applied Intuition – Streamline autonomous system development, testing, and deployment

In the rapidly evolving landscape of autonomous technology, Applied Intuition offers cutting-edge solutions to streamline the development, testing, and deployment of automated driving systems and vehicle software. With a focus on both on-road and off-road applications, this platform is engineered to bolster the capabilities of industries ranging from automotive to defense.

Its comprehensive suite of tools supports the entire lifecycle of autonomous system development, making it a critical resource for teams working on AI agents and complex workflows.

What is Applied Intuition?

Applied Intuition is a platform dedicated to accelerating the development of autonomous systems. It provides software solutions that enable engineers to design, simulate, test, and validate advanced driver-assistance systems (ADAS), automated driving (AD) technologies, and off-road autonomy stacks.

The platform serves as an end-to-end development environment, reducing reliance on costly and time-consuming real-world testing by leveraging high-fidelity simulation. It is part of a broader ecosystem of AI automation tools designed for industrial and enterprise applications.

Key Features

• ADAS and AD Development Platform: Enables comprehensive development, testing, and validation of advanced driver-assistance and automated driving technologies.

• Vehicle Software Platform: A robust framework for developing, deploying, and managing complete vehicle software ecosystems.

• Off-road Autonomy Stack: Tailored solutions for enhancing autonomous operations in unstructured, off-road environments.

• Simulation and Validation Tools: Advanced simulation capabilities that replicate complex real-world scenarios for thorough testing.

• Applied Intuition Copilot: A generative AI-powered chatbot that assists users within the development platform.

Use Cases

• Automotive Manufacturers: Innovating and enhancing the safety and efficiency of next-generation vehicle systems.

• Defense Contractors: Developing autonomous systems for defense and security applications in challenging terrains.

• Agriculture Sector: Automating and optimizing machinery for farming, planting, and harvesting.

• Mining and Construction: Improving safety and operational efficiency for heavy machinery in harsh environments.

Underlying AI Models or Technology

Applied Intuition's platform integrates a range of AI and machine learning technologies. Its core simulation engine relies heavily on computer vision and sensor fusion models to create realistic virtual environments. For decision-making and planning modules, the platform utilizes techniques from robotics and reinforcement learning.

The Applied Intuition Copilot feature is powered by generative AI, leveraging large language models for natural language interaction. This assists engineers in querying system data, generating code, and troubleshooting, effectively applying language generation capabilities to a specialized engineering context.

Pricing

Applied Intuition operates on a custom pricing model. Costs are tailored based on specific industry requirements, the scale of deployment, and the modules or services selected.

For the most accurate and current pricing details, visitors should refer to the official Applied Intuition website.

Pros and Cons

Pros

• Accelerated Development Cycles: Facilitates quicker iterations and problem resolution, significantly reducing time to market.

• Enhanced Safety Protocols: Utilizes simulation to minimize risks associated with real-world testing.

• Cross-industry Adaptability: Offers flexible solutions applicable across automotive, agriculture, defense, and more.

Cons

• Steep Learning Curve: The advanced nature of the tools may require significant training for new users.

• High Infrastructure Dependency: Optimal performance relies on robust technological setups, which can be a barrier.

Alternatives

Teams exploring autonomous system development may also consider these platforms:

• CARLA: An open-source simulator for autonomous driving research.

• NVIDIA DRIVE Sim: A simulation platform built on NVIDIA's Omniverse for AV development.

• MathWorks RoadRunner: A tool for designing 3D scenes for simulating and testing automated driving systems.