Company: CCIXW
Filing Date: 2025-12-05
Form Type: S-4/A
Source: 0001193125-25-309933
Chunk: 465

Company: Churchill Capital Corp IX/Cayman
Filing Date: 2025-12-05
Form: S-4/A
Chunk 465
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 Architecture

SuperDrive is powered by a layered AI architecture consisting of modular, specialized components that work together to perceive, reason, and act in real time:

Reasoning Model (Vision‑Language Model). Built on a vision‑language architecture, this model is responsible for high‑level decision‑making and contextual understanding. It interprets complex environmental cues (e.g., construction zones, temporary signage, unusual traffic patterns) and supports behavior that mimics human‑like judgment and intent recognition.

Reflex Model (End‑to‑End Transformer) . An end‑to‑end transformer‑based architecture composed of two integrated sub‑models—perception and motion forecasting. The Reflex Model processes sensor data to directly generate driving actions in real time and outputs an interpretable intermediate perception layer used by the Guardrails system. This dual‑functionality supports fast, data‑driven reactions while maintaining system transparency.

Guardrails (Safety Assurance) . A rule‑based module that continuously monitors and evaluates the Reflex Model’s proposed driving trajectories to ensure alignment with core safety principles, including collision avoidance, safe following distances, and compliance with traffic laws. Guardrails will automatically override unsafe actions and, if no safe maneuver is possible, bring the vehicle to a controlled stop.

This layered oversight ensures SuperDrive maintains a high level of operational safety and reliability under a wide range of driving conditions.

Our architecture is intentionally designed to promote transparency, auditability, and safety assurance. By exposing intermediate perception outputs and validating every driving action through the Guardrails system, PlusAI addresses the “black‑box” limitations common to fully end‑to‑end neural networks. This hybrid design combines the flexibility of large AI models with deterministic rule‑based safety mechanisms, enabling scalable deployment while meeting the rigorous standards required for autonomous operations.

Efficient Learning and World Models

PlusAI leverages generative AI, open foundation models, and a proprietary dataset accumulated over nine years of development to build highly generalizable driving intelligence. The dataset spans multiple geographies (United States, Europe, Asia), day and night driving, various weather conditions, and different traffic densities.

Key capabilities include:

Self‑Supervised Learning . Our company’s generative world model predicts future video frames to learn physical dynamics, traffic rules, and human behavior without heavy manual labeling.

Scenario Simulation . Text‑based and tokenized trajectory conditioning enables simulation of rare and safety‑critical events, enhancing robustness in edge cases.

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This approach improves model generalization and allows for faster iteration without the limitations of manually