Our unwavering focus lies in the advancement and widespread adoption of autonomous AI products and machine learning platforms. We firmly believe that the key to enabling automated analysis, control, and autonomous edge devices lies in the utilization of an advanced AI-driven approach to vision and planning, coupled with the efficient utilization of inference hardware. What sets our machine learning platform apart is our innovative utilization of vector databases.

Neural Networks

Utilizing the latest research findings, we train deep neural networks to address problems from sensing to control. Analyzing vast amounts of video data, we teach the network tasks such as semantic segmentation, object detection, and depth estimation. Based on the learned results, multiple real-time video streams are integrated, and spatial layouts, static infrastructure, and 3D objects are directly output from a top-down perspective. Additionally, the developing network learns from real-time, complex, and diverse scenarios supplied continuously.

Autonomy Algorithms

We develop autonomous driving algorithms for vehicles, we create mathematical models that mimic the surrounding environment and employ them to chart the vehicle’s path. In order to anticipate these models, we amalgamate data from numerous autonomous sensors, systematically generating accurate and comprehensive ground truth data. Harnessing cutting-edge technology, we construct resilient planning and decision-making systems adept at navigating uncertain and intricate real-world scenarios. Ultimately, we rigorously assess the most dependable integrated algorithms.

AI Training

We are dedicated to constructing an AI learning platform designed for the seamless execution of large-scale AI models. We are committed to developing cutting-edge technology that possesses the flexibility to adapt across the spectrum, from the most compact edge devices to sprawling multi-cloud distributed environments. Our approach includes meticulous design and architecture considerations to ensure peak performance, maximum throughput, and optimal bandwidth allocation at every level of granularity. We also prioritize the creation of methods for proof of concept (PoC) and performance validation to guarantee functional accuracy. In addition, we specialize in developing compilers and drivers for neural networks to enhance overall network efficiency in terms of power consumption and performance.

AI Inference

While considering microarchitecture, we build an AI inference platform that maximizes the inference performance per watt. We conduct requirement development, functional analysis, and architecture design, followed by floor planning and rigorous testing to verify performance. After performance optimization and ensuring redundancy, we implement the platform. Finally, we validate the design patterns of the platform and automate the construction process.

Build the Future of Artificial Intelligence

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