Automotive

Deep Learning in the Automotive Industry

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THE BENEFITS OF EMBEDL'S MODEL OPTIMIZATION SDK

Embedl's Model Optimization SDK offers several benefits to companies in the automotive industry. These benefits include:

  1. Cost Reduction: By reducing the size of the model and reducing the power consumption and memory usage of the system, Embedl's Model Optimization SDK helps reduce the unit cost of manufacturing next-gen safety and convenience systems.
  2. Faster Time to Market: With Embedl's Model Optimization SDK, engineers can focus on building state-of-the-art models and be more flexible when it comes to what SoC to use. This, in turn, helps reduce the time to market for new products.
  3. Improved System Performance: By optimizing the code and reducing the size of the model, Embedl's Model Optimization SDK can improve the overall performance of the system, making it more efficient and reliable.
  4. Reduced Maintenance: With Embedl's Model Optimization SDK, engineers will spend less time on optimization and maintenance and more time building state-of-the-art models.
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FASTER EXECUTION

By using state-of-the-art methods for optimizing Deep Neural Networks, we can achieve a significant decrease in execution time and help you reach your real time requirements.

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The Embedl Optimization Engine automatically reduces the number of weights , and thus size of the model, to make it suitable to be deployed to resource constraint environments such as embedded systems.
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SHORTER
TIME-TO-MARKET
The tools are fully automatic, which reduces the need for time consuming experimentation and thus shorter time-to-market. It also frees up your data scientists to focus on their core problems.
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Less ENERGY USAGE

Energy is a scarce resource in embedded systems and our optimizer can achieve an order of magnitude reduction in energy consumption for the Deep Learning model execution.

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IMPROVED
PRODUCT MARGINS

By optimizing the Deep Learning model, cheaper hardware can be sourced that still meets your system requirements leading to improved product margins.

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DECREASED
PROJECT RISK

Optimizing and deploying our customers’ Deep Learning models to embedded systems is what we do. By outsourcing this to us, your team can then focus on your core problems.

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