Generative AI

"Artificial intelligence is one of the most profound things we're working on as humanity. It is more profound than fire or electricity"

Sundar Pichai

Generative AI is an exciting development in the field of Artificial Intelligence. It involves the application of machine learning techniques to create new content that is similar to the data it was trained on. This technology has the potential to transform many areas of our lives and has already opened up new possibilities for embedded system development. The OpenAI Codex project which was one of the catalysts for AI hardware development launched in 2021. It created an AI system that translates natural language to code in multiple different programming languages including Python, C, C++ and more.

Generative AI is already changing the way companies approach hardware development. The most innovative companies are embracing this technology to reduce costs, speed up the development process, and create cutting-edge products at lightning fast speed. For instance, it is being used by Collimator customers to generate synthetic data for testing, optimize control system design and performance, and even design and prototype new hardware systems.

40%

of all working hours can be impacted by large language models (LLMs) like GPT-4. - Accenture

Why is AI code generation important for embedded systems?

AI generated code, a subset of Generative AI, is a powerful technology that can revolutionize embedded system development. It involves the use of machine learning algorithms to generate code automatically, reducing the time and effort required for manual coding. There are several reasons why AI code generation is being adopted rapidly for embedded systems development, including:

Increased Efficiency: AI code generation can significantly increase the efficiency of the development process, allowing hardware engineers to focus on higher-level tasks. For example, instead of manually coding low-level functions, AI code generation can automate the process, allowing engineers to concentrate on more complex and critical areas of the system. This can reduce the time to market and give companies a competitive advantage
Improved Quality: AI code generation can help improve the quality of code produced. It can catch errors and improve performance by generating optimized code, thereby reducing the likelihood of bugs and other issues. This can lead to more reliable and higher-quality systems, which are essential for safety-critical embedded systems such as automotive and aerospace systems

A shift is underway - are your modeling and simulation tools helping or hindering?

Collimator is the only tool that allows you to leverage generative AI tools to design embedded systems so you can increase your efficiency while improving reducing your risks

Unlock the full potential of your engineering team with powerful features

Design

Explore the vast number of possibilities, model to your desired complexity

Simulate

Move faster with speed and agility, get high fidelity insights earlier

Visualize

Analyze your results, increase confidence on your designs, iterate

Deploy

Automatically generate code and deploy code to your target hardware

Collaborate

Integrate your workflows and streamline
collaboration

Traditional Applications

No generative AI capabilities to automate coding tasks

Limited integrations with other development environments and tools

Involves extra time, effort and money to run HPC simulations

Python code generator AI that can be used to develop control systems or physical systems

C code generator AI that is MISRA and SAFE and can be deployed to microcontrollers

Native integration with Github and other IDEs including Visual Studio Code, Jupyter Notebooks and Github Co-Pilot

Quickly generate synthetic data over millions of runs using HPC in the Cloud