Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”. Machine Learning is a current application of AI based around the idea that we should just be able to give machines access to data and let them learn for themselves.
New technologies and capabilities have emerged to enable the development of intelligent decision-making solutions from data provided to compute systems. For multiple applications and industries, there is a close working relationship between AI, Machine Learning, Neural Networks and Deep Learning. Development platforms are available for Machine Learning/Deep Learning developments including TensorFlow and Caffe.
Deep Learning is one of the most effective methods for recognizing patterns and developing insights from unstructured data such as images, sounds, video and text, and is a key branch of Machine Learning & Artificial Intelligence development. Applications include Image Recognition, Behaviour Data Analysis, Video Surveillance and Automation & Robotics.
The emergence of AI/ Machine Learning/Neural Networks/Deep Learning solutions has also challenged the hardware side with fast and efficient SoC/ASIC/GPU/FPGA devices and solutions required.
Chipright has delivered design services within the AI technological domain by utilizing a proven pool of highly skilled senior level engineering resources. Chipright provides engineers and teams that are expert in their fields on-site or remotely. We have the capacity to supply the market with the right skill at the right price in the right location at the right time.
New clients often ask us about projects we have worked on and implemented over time in the AI market space. They also ask us about the resource pool we use on these projects. We respect the curiosity but also respect our clients NDA’s. Thus, whilst we are restricted from conveying specific information about the R&D technological projects we continually work on, we can provide a brief snapshot of some of the work without disclosing our customers detailed project information here.
Case Study – Camera Vision – SOC verification of VPU 16nm 700MHz
- Review of algorithms and test cases written in C
- Porting of the software tests and algorithms to SystemVerilog
- Added in new functionality as per AI requirement spec
- Refactored software tests to be backward compatible with previous algorithm
- C testcases requirement to be used in a HW-SW co-simulation environment
- SystemVerilog and UVM solution provided
- Updated simulation and regression flow for the new test suite
- Implemented new software testcases for some of the VPU’s security features
- Regressions and debug of software testcases for the vision subsystem verification
- Implemented SystemVerilog/UVM testcases for the image streaming logic
- Regressions and debug of both software and SV-UVM testcases
- SystemVerilog and UVM solution provided