AI and ML applications have seen rapid uptake across industries as low-cost processing and data handling capabilities increase and the power of neural networks is more widely acknowledged. Awerian maintains a competitive edge in AI and ML by working across a wide variety of applications, including signal processing, code analysis, time-varying event detection, items of interest recognition and edge analytics demonstrations for video and acoustic purposes.
Awerian’s experience translates into a deep understanding of both the common and less familiar challenges faced by the ML community. Training of networks is crucial, however this often falls victim to the limited availability of suitable data. Open source intelligence can enable the delivery of high quality data; yet, challenges such as accurate labelling, confounding signals, measurement by proxy, processing at scale and privacy concerns must all be addressed. A combination of large datasets and complex neural networks coupled with limited power or computational resource also demands innovative approaches, such as K-shot learning.
Awerian’s broad understanding across software, engineering, physics and mathematics informs an integrated approach. This applies to both processing pre-existing data and generating and augmenting new training data that replicates real-world datasets to create stronger ML models. For example, Machine Vision solutions require not only intelligent algorithm development but also optical design and simulation; hardware, electronics and firmware capabilities; and whole system integration.