One of the harder to observe effects of COVID-19 has been its impact on AI models. For all the advantages AI offers, AI applications are not infallible. Arguably the most common way machine learning models fail over time is when the data they were trained... (more…)

AI  Benchmark  V4:   NNAPI-1.2 Tests,  Native Hardware Acceleration,  Throttling Tests  and  More    ... (more…)

The study details a new algorithm that can produce high-resolution, photo-realistic face swaps, but head shape remains an issue. (more…)

AI is not perfect. It gets things wrong. Punctuating this is the fact that we largely don’t know how AI comes to the answers it does. Enter explainable AI. (more…)

Reproducible machine learning is hard, particularly when training deep learning models. We review common sources of DL non-determinism and how to address them. (more…)