artificial intelligence to detect brain anomalies in an unsupervised manner (Baur et al., 2021).Datasets of MRIs of diseases including microangiopathy, glioblastoma, and multiple sclerosis were assessed with both supervised and unsupervised U-net models. The unsupervised deep learning model was ultimately very effective in detecting wide range of brain anomalies (Baur et al., 2021). Studies like this demonstrate that we are in the digital age of medicine, and students should be trained in artificial intelligence to be successful with these new technologies.Anatomy 3D software packages may be beneficial but are costly. Instead, we feel that institutions should start preparing and storing their own recorded practical sessions and other electronic resources in their departmental repositories to prepare for future lockdown situations. One caveat is that online sessions do require fast internet connection with adequate bandwidth. Remote areas with decreased technology infrastructure will be disproportionality affected by this. We feel that a proper responsive ecosystem needs to be created for active online learning. We think that more e-learning methods and virtual community platforms based on various social, educational, cultural, financial and geographical diversities could better learning outcomes. Modern learning materials, interactive media, information technology, and new devices can provide a better learning ecosystem. Teaching has to be made a community property (Hutchins, 1996).As stated in recent editorial, anatomists need to be leaders and should demonstrate skills to cope up with crisis in addition to being educators (Smith and Pawlina, 2021). Anatomy educators have a bigger role to play and must learn from the benefits and shortcomings of teaching methods employed during the Covid-19 pandemic.We applaud the excellent work by the authors and thank the editor for publishing such an important article.