As artificial intelligence becomes more integrated into our daily lives, it's important to consider the impact it has on our society. To avoid discrimination and bias, the most promising solution is federated learning, which uses a decentralized network of devices to process data, rather than relying on a central database, data warehouse or data lake. This approach helps to reduce the risk of biased results and makes it possible for a diverse group of people to contribute and help address potential biases. Join us in exploring this exciting area and how it can help shape a better future for all of us.
Public cloud displacement is a subject we don't discuss as often as we ought to. Many see relocating data and apps back from a public cloud provider to an enterprise data center as an admission that the initial decision to move the workloads to the cloud was a grave error. In my opinion, this is less of a failure than a hosting platform change depending on the current state of the economy. People frequently return to more conventional platforms because of the high expense of cloud computing. You surly remember the article from Dropbox (1), explaining why they left their public infrastructure and went to a private cloud approach.