What Applied AI Be About in 2022?
AI chips, an advanced creation of hardware designed to run AI-related workloads, continue to experience explosive growth, improvement, and modernization. Nvidia has been controlling the whole market for decades and has managed to create a vast empire around its hardware and software ecosystems. During last year, scientists had tried to
AI chips, an advanced creation of hardware designed to run AI-related workloads, continue to experience explosive growth, improvement, and modernization. Nvidia has been controlling the whole market for decades and has managed to create a vast empire around its hardware and software ecosystems.
During last year, scientists had tried to explain various areas related to MLOps and found the MLOps domain that includes data version controls and continuous machine learning, as well as implemented the equivalent of test-driven development for data, among other things.
Knowledge sharing in machine learning was also on the rise. Leaders such as Intel’s Gadi Singer, LinkedIn’s Mike Dillinger, and Hybrid Intelligence Centre’s Frank van Harmelen, all highlighted the importance of knowledge association in the form of knowledge graphs for the future of AI.
Source: VentureBeat.
