PREDICTING VIA MACHINE LEARNING: A DISRUPTIVE PERIOD FOR ENHANCED AND USER-FRIENDLY AUTOMATED REASONING INFRASTRUCTURES

Machine learning has advanced considerably in recent years, with algorithms achieving human-level performance in diverse tasks. However, the main hurdle lies not just in creating these models, but in implementing them efficiently in practical scenarios. This is where inference in AI becomes crucial, emerging as a primary concern for experts and tec