Proponents of AI trading argue that these systems have the potential to deliver higher returns compared to traditional trading methods. AI can spot market trends, identify opportunities, and react to changes in real-time, potentially maximizing profits and minimizing losses. Nothing is guaranteed in life, but AI can be used to deliver technical-based trading signals and significantly increase profit possibilities. AI can be used, for example, to analyse each cryptocurrency’s chart to determine if it has a bullish or bearish technical setup.
Weather forecasts have historically relied on physics-based simulations powered by supercomputers. Such methods, called Numerical Weather Prediction models, are constrained by long computational time, and are sensitive to approximations of the physical laws on which they are based. AI will revolutionise weather forecasting, and is already being used in multiple cutting-edge weather prediction models - covering both short-term (MetNet-3) and medium term (GraphCast) weather forecasts, to help meteorologists to advance and understand how weather is predicted.
Tanks to AI, conventional traffic management systems have rapidly way to Active Traffic Management (ATM). ATM allows traffic to be managed dynamically, according to current or expected traffic conditions. In traffic flow prediction, AI models can be designed to run analysis on historical and real-time traffic data. This is done to consolidate the data and use it to understand patterns and trends in traffic flow. Predictive analysis is used by traffic planners to forecast future conditions so that personnel are better able to deal with it effectively in terms of resource allocation, route optimization to minimize traffic congestion, and the adjustment of traffic signal times.
