“Nearly 90 percent of ML models built globally are never brought to light, primarily because they cannot adjust to the variety of information available in real-world applications.
The solution Andrew Ng has proposed is to put aside the architecture of an AI model and focus on what it is working with, i.e. the data. By paying close attention to what a model learns and improving the quality of data, and subsequently retraining the ML model, engineers can build higher quality systems in a much shorter time.
Andrew Ng believes that the right people can put this idea to use constructively to counter many issues, such as manufacturing, treating diseases, energy consumption and food production, all with the help of AI-backed with the appropriate data.”
