Andrew Ng Deep Learning God & Model Quality or Data Quality : What Is More Important?
““In business applications (like much of science in general!) human intuition will typically lead to quality and availability data. This doesn’t mean we stop at intuition – we want to apply AI and technology to augment intuitive intelligence, correct its biases, and scale it in a cost effective way.
The best way for the data to catch up to intuition is to get the intuition into a model that can quickly improve decision making and be a guiding light for investments in future data. The ROI of data becomes clear, and the flywheel effects can ensue.
In this sense, the models deeply matter and your initial models are especially important for success on the journey, especially when decision making and humans are in the loop of your AI approach. Explainable and causal models are quite important.” – Wharton Professor Amit Gandhi
One needs a robust machine intelligence ecosystem that can be applied to multiple problem sets and anchor the core of an enterprise strategy.
Unfortunately, there is no lack of noise in the AI space, leaving business leaders confused, out of their depth of expertise, or constantly justifying investments.
The result?
Most first-generation AI initiatives are in a perpetual state of “POC,” over-complexifying the non-complex while simultaneously ignoring the actual complexities.
This leads to noncompetitive products, bored data science talent, and zero models production-ready in any true machine learning sense, which can add up to hundreds of millions of dollars in waste.
Companies need to promote unorthodoxy and divergence from legacy belief systems if they hope to build more competitive strategies where real competitive advantage exists.
To avoid irrelevance requires a convergence of an in-depth technical understanding of machine learning,, and intellectual value creation embedded as the anchor of strategies and operations.
This is a rare thing In most corporations, especially old ones, characteristics that would make an AI program great are systematically rooted out.
Model Quality or Data Quality : What Is More Important?
Algorithm Construction for Data Analytics – Rebellion Research
Andrew Ng Deep Learning God & Model Quality or Data Quality : What Is More Important? Model Quality or Data Quality : What Is More Important? Model Quality or Data Quality : What Is More Important?
