"AI is not a panacea. It cannot solve all problems. And like every technological disruption before it (the steam engine, internal combustion, electricity), it will bring about disruption good and bad." (Andrew Ng, [blog post] 2018)
"Carrying out error analysis on a learning algorithm is like using data science to analyze an ML system’s mistakes in order to derive insights about what to do next. At its most basic, error analysis by parts tells us what component(s) performance is (are) worth the greatest effort to improve." (Andrew Ng, "Machine Learning Yearning", 2018)
"In practice, increasing the size of your model will eventually cause you to run into computational problems because training very large models is slow. You might also exhaust your ability to acquire more training data. [...] Increasing the model size generally reduces bias, but it might also increase variance and the risk of overfitting. However, this overfitting problem usually arises only when you are not using regularization. If you include a well-designed regularization method, then you can usually safely increase the size of the model without increasing overfitting." (Andrew Ng, "Machine Learning Yearning", 2018)
"It is very difficult to know in advance what approach will work best for a new problem. Even experienced machine learning researchers will usually try out many dozens of ideas before they discover something satisfactory." (Andrew Ng, "Machine Learning Yearning", 2018)
"Keep in mind that artificial data synthesis has its challenges: it is sometimes easier to create synthetic data that appears realistic to a person than it is to create data that appears realistic to a computer." (Andrew Ng, "Machine Learning Yearning", 2018)
"AI is the new electricity: even with its current limitations, it is already transforming multiple industries. (Andrew Ng, [blog post] 2018)
"Artificial Intelligence can't solve all the world's problems, but it can help us with some of the biggest ones." (Andrew Ng) [attributed]
"Artificial Intelligence is a tool to help us be better humans, to help us get through the world more easily and richer and be more productive and engaging." (Andrew Ng) [attributed]
"If you can collect really large datasets, the algorithms often don't matter." (Andrew Ng) [attributed]
"Missing data is an opportunity, not a limitation." (Andrew Ng) [attributed]
"No one knows what the right algorithm is, but it gives us hope that if we can discover some crude approximation of whatever this algorithm is and implement it on a computer, that can help us make a lot of progress." (Andrew Ng) [attributed]
"Real-world problems are messy, and they rarely fit exactly into one category or another." (Andrew Ng) [attributed]
"The ability to innovate and to be creative are teachable processes. There are ways by which people can systematically innovate or systematically become creative." (Andrew Ng) [attributed]
"The key to AI success is not just having the right algorithms, but also having the right data to train those algorithms." (Andrew Ng) [attributed]
"The more data we can feed into the algorithms, the better models we can build." (Andrew Ng) [attributed]
No comments:
Post a Comment