“AI is akin to building a rocket ship. You need a huge engine and a lot of fuel. The rocket engine is the learning algorithms but the fuel is the huge amounts of data we can feed to these algorithms.”— Andrew Ng, amazon.com
“Metadata use is growing because it helps content producers and distributors adapt to changing business requirements, build greater efficiencies, optimize content slates and revenue, and create more relevant experiences for consumers.”— Ooyala, go.ooyala.com
“Time spent up-front understanding all of the nuances and intricacies of the data is time well spent.”— Marck Vaisman, amazon.com
“The more context an AI has, the better it can handle open-ended requests.”— Mark Zuckerberg, facebook.com
“More structure leads to more flexibility. It’s the foundation of adaptive content. Instead of one all encompassing blob of content we should lean toward several meaningful chunks. More and smaller chunks of content provide a means to better combine our content in different ways.”— Steven Bradley, vanseodesign.com
“In general, the more rules and facts we start out with, the more opportunities we have to induce new rules using ‘inverse deduction.’ And the more rules we induce, the more rules we can induce. It’s a virtuous circle of knowledge creation, limited only by overfitting risk and computational cost.”— Pedro Domingos, amazon.com
“And people are an essential part of this process. You must be able to incorporate human knowledge and expertise into your data pipeline at almost every level; it is the right balance and combination of humans and machines that will determine a deep search system’s true capabilities and ability to ad…”— Jacob Perkins, streamhacker.com
“As a rule of thumb, a dumb algorithm with lots and lots of data beats a clever one with modest amounts of it.”— Pedro Domingos, homes.cs.washington.edu
“Deep search requires a deep understanding of your data: what it is, what it looks like, what it’s good for, and how to transform it into a format that machines can understand.”— Jacob Perkins, streamhacker.com
“If you think that something might be a concern in the future, it is better to get historical data now.”— Martin Zinkevich, martin.zinkevich.org
“Machine learning only works when you have data — preferably a lot of data.”— Adam Geitgey, medium.com