If you're too young to realize where the title reference comes from, I'm gonna make you lose your mind. It has something to do with parties and rocks and anthems. Actually, no, I just want you to have a good time so I'll instead ask you to take a look at the title picture. I am obviously drawing your attention to both the title and picture for a reason. With the title, you might not have realized there was a "pattern" to it till I pointed it out.

Shaw: Pedro Domingos has one of the most incredible resumes in the world of AI, and we were thrilled to host him for a fireside chat at our most recent Data Driven NYC. We covered a bunch of things, including why finance is a killer app for machine learning, his much-lauded book, 'The Master Algorithm' and what's truly scary about AI (hint: not the Terminator). The video is below, followed by some conversation notes. Finance is "the killer app for machine learning": Having said that if you look at the number of connections that the state of the art machine learning systems for some of these problems have, they're more than many animals – they have many hundreds of millions or billions of connections. What we're trying to do with AI is just to repeat that but a million times faster, or even 10 or 100 million times faster – and I think we can. But for evolution there is a bottleneck, which is the size of your genome.

Sign in to report inappropriate content. Pedro Domingos, bestselling author and Head of Machine Learning at DE Shaw, spoke with FirstMark's Matt Turck at a fireside chat at Data Driven NYC in October 2019. They spoke about Pedro's book, The Master Algorithm, why Pedro considers financial markets'the ultimate machine learning problem,' and much more. Data Driven NYC is a monthly event covering Big Data and data-driven products and startups, hosted by Matt Turck, partner at FirstMark Capital.

Machine learning is something new under the sun: a technology that builds itself. Right now we have limited algorithms with limited potential, but, if it exists, the Master Algorithm could derive all knowledge in the world from data. Inventing it would be one of the greatest advances in the history of science, speeding up the progress of knowledge across the board and changing the world in ways we can barely even begin to imagine. So says Pedro Domingos, professor of computer science at the University of Washington and author of the book "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World." He joined the podcast to discuss his book and the possible utopian and dystopian futures of AI. Below is a lightly-edited transcript of our conversation. You can also subscribe to my podcast on iTunes or Stitcher, or download the podcast here. JAMES PETHOKOUKIS: In the book you write, "Machine learning is something new under the sun, a technology that builds itself. And at its core, machine learning is about prediction: predicting what we want, the results of our actions, how to achieve our goals, how the world will change." Now, your book came out in 2015, and while it made the bookshelf of China's president in his New Year's address, I missed the book when it came out. The reason we are chatting today and I found out about the book was because Amazon recommended it to me. I had bought a previous book, called "Why Information Grows" by Cesar Hidalgo, who will also be a guest on an upcoming podcast, and when I bought that book it recommended your book as something I would also like. So, I bought it, and indeed I liked it very much. Now, for that recommendation I can thank machine learning, right? So machine learning tries to figure out what your tastes in books are, and clearly in this case it was a good call. So, for example, "Why Information Grows" -- by the way, I know Cesar well; he is a great guy -- is related to machine learning, so if you read that book you might like "The Master Algorithm" as well, and it seems that was a good call. Now, I suppose as a way of kind of explaining what machine learning is: How did that algorithm, Amazon, how did it do that?

In my last article about Blackbox Society we had discussed how biased algorithms are influencing our society. If you are familiar with machine learning algorithms you would know that there are different type of algorithms for different purpose. There is no one solution or one approach that fits all. Based on the data type, category of problem and constraints you identify the algorithm. With so many techniques and algorithms will there be a single master algorithm that solves all the problems including choosing, prioritizing and combining various algorithms.

With wit, vision, and scholarship, Domingos decribes how these scientists are creating programs that allow a computer to teach itself.

Typing "what is machine learning?" In addition to an informed, working definition of machine learning (ML), we aim to provide a succinct overview of the fundamentals of machine learning, the challenges and limitations of getting machine to'think', some of the issues being tackled today in deep learning (the'frontier' of machine learning), and key takeaways for developing machine learning applications. The above definition encapsulates the ideal objective or ultimate aim of machine learning, as expressed by many researchers in the field. The purpose of this article is to provide a business-minded reader with expert perspective on how machine learning is defined, and how it works. References and related researcher interviews are included at the end of this article for further digging.

The quality and shape of human decision-making is taking a profound leap forward thanks to new partners: artificial intelligence and machine learning. Many intelligent people view AI with alarmism, but not Pedro Domingos, the University of Washington professor working at the cutting edge of machine learning. He wrote The Master Algorithm, which I swallowed whole and have been digesting every since. I was fortunate enough to have a long and fascinating conversation with him over dinner one night which I hoped would never end -- but that ended up leading to this interview, in which we explore new sources of knowledge, why white collar jobs are easier to replace than blue collar jobs, centaur chess players, and so much more. The Excerpts below are from my interview with him for the knowledge project, a podcast exploring ideas, methods, and mental models, that help expand your mind, live deliberately, and master the best of what other people have already figured out.

To the right, young software engineers sit in front of their laptops in the windowless, artificially lit rooms. To the left, computer science professor Pedro Domingos opens the door to his office, which has a view of the massive trees on campus. Domingos' book "The Master Algorithm," about the technology of artificial intelligence (AI), made him famous and is also considered a standard reference work. The best-selling book, published in 2015, describes how machines that can learn are changing our everyday lives -- from the social networks and science to business and politics and right up to the way modern wars are waged. The book drew praise from Microsoft founder Bill Gates and Google CEO Eric Schmidt. Recently, a third prominent figure noted that he'd read the book: Chinese President Xi Jinping. When state television broadcast his new year's speech this year, viewers discovered that next to Marx's "Capital" and "Selected Works" by Mao Zedong, he also has a copy of "The Master Algorithm" on his bookshelf. "The book is much read in China," says Domingos. "That's probably why Xi and his people became aware of it. It's possible that it has now become even more popular."

With wit, vision, and scholarship, Domingos describes how these scientists are creating programs that allow a computer to teach itself.