Seventy years ago was arguably the start of the modern computer age. A machine that took up an entire room at a laboratory in Manchester University ran its first programme at 11am on 21 June 1948. The prototype completed the task in 52 minutes, having run through 3.5 million calculations. The Manchester Baby, known formally as the Small-Scale Experimental Machine, was the world's first stored-program computer. It paved the way for the first commercially-available computers in a city known for centuries of science and innovation. Dr "Tommy" Gordon Thomas was 19 and in the final year of a physics degree at Manchester when he met Sir Freddie Williams, who designed The Baby with colleagues Tom Kilburn and Geoff Tootill.

On the sidelines of Money20/20, held in Amsterdam this week, bobsguide caught up with Nick Cook, head of regtech and advanced analytics at the UK's Financial Conduct Authority (FCA). All of the external facing regtech sits under my department. Internally, I'm leading our more advanced analytics, both the technology side - cloud analytics - as well as building out our human side - our data science capability. Over time, through training and development we can start to build it out and expand in an osmotic fashion across the wider organisation - effectively enabling us to leverage machine learning. We're also running sandboxes and hackathons to develop and encourage the regtech contingent of the UK startup market.

When you post something on LinkedIn, chances are that an algorithm made by Rushi Bhatt's team in Bengaluru has checked if it's kosher to be on the professional network. It sounds easy but consider the complexity: LinkedIn has over 560 million members, 20 million companies, millions of job postings and it works in 24 different languages. If all its millions of users seamlessly post on the platform every day, it is because LinkedIn's algorithms, with a lot of help from humans, green-light them before the user can blink an eye. "We have to walk this fine line between freedom of expression and not letting poor content live on the site. That makes it really complicated for everybody, including humans," says Bhatt, an alum of Amazon and Yahoo with a Ph.D. in cognitive and neural systems from Boston University and degrees from the Tata Institute of Fundamental Research and what is today NIT, Surat. At its worst, a poor newsfeed can drive away users. On the other hand, a good one can keep you hooked on a platform for hours. At LinkedIn, it is the job of the "Feed AI" team to maintain fidelity. Bhatt's job is to literally keep the NSFW stuff away. It's a problem almost all major platforms with user-generated content – be it Youtube or Twitter – struggle with.

Jeff Maggioncalda was recently named CEO of Coursera. I have interviewed both founders of the company, Andrew Ng and Daphne Koller, so I was curious about Maggioncalda's perspective on the company, education technology and the massive open online courses more generally, and his own background as an entrepreneur. Regarding the last point, Maggioncalda was previously the CEO of Financial Engines Inc, a company co-founded by economist and Nobel Prize winner William Sharpe and recently sold for $3 billion. During his 18 years as CEO of Financial Engines Inc, Maggioncalda had to pivot three times from his original idea before becoming a success. Financial Engines would go on to beocme the largest independent online retirement advice platform with more than $100b under management.

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.

George Dyson was born in 1953 and had a unique opportunity to witness firsthand the conjunction of mathematics and physics that brought the digital revolution to life. He has been observing the relationship between nature and technology ever since. Dyson's latest book, Turing's Cathedral: The Origins of the Digital Universe, illuminates the transition from numbers that mean things to numbers that do things in the aftermath of World War II. I am very happy I had the opportunity to have him appear on Singularity 1 on 1 where we talked for over an hour. During our discussion with Dyson we cover a very wide variety of topics such as: his unique childhood of growing up as the son of theoretical physicist Freeman Dyson; playing around the Institute for Advanced Studies in Princeton; having Helen Dukas i.e. Einstein's secretary as a babysitter; his interest in boats and boat-building as inspired by reading Kon-Tiki; George's previous book titled Darwin Among The Machines; Samuel Butler and Ted Kaczynski; Turing's Cathedral and the origins of our digital universe; Alan Turing and John von Neumann; the hydrogen bomb and what von Neumann called "the deal with the devil"; technology's power to liberate and/or enslave; artificial intelligence, the technological singularity and our chances of surviving it.

In this conversation with Elias Crespin, a Venezuelan-born artist who builds kinetic sculptures using complex algorithms, they discuss the evolution of Crespin's work and the future of Artificial Intelligence as it pertains to art. You started your career as a computer engineer. When and how did you start creating art? As a teenager I wanted to be an architect. I loved to draw blueprints.

Coinvision sat down with Erich Spangenberg and Dan Bork, respectively, the CEO and the CTO of IPwe, a new venture creating a blockchain and AI enabled global patent market that has been attracting a lot of attention in recent months. Coinvision: Can you give us a short overview on IPwe? Maybe a little on how you came up with the business? Erich: IPwe is creating the patent asset class. We are using AI and blockchain to answer basic questions about patents – Do they exist?

New York:Thomas Tull scored a blockbuster ending to his Hollywood career. He sold his production company, Legendary Entertainment, to Dalian Wanda Group for $3.8 billion in 2016 after using data analytics for the production, marketing and distribution of blockbusters including "Inception," "The Dark Knight Rises," and "Jurassic World." Tull, 48, is adopting a similar approach with his latest venture. Tulco, based in his adopted hometown of Pittsburgh, is an investment holding company that uses artificial intelligence, machine learning and data analytics to identify investments and grow the businesses. In a phone interview with Bloomberg, Tull discussed this approach, negotiating tactics and winning a Super Bowl with the Pittsburgh Steelers. Comments have been edited and condensed.

Marvin Minsky (who passed away in 2016) was one of the founding fathers of Artificial Intelligence. Some of his achievements include a Turing Prize (awarded in 1969) include major contributions to AI, cognitive science, mathematics and robotics. Technology review posted a short interview of him in 2015 reflecting on AI research . What I find particularly interesting is when he said that they were used to major breakthroughs every week. Breakthroughs now take a few years. Sometimes we tend to lose ourselves in the enthusiasm of our machine learning's successes, and forget that we are far from the true vision of creating general artificial intelligence.