The World Economic Forum predicts that, by the year 2030, an estimated 400-800 million jobs worldwide will be lost to “Big Data” powered beings. That’s 30% of the world’s population, if you were wondering. I say beings because, at the rate we’re going, to the place that technology is taking us, I believe that the devices and machines we’ll be interacting with will be little less than that.
Yes, some of us will become redundant, jobs will be lost and even skills that have become sought after will be deemed worthless. We will slowly be replaced by shiny silver machines and smart-arse algorithms, but if you look deep enough and with the right intentions, this pivotal point in our existence isn’t all doom and gloom.
People will be forced to look outside of their usual surroundings, potentially deeper within themselves for new opportunities. Companies will be hunting for out-of-the box thinkers, strategic, creative minds, and leaders. Schools will be better staffed than ever before, and businesses will be paying higher than ever too now that they don’t need Sharon from finance processing payments and paying staff entertainment bills. We will see an exponential increase in the number of SMEs, startups, and entrepreneurs and, who knows, maybe we will even see the next great art movement.
What’s so Big about this Data?
Data is the new oil. It is the steam powering this colossal train we call The Fourth Industrial Revolution. Data is the reason why computers can see better than humans, read road signs, and diagnose cancer.
Think about the last time you were shopping online, remember all those “other items you may like” or “shoppers who bought this also bought that” links at the bottom of the page? That was an example of one of the first commercially recognisable machine learning applications and, if you think about it now, it’s been around longer than you thought.
“Big Data”, a term loosely thrown around these days in the tech world, is defined by Google as:
“extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions”.
Put simply, it is clear to see why data is fuelling this wildfire revolution.
Machine learning, artificial intelligence, deep learning, the internet of things, and quite frankly, every industry, business, and our entire global economy, relies on the processing, analysing, and understanding of data, regardless of scale, shape or form.
Remember Will Smith in “I Robot”? Remember the issues he was having with the robots in the beginning of the movie? Neither do I, there weren’t any.
Eventually, however, the Robots began to learn, became more intuitive, grew faster, and stronger than poor Will, and his human edge was no longer all that useful.
Over time, every day, hour and minute, every visual cue, noise and reaction just became points in a dataset for the powerful computers inside the robots to leverage, and guess what?
The same still applies in our world today: it’s just much less chaotic, and quieter. We, as human beings living in the modern era, are permalinked to the computers inside the Internet. Forbes estimates that 90% of the world’s data has been created in the past two years – that’s easier enough to believe when you realise that we create about 2.5 quintillion bytes a day, 2 500 000 000 000 000 000 bytes a day.
Now think about what you could do with all that data, it makes sense: it’s time to build a crowd sourced hedge fund of course!
Wisdom of the Crowd
If you ever get the chance, do yourselves a favour and watch a couple episodes of the series by the same title, “Wisdom of the Crowd”. Not only does it star Jeremy Piven (Ari Gold from Entourage), but it also gives you a slight glimpse into yet another application of our new friend, Big Data and more particularly, Crowd Sourcing.
I won’t spoil the plot but in short, a crime needs solving and the guy trying to solve the crime, a tech billionaire, turns to AI and Machine Learning to help. He creates a social network for people to share information relating to the crime, where it’s picked apart by millions of people, and some clever algorithms eventually leading to the crime being solved.
I’m sure you’re asking this question by now: what do any of the past 750 words have to do with cryptocurrency?
Introducing Numerai, the world’s first hedge fund to give away all of its data, allow anyone around the world to model it with machine learning, and submit their predictions to be traded in a global equities fund. The best predictions, and therefore their masterminds, are awarded their share of the pot, some shiny Bitcoin, and the world’s biggest data science competition is born.
An anonymous team of 12 000 odd data scientists are now building the brain of Numerai’s hedge fund. Bear in mind that this is about 11 963 more than the world’s largest hedge fund, Bridgewater Associates, who have about 150 billion dollars of assets under management. Now, what’s stopping all these data scientists from just starting their own hedge fund?
Precisely this: Numerai’s data is encrypted and randomised through a very complex method called obfuscation. The data sets consist of 50 features, and the scientists are modelling a binary target of 1 or 0. Patterns can still be found even if the data is masked: think about those scatter plot graphs we had to draw as kids, all those dots. It was easy to find the best line that would connect them all even, if we had no idea what an x or y axis was.
Numerai is finding the line, but it’s just doing it in 50 different dimensions. Numerai is in control of exactly what data they want analysed, shaping the strategy while the users optimise it, still allowing them to keep their hands on the reins.
The problem of human greed then came in, with Numerai receiving more than 100 million predictions a day. With models and their respective predictions built on historical data, some sneaky scientists decided to start “over fitting” their models, making them perform much better on old data than they would in live markets.
This, in turn, scored their makers some dishonest prize money and went against exactly what the founders were striving to rectify in a very broken Wall Street economy. So what now?
That’s where the Numeraire came in – Numerai’s own cryptocurrency, and the first cryptocurrency to belong to a hedge fund. 1 000 000 of these tokens were airdropped to the scientists and they now had to stake a portion on the models they most believe in. If their model walks the walk and talks the talk, you get your stake back and a little something extra, if its flops, you lose it.
Each week, the users receive a fragment of the newly minted Numeraire and get ready for the next set of data and the next round of the world’s biggest data science competition. So why hasn’t this turned into a race to the bottom fuelled by unhealthy competition and greed?
Well, introducing the Numeraire token created another incentive: the network effect. Loosely explained, this states that the more people using something, the more valuable it becomes. Naturally, this encourages data scientists and the community as a whole to get involved rather than keep it all one big secret.
The value of Numeraire grows when the value of the hedge fund grows. Therefore, everyone staking Numeraire and competing in these weekly tournaments, has the incentive to grow the talent pool and collaborate in a mutually beneficial manner.
Wall Street and the economic environment as a whole thrives off competition, some of it unhealthy as we see massive corporate scandals surfacing every year. But, let’s not forget: collaboration has its place too, as we are beginning to see a large shift in the way in which businesses, specifically small and medium sized businesses operate and interact. But that’s a story for another day.
Richard Craib, the South African mathematician behind Numerai wants exactly that, not just of his community but that of the economic and social communities.
“The stock market is inefficient with respect to new developments in machine learning — only a fraction of the world’s data scientists have access to its data. Numerai is changing this”
For more info on exactly what Numerai is up to visit their website.