Numerai-A New Cryptocurrency For Coordinating Artificial Intelligence on Numerai

  • One hour ago, 12,000 data scientists were issued 1 million crypto-tokens to incentivize the construction of an artificial intelligence hedge fund. Here’s why.

    Benevolence of the broker

    Markets work not because anyone is trying to make them work. No one trading in a market is trying to make that market efficient. The efficiency is merely a byproduct of the market participants believing in the value of the money abstraction, and then selfishly trying to get more of it.

    A stockbroker would prefer a world of permanent inefficiency so he can make money from it. A hedge fund would prefer permanent information asymmetry where it can extract rent on data that no one else has. In the stock market, no one wants the market to be efficient.

    The problem here is that self-interested market participants trading with all their might to earn more money are not in alignment over a goal. They are adversaries. They have no incentive to work together, to share knowledge, to share data or share code to improve the market. Finance is anti-collaborative, and that hinders progress big league.

    You may think that the problem lies with the self-interest of market participants. A solution may be to curb and regulate self-interest. But regulating self-interest is morally abhorrent. The problem isn’t with self-interest. The problem is with money itself.

    Specie and statecraft on the blockchain

    Money was invented to solve the coincidence of wants problem and facilitate transactions. But as fiat currencies continue to lose relevance into the 21st century, cryptocurrency presents solutions far beyond money transfer. Cryptocurrency can now be used to incentivize cooperation in populations.

    With cryptocurrency, money can now be software. There can be programmed rules for how money behaves. The ability to program money seems subtle, but small changes to the rules of money can have large effects on the behavior of the holders of that money. For a historical example of primitive money software influencing a population, see The Wörgl Experiment of 1932. For a modern example, consider how bitcoin incentivized thousands of people around the world to mine it.

    The stock market presents a situation similar to the prisoner’s dilemma. The market would be better off if market participants collaborated, but rationally they don’t. Regular money simply does not incentivize them correctly. Regular money is too low-tech.

    Imagine the prisoner’s dilemma in a world that exists entirely on a blockchain. Now suppose the prisoners are issued a cryptocurrency similar to a normal money except for one small change: it is programmed to self-destruct whenever anyone goes to prison. By defining the money in this way, the prisoners’ fates are now financially bound. Prisoners in this scenario realize that if they don’t keep the other prisoner out of jail, they will lose all of their money with certainty.

    This new cryptocurrency results in a world where citizens have a financial incentive to collaborate to keep each other out of jail. The prisoners are still motivated by self-interest but they now live in a universe where the money nudges them to collaborate in pursuit of that self-interest.

    Introducing Numeraire

    Last year, Numerai proposed a new kind of hedge fund, which allows any data scientist to build machine learning models on our data, and submit predictions to control the capital in our hedge fund.

    Today, we are releasing a new money abstraction for Numerai. It begins a new commerce with our data scientists based on long-term alignment not possible with regular money.

    It is a new cryptocurrency called Numeraire, and it makes collaboration compatible with self-interest.

    Proof of intelligence

    Data scientists collaborate on Numerai already. They share code. They share ideas on Slack. They write blog posts and tutorials. Numerai already has the spirit of a collaborative open software project. But the system design isn’t perfect.

    It isn’t economically rational to tell your friends to join Numerai because it isn’t rational to help anyone beat you. There is a finite amount of bitcoin given away each week so the game is zero-sum.

    So Numerai, like the market, has negative network effects — and that’s bad. Bitcoin facilitates the trade of dollars for machine intelligence on Numerai but this transaction clears the relationship and connection between Numerai and the data scientist because bitcoin and US dollars have little to do with Numerai. A Numerai data scientist has no economic incentive to tell his data scientist friends about Numerai. He would only be bringing in competition and making it harder for himself to earn bitcoin. But if every data scientist could benefit from the overall network improving then collaboration would become rational and the game would shift to positive-sum.

    Today, Numerai issued 1,000,000 Numeraire crypto-tokens to our existing 12,000 data scientists based on their past performance in Numerai tournaments. There will be no crowdsale. Numeraire can be earned right now by competing in Numerai’s data science tournaments. In a sense, Numeraire is mined by data mining Numerai’s data, and submitting predictions is the proof of work.

    With 1,000,000 Numeraire now issued, the data scientists on Numerai will all prefer those tokens to be worth more rather than less money. They are all incentivized to make them worth more. But a cryptocurrency without a compelling use case is merely a souvenir with no economic value. Numeraire’s economic value comes from its use inside Numerai.

    Staking Numeraire

    On Numerai, data scientists can never lose money, they can only win bitcoin. But starting today, there is something to lose in order for there to be more to gain.

    When a data scientist submits predictions to Numerai, those predictions are validated against historical data, and Numerai makes payouts based on how well the models performed on historical data. But Numerai cares much more about live performance in our hedge fund than backtest performance. Staking Numeraire is a way to incentivize live performance and completely disincentivize overfitting. The staking mechanism solves the biggest problem in quantitative finance; it is an economic forcing function to make backtest performance identical to live performance.

    When a data scientist submits predictions, they will be able to stake Numeraire on those predictions. This involves sending Numeraire to Numerai’s smart contract on the Ethereum blockchain. After a period of time, the predictions are analyzed. If the predictions are accurate, the data scientist who staked Numeraire on them will earn money. If the predictions are poor, their Numeraire is permanently destroyed.

    With Numeraire, there is now a way for data scientists to express confidence in their predictions the same way that traders do: by deciding how much to stake. Through our proposed staking mechanism, Numerai data scientists stand to gain by building models that perform well on live data, and stand to lose on models that overfit the past.

    The value of Numeraire is connected to the stake payouts which will increase over time. Since Numeraire allows data scientists to earn more money by staking it, it is sensible to reason about its economic value. For example, the value of all Numeraire to a data scientist with a perfect model is the net present value of all the future stake payouts by Numerai.

    Network effects in capital allocation

    Nearly all of the most valuable companies throughout history were valuable through their strong network effects. If there is one motif in American economic history it is network effects. Every railroad made the railroad network more valuable, every telephone made the telephone network more valuable, and every Internet user made the Internet network more valuable.

    But no hedge fund has ever harnessed network effects. Negative network effects are too pervasive in finance, and they are the reason that there is no one hedge fund monopoly managing all the money in the world. For perspective, Bridgewater, the biggest hedge fund in the world, manages less than 1% of the total actively managed money. Facebook, on the other hand, with its powerful network effects, has a 70% market share in social networking.

    The most valuable hedge fund in the 21st century will be the first hedge fund to bring network effects to capital allocation.

    We made a new film about network effects and Numeraire featuring Numerai investors Joey Krug (co-founder of Augur), Juan Benet (founder of IPFS and Filecoin), Andy Weissman and Fred Wilson at Union Square Ventures.

    Learn more about Numeraire in Forbes and Wired.

    Numeraire white paper by Richard Craib, Geoffrey Bradway, Xander Dunn and Joey Krug

    Numeraire smart contract by Alex Mingoia and Joey Krug

    More Details:

    A New Abstraction 

    The stock market is inefficient with respect to new developments in machine learning because only a small fraction of the world's data scientists have access to its data. Numerai data scientists aren't traders or quants, and they don't want to be. They are experts in statistics, machine learning and artificial intelligence, working as geneticists, physicists, students and professors. They have specialized in building predictive models on data—any data. So we give them stock market data in its purest, most abstract form and let their machine learning algorithms discover its predictive structure.

    Learn more about our thesis in Encrypted Data For Efficient Markets

    Assembling a Super Intelligence 


    Numerai is not a search for the ‘best’ model; it is a platform to synthesize many different, uncorrelated models with many different characteristics. Data scientists compete on the leaderboard but models are ranked and rewarded based on their contribution to the meta model.

    Learn more in Super Intelligence for the Stock Market

    A Proof of Intelligence 

    Nearly all of the most valuable companies and infrastructures throughout history were valuable through their strong network effects. But no hedge fund has ever harnessed network effects. Negative network effects are too pervasive in finance, and they are the reason that there is no one hedge fund monopoly managing all the money in the world. To make Numerai the first hedge fund with positive network effects, we issued a million crypto-tokens to our twelve thousand data scientists to incentivize coordination. Learn more in A New Cryptocurrency For Coordinating Artificial IntelligenceRead our white paper

    A Rogue Intelligence

  • Numerai’s New Tournament to Crowdsource the Future of the Stock Market

    The traditional crowdsourced machine learning tournament depends on a holdout dataset. The holdout data is some historical data known to the tournament organizer and unknown to the data scientists participating in the tournament. Data scientists’ submissions are graded and paid based on their ability to predict this holdout dataset. This creates an incentive to predict the holdout set as closely as possible, but there is no incentive to build models that generalize to the future. Data scientists are being rewarded to predict the past. This incentivizes overfitting, the primary enemy of data-driven endeavors.

    In data science, logloss is a standard metric for measuring how good a set of predictions are. Data science competitions use logloss to rank competitors. On each submission, a data scientist is given a public logloss to indicate how good the predictions performed on the public holdout dataset. The major problem with this approach is that getting consistent feedback from the competition enables competitors to tailor their predictions to the feedback itself rather than solving the actual problem. This enables the overfitting that is incentivized by holdout dataset-based rewards.

    There are many attempts to mitigate the overfitting that data scientists are incentivized to achieve in this tournament format. Most approaches involve complicating the selection of holdout sets and diminishing the usefulness of the logloss reported to the data scientists. Rather than bring together thousands of data scientists to achieve a good logloss on the past, Numerai’s only interest is to predict the future.

    Incentivizing Generalization

    To perfectly align incentives with data scientists, Numerai no longer has a holdout dataset or a leaderboard, either public or private. Rather than hide information from the data scientists, Numerai gives data scientists all known information. Instead of grading data scientists on a fixed set of past data, data scientists are graded on future data once it becomes known. Four weeks after a tournament begins, the actual outcome of what was being predicted is known. Data scientists are then ranked and paid both USD and Numeraire based solely on their ability to predict those four weeks. This makes the overfitting problem the direct adversary of the data scientists.

    A paid round of the tournament, four weeks after the tournament began. The “Live Logloss” represents how well the model predicted those four weeks.

    The above graph shows the logloss performance of an ensemble of the top user predictions in a round of the Numerai tournament. The orange line is the logloss expected of random predictions. Anything below it is a good prediction.

    Here, all the data scientists’ predictions on the future for a round of the Numerai competition are compared against a backtest (test logloss). Their backtest logloss and their actual future outcome logloss (live logloss) are very similar, indicating the backtest was a good indication of out-of-sample, future performance.

    Rather than devising increasingly complex methods of concealing information to combat overfitting, we’ve crowdsourced the overfitting problem itself. The above graphs show not only that data scientists successfully predicted the future, but that their future success was predictable. Predictable predictions can be leveraged infinitely.

    To Better Predict the Future

    Now that the data scientists in Numerai’s tournament are focused solely on generalization to the future, we’ve also released a new, human-readable feature to aid building models that are robust through time. The dataset now contains a column with time information that can be used to train models that strive for time-invariance.


    Numeraire, our new cryptocurrency to coordinate machine intelligence, will be the final economic incentive layer against overfitting.

    Learn more about Numeraire in our Film, Medium post, Smith and Crown, and Wired.

    Silicon Doesn’t Sleep. — [email protected]

  • Numerai An AI Hedge Fund Goes Live On Ethereum

    In February, Numerai announced Numeraire, a cryptographic token to incentivize data scientists around the world to contribute artificial intelligence to our hedge fund (see Forbes, Wired, Smith+Crown). Earlier today, the Numeraire smart contract was deployed to Ethereum, and over 1.2 million tokens were sent to 19,000 data scientists around the world.

    A Protocol For AI

    Numerai is building the protocol to connect machine intelligence to the stock market, and we want you to build on top of it.

    Numerai has made over $200 000 in payments to our users. We have used bitcoin to make these payments. The problem with bitcoin is that it exists on a different blockchain to the Numeraire token. This drastically limits the extent to which decentralized applications based on Numerai can be automated and unstoppable because these applications cannot receive payment in bitcoin, they can only receive and use ether.

    If Numerai made payments in ether, then a decentralized application on Ethereum could automatically use that ether to fund its operations (for example, its gas costs). Bitcoin payments make sense for people not for decentralized autonomous organizations (DAOs). We want to move more of Numerai onto Ethereum to accommodate DAOs. Making payments in ether will have large cascading effects for the kinds of applications that can interface with Numerai.

    Today we are announcing that we are abandoning bitcoin. It will be phased out of Numerai by September 30th. From that point on, all payments will flip into ether and Numeraire.

    Numeraire Live On Ethereum

    Starting today, data scientists can withdraw Numeraire tokens to any Ethereum address, and interact with the smart contract. Data scientists can also use Numeraire to earn more money by staking it on their predictions. If their predictions perform well, they earn more money. If their predictions perform badly, their Numeraire is destroyed on the blockchain.

    The staking mechanism creates a powerful new incentive to build the best machine learning model on Numerai. For thousands of people, staking Numeraire will be the first time in their lives they have interacted with an Ethereum smart contract. And they can do it all from Numerai’s website without needing to manage keys or use an Ethereum client. This is not speculative; you can stake Numeraire right now, and the Ethereum transaction will influence the course of Numerai’s hedge fund.

    Staking Numeraire on the Ethereum blockchain

    Proof Of Intelligence

    Numerai has already raised $7.5 million in traditional venture capital from Union Square Ventures, Joey Krug (Augur), Juan Benet (FileCoin), Fred Ehrsam (Coinbase), and Olaf Carlson-Wee (Polychain). So the Numeraire token will not be sold in a “crowdsale” or “ICO”.

    It is important to us that the holders of Numeraire are the people who it is most valuable and useful to: the data scientists building Numerai. So we have distributed the initial allocation of Numeraire for free to our data scientists based on their past performance in Numerai’s tournament. Numeraire can only be earned by competing in Numerai’s data science tournament.

    The Numeraire token is the reward for proving the intelligence of a machine learning model on Numerai.

    Interacting With The Contract

    More on Numeraire

    Join our Slack

    Thanks to Jeremy Gardner.

  • $1 Million Numerai (NMR) Giveaway

    n October, Numerai announced Erasure, a protocol for building trusted, unstoppable data markets. In March, we announced an $11 million raise
    to make it happen. We’re announcing lots more this quarter. Starting
    with this: we’re launching the Numerai Grants Program, $1 million in NMR
    to support teams building on top of Erasure.

    Erasure Vision

    Recapping the Erasure plot

    “A very advanced form of lie detector that measures contractions of the iris muscles…” — Blade Runner’s Voight-Kampff Test of Humanity

    Erasure powers markets for information, by leveraging the core trust models of crypto — staking, time-stamping, and public-key identities.

    On Erasure, you can upload encrypted data, stake it with cryptocurrency, then sell it to a buyer. The buyer trusts you because your past is etched into the blockchain, your stake can be burned if your claims are false, and because the purchase is handled atomically via smart contracts.

    Erasure started with finance. What if we took everything Numerai’s learned about crowdsourcing ideas for trades, and built a platform for anyone to build a market for themselves? I joined the project because, after a stint at a hedge fund in Connecticut and a payments app outside Somaliland, I saw Erasure as part of a defining, generation-long effort: to extend market infrastructure to the frontier. Erasure answers the question of how to drive more capital into Ethiopia, or into fusion startups. Build a marketplace for diligence.

    But as we built, the vision expanded. Markets with both high trust and high privacy can empower whistleblowers. Richard tweeted: “The next Snowden will use Erasure.” We started to see Erasure as part of another grand, generational project: to make the Web more trusted. Fake news is a signal problem of our time, and it’s getting worse. Imagine a Web where skin-in-the-game is de rigueur, where activity is logged on permanent but anonymized identities, where communication is peer-to-peer. It’s a Web we want. Drop Erasure into your next site.

    Grants ⇋ NMR

    Grants in the context of NMR 2.0

    Erasure wants a great developer community. Numerai wants NMR to be the best token in the world. The Grants Program serves both.

    In December, we announced our plan to fix all the bad things with NMR.

    Good tokens have constrained supply. So we committed to burn most of the NMR we had the right to mint (reducing total supply by ~50%). Good tokens are secure. So we committed to shutting down contract upgradability (so the rules never change).

    Good tokens are widely used. Erasure will help here — majorly. It will expand the usefulness of NMR from Numerai’s tournament, for only Numerai’s data scientists, to a theoretically unbounded set of finance tournaments, media sites, and apps of other kinds.

    Good tokens, finally, are widely held. This is where the Grants Program comes in. Tokens are subject to classic network effects. Getting them into engaged holders’ hands mean new transaction possibilities, more global incentive alignment, and less discretionary market power for whales. NMR should be held by the community, not by Numerai, in the long run. We believe this strongly.

    Let’s be quantitative. Below is NMR’s current state, then ideal state. We get there via a contract upgrade in the immediate term, and Erasure in the long term. The token on the right, simply put, is the one we’d prefer to hold. We expect it’s the same for you.

    The best way to get NMR to the community is to give it to the community. But we’ll do this carefully. New supply in circulation should generate lasting value, and offsetting demand. This is why we love grants. A great way to build value for NMR is to give NMR to builders. There’s a precedent close to home. NMR wasn’t launched with an ICO. We gave it to our best data scientists. The strategy worked. So we’re doing it again.

    How to Apply

    How does Numerai’s Grants Program work?

    We’re looking for people with charismatic ideas about the future. If you have them, we’ll support you.

    The grants process is direct:

    1. Send us your concept for an app powered by Erasure to [email protected] Write as much detail as you can. Tell us your budget.
    2. If we’re intrigued, we’ll chat. We’ll give you suggestions. We’ll introduce you to our protocol team.
    3. Once we get a final plan, including milestones for releasing funds and technical specs, if everyone is excited, we’ll roll.

    App Concepts

    What can be built on Erasure?

    We love the idea of new trading tournaments built on Erasure. We love the idea of media sites with Erasure baked in. Or surprise us.


    “How can a Marriott spin-off be an exciting market inefficiency and the chaotic development of half the planet not be?” — What Would Ben Graham Do Now?

    Imagine a world where every hedge fund ran their own tournament. They’d pull the backend data direct from Erasure. Their frontend would be an oracle for calculating reputation. They’d put up a bounty for signals and call on the community to submit.

    Some tournaments we’d love to fund:

    • One specialized entirely in Tesla (or another widely-followed company), calling for predictions across its financial statements.
    • One specialized in a fast-growing frontier country stock market, like Kenya’s, helping developed-world funds move money to it from abroad.
    • One specialized in crypto, both quant and discretionary.


    “Time’s up on 10,000 years of recorded history. This is coming. This is real.” — Steve Bannon on #MeToo

    Imagine a world where every company had an open bounty for information on corporate crimes. The site is native to Tor, and because it’s on Erasure, its backend is as censorship resistant as the blockchain. Or imagine a social media site where people staked cash on their claims. You burn scambots to the ground, and the $TSLAQ fintwit folks have to put money where their mouths are.

    Some apps we’d love to fund:

    • Bounties to whistleblow crimes, corporate and otherwise.
    • A Twitter UX, but with a tip jar and a burn lever.
    • A browser plugin, that puts money at stake on real Twitter from Chrome.


    Or surprise us. Drop Erasure into a remote work platform to align incentives. Build a decentralized bug bounty system leveraging Erasure’s anonymity. We’d love a React package that makes it easy for an Erasure modal to pop up anywhere.


    “The enhancement of agency — this theme, this is the ground on which the right and the left can meet” — Roberto Unger to Peter Thiel

    What’s the connecting thread? The ultimate goal, to my mind, is redistribution: get capital into the hands of people who know scarce truths. You can be a teenager in Nairobi with a Juypter install, competing in a crowdsourced signal tournament. You can be a janitor at a bank in London, who’s witnessed fraud. Or you can be an AI. We’re building systems of moving money where truth is the sole objective function. Join us.

    Thanks to Richard Craib and Natasha-Jade.

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