FanDuel’s co-founder leaves to create an eSports company

FanDuel co-creator Nigel Eccles has been toying with startup ideas ever since his company proposed a merger with DraftKings, and he's taking action now that the merger has fallen apart. Eccles has stepped down from his CEO and chairman positions to h…
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FanDuel CEO and co-founder Nigel Eccles is leaving to start an eSports company

FanDuel’s board is getting an overhaul, too.

FanDuel CEO and co-founder Nigel Eccles is leaving the company and stepping down from its board, where he was chairman.

Eccles, who’s been CEO since the company’s founding in 2009, announced internally that he is leaving to start an eSports company. Monday is his last day.

Eccles had been kicking around new startup ideas ever since FanDuel and DraftKings, rival fantasy sports sites, agreed to a merger late last year. Eccles was set to be the chairman of the new joint company but he was not going to be CEO. Hence the interest in starting something new.

That deal fell through in July after the government threatened to block it to prevent the two companies from forming a monopoly. While both companies are relatively small, they both offer daily fantasy sports competitions, which are a somewhat niche portion of the fantasy sports world. The Federal Trade Commission argued that “the combined firm would control more than 90 percent of the U.S. market.”

That meant that Eccles, who had been planning something new, was suddenly back in charge of FanDuel for the long haul. That obviously is no longer the case.

Eccles replacement as CEO is Matt King, who served as FanDuel’s CFO for three years ending in 2016. He then left and spent a year at insurance broker Cottingham & Butler before returning to FanDuel to become its CEO. King, who has also spent more than a decade at investment firm KKR, is taking a board seat.

FanDuel is adding two more people to its board. Carl Vogel, former vice-chairman and president of Dish Network, is joining FanDuel’s board as chairman. David Nathanson, a former Fox Sports executive who left the company this fall, is also joining the board.

Eccles isn’t say much about his new venture just yet, except that it’s in the competitive video gaming industry know as eSports and it’s very early. “Just a thought in my head,” he said in an interview. Eccles says he’s excited about getting into an industry that’s just taking off — eSports is much less established than the traditional sports world he’s been focused on with fantasy sports.

“Traditional sports are in harvest mode,” he said in an interview with Recode. “ESports are in growth mode.”


Recode – All

Alibaba was selling counterfeit Brooklyn Nets gear even as its co-founder was buying a stake in the team

Fake Nets apparel was readily accessible on the Taobao shopping site.

On the day news broke that Alibaba co-founder Joe Tsai was purchasing 49 percent of the Brooklyn Nets NBA franchise, plenty of the team’s gear was available on his company’s shopping sites.

The problem is that many of those items were counterfeit, Recode found after reviewing listings on Alibaba’s Taobao shopping site on that October day as well as on Singles Day, China’s massive online shopping holiday on Nov. 11.

Some seemed like obvious fakes just by looking at them.

A counterfeit purple Brooklyn Nets sweatshirt listed on Alibaba’s Taobao shopping site.
A counterfeit Brooklyn Nets sweatshirt listed on Alibaba’s Taobao shopping site. 178 Chinese Yuan is approximately $ 27.

While in other cases, a sale price of $ 7 for a basketball jersey coupled with blurred-out labels gave it away.

A counterfeit Jeremy Lin Brooklyn Nets jersey listed for sale on Alibaba’s Taobao shopping site.
A counterfeit Jeremy Lin Brooklyn Nets jersey listed on Alibaba’s Taobao shopping site.

In a statement, an Alibaba spokeswoman said: “Once these listings, which were posted by third-party sellers on Alibaba’s marketplace, were brought to our attention, we took action to investigate and remove them. As is our commitment and practice, we will continue to do so in close cooperation with rights holders.”

For years, Alibaba has struggled to fight the perception that its shopping sites — particularly Taobao, where millions of small merchants hawk their wares across one billion listings — were hospitable to counterfeit and knock-off goods.

In December, the U.S. placed Taobao back on its “Notorious Markets List” of “online and physical marketplaces that reportedly engage in and facilitate substantial copyright piracy and trademark counterfeiting.”

At the time, Alibaba said it was “very disappointed” with the decision and insinuated it was “influenced by the current political climate” following the election of President Donald Trump, who has criticized the current trade relationship between the two nations.

Earlier this year, the company announced the “Big Data Anti-Counterfeiting Alliance” with big consumer brands to share information and data to curb counterfeiting.

Alibaba says it uses machine learning and other advanced technologies to identify and weed out fakes. It said it closed down 180,000 merchant storefronts on its properties. The company also relies on rights-holders — or brands — to help it identify fakes when its technology doesn’t.

A solution still seems a ways off, though. Even after the Nets listings in question were taken down, other NBA team jerseys that appear to be counterfeits still remain.

An NBA spokesperson did not respond to a request for comment.


Recode – All

Full transcript: Bridgewater Associates hedge fund co-founder and author Ray Dalio on Recode Decode

“Our goals are to have meaningful work and meaningful relationships through radical truthfulness and radical transparency. That is a magic formula.”

On a recent episode of Recode Decode, Ray Dalio, the founder of the world’s largest hedge fund Bridgewater Associates, talks about his new book, “Principles: Life and Work.” In the book, he outlines the “idea meritocracy” in place at Bridgewater and how it can be used to make better workplaces. Independent thinking, he says, is the most important principle.

You can read some of the highlights here, or listen to the entire interview in the audio player below. We’ve also provided a lightly edited complete transcript of their conversation.

If you like this, be sure to subscribe to Recode Decode on Apple Podcasts, Spotify, Pocket Casts, Overcast or wherever you listen to podcasts.


Kara Swisher: Recode Radio presents Recode Decode, coming to you from the Vox Media podcast network. Hi, I’m Kara Swisher, executive editor of Recode, and you’re listening to Recode Decode, a podcast about tech and media’s key players, big ideas and how they’re changing the world we live in. You can find episodes of Recode Decode on Apple Podcast, Spotify, Google Play Music or wherever you listen to your podcast. Or, just visit recode.net/podcasts for more.

Today in the red chair is Ray Dalio, the co-chairman of the hedge fund Bridgewater Associates, which he co-founded in 1975. He’s the author of “Principles: Life and Work,” which the New York Times described as part memoir and part how-to guide. In the new book, he shares lessons and processes that have guided him throughout his career. Ray, welcome to Recode Decode.

Ray Dalio: Thank you. Glad to be here.

Thanks for coming in. I’m going to go first to your background. It’s a famous hedge fund. It’s one of the biggest … Is it the biggest or … ?

Yeah, it’s the biggest.

Okay, so talk a little bit about how you got to where you got, and then we’ll get into the book itself.

Well, I grew up on Long Island, and when I was 12 I caddied at a local golf course, and then I learned … At the time, the stock market was hot. I took my caddying money and I put it in the stock market.

When you were 12?

Well, it sounds precocious but, at that time, everybody was talking about the markets. Then, when I put it in the markets, I bought a stock. It was the only company I ever heard of that was selling for less than $ 5 a share. I thought I could buy more shares, and I’d make more money if it went up, which is a dumb strategy, but I got lucky. The stock tripled.

Which stock?

Northeast Airlines.

Oh my God, I remember, yeah.

It was a company … “Come on down. Let’s go to Florida on Northeast Airlines.” Anyway, it tripled in value, and I was hooked on the market. I thought it was easy. Investing in the markets is anything but easy, it’s really taught me humility, which was the most important thing. That’s how I got started. That was the game I liked. I was no good at school. I have a bad memory. I didn’t like school, but I loved playing the markets. Then, I got into C.W. Post College on probation.

Right, on Long Island.

Yeah, on Long Island, and then, I …

I grew up in Roslyn Harbor, that’s why.

Oh, okay.

Yeah.

We know the neighborhood.

Yeah.

I loved college, because it was a whole different thing. Then, I went to Harvard Business School, and I traded markets. Then, when I got out in 1973, and that was the time of the oil crisis. I went as Director of Commodities to a brokerage house, because I knew how to trade commodities. Then, I started my own business in ’75, because I didn’t fit in well in the company and I like to do things myself, so I formed Bridgewater in ’75.

What was the theory? Did you ever … All the hedge funds, the ones I’ve met, have a theory of the market. Did you have one or what was your conception?

No, no. I love playing the game, and I love macro. I love economics. I like the whole … seeing the whole world, global macroeconomics. That was my game. Everybody’s got a different angle, but I like macro.

Mm-hmm, but that was a very different trading situation when you started, it was very different. It wasn’t quite as automated. Algorithms were not as important, and different things. Talk a little bit how it’s changed, because I think, especially with the Internet, everything became very different on Wall Street on how people … or, maybe not.

Yeah, yeah. Well, artificial intelligence began in 1953, and we’ve gone through this long phase. For me, it’s been a long time, 25 years of writing down algorithms and doing that, and of course, it’s developed, but there were neural nets, there were all sorts of ways of thinking, and also, by the way, a lot of lessons to be learned from that.

Of course, now, it’s much more the case that people are beginning to understand, I still think it’s just the tip of the iceberg, that in investing or in any other area, that you can express your thought in an algorithm, and that the computer can make decisions in parallel with you. We’re seeing that operate in trades and in the markets, but we’re seeing it operate in everything. It’s just that evolution.

I do want your take on how Wall Street has changed, though, in the past … between 1975 and now, that’s a really … it’s a delta.

First, in terms of transactions. In the old days, you would call a person to make an order. There were certain people who, they are pals with the broker and there’s all of that. Now, it’s just automated, and it’s a blessing to get past all of that, because you have the conflicts of interest that existed back then. If this guy’s a pal, he’s not giving you the best trades, all of that was going on. Order execution has totally changed. Information processing has totally changed, and we’re just beginning, really, the movement toward algorithmic decision-making, meaning, generally speaking, the last, maybe year or two, or three, you start to see people do better algorithmic decision-making. Let me break it out in this way.

All right, please do.

It’s true for all of AI. How do you come up with your algorithms? You’re going to come up with your algorithms … Let’s get off of the Wall Street thing, because I think it’s absolutely true.

Yeah, it’s everywhere.

It’s the same thing everywhere, right? The question is, what do you come up with your algorithms? Do you put the data into the computer and let them derive the algorithms, and believe those algorithms, and then move forward and bet on with that?

Based on those, mm-hmm.

Okay, is that where you come up with them? Or, do you have the criteria in your head and then express them as algorithms? That is the big difference, right, as we’re at this juncture. I think the important thing, I just want to get this out, is the question is, what is the role of understanding, and when can you do that, and when can’t you do that?

My experience in the history of the markets has shown that if it doesn’t … If you don’t understand it, if you can’t explain the algorithm, and understand that that cause-effect relationship make sense, whatever it is, and the future is different from the past, you’re probably headed for trouble. That’s not true of just markets, so algorithmic … How do you come up with them?

Right. What inputs do you put into them?

I express them. I need to have deep understanding for the cause-effect relationships, though in some cases, you don’t need it if you know the future is going to be similar to the past. If you’re playing chess, no problem. If doctors are doing surgeries and you take that data, and you’re going … no problem. If you don’t have a deep understanding and you’re in a situation where the future is different from the past, God help you.

Yeah, it’s interesting, because algorithmic decision-making, obviously, it’s the hot area in Silicon Valley, and how it applies to various businesses and everything else. In terms of making investment decisions, do you imagine it leading to … You were talking about input that is required by you.

Yes, in my approach.

Right.

By the way, it’s not just investment decisions. What’s happened is, the people decisions are made the same way, as you saw it from my TED talk. When we’re dealing with any individuals making any decisions, the real question is, can you write that down clearly and write it in words.

Right, and then express it.

Then, convert that into algorithms. What I learned was this magic that has nothing to do with investments, although it works in investments, everything else, is that whenever I would make a decision, rather than just make a decision, I would take the time to write down what my criteria for the decisions are.

Whenever I encounter something, I have those principles written down, that’s what the book is, but mostly a collection of those principles. And then magic happened, wonderful things happened, because when that was written down, first of all, I could, when the next one of those situations came up, I can refer to it. I would be able to collaborate with others to see all those good criteria so we would form …

Shift them dependently.

Pay our attention, we would modify them. Then, we were able to convert words into algorithms, and then we could take those algorithms and back-test how they would have performed in the future, to enhance our learning. Then, put them into decision-making so that the computer works in parallel with us, like driving with a GPS, it gives its decisions and I’m giving decisions next to it, or playing chess with it, a chess game next to you, playing as your partner. Then, when I’m doing that reconciliation, either it teaches me or I help to teach the computer, and that has been the key to our success.

Okay, that’s a great hope, obviously. There is also others that feel like the computer will take over all decision-making.

Well, but I think the question is, is it in parallel? Are you working in parallel, like playing that chess game? Garry Kasparov, I was speaking with him about that. He loves to play it with the chess game next to him, and him next to it, that kind of interaction. I think that’s the best way to do it. It doesn’t take over unless it makes sense.

Right, and you’ve read about all the worries around that.

Yes, and I’m trying to address that, and I’m saying, “What do you do about it? When should you worry and when shouldn’t you worry?” I’m distinguishing when you shouldn’t worry from when you should worry, that’s what I’m answering your question about.

All right, so let’s talk a little bit about it. What caused you to … You’re here running this huge hedge fund, what is the size of it?

We manage $ 160 billion.

That’s a lot of money. Yeah, that’s a lot. You are doing this, obviously, busy doing this, what prompted you to write this book about it? Then, we’ll go through some of the principles you think are critical.

The book is not about investment principles. There’s two sets of principles. I wrote the book to help people make their decisions better, because I learned through my experiences. Matter of fact, so the history is that I don’t even like to be public. I didn’t want to write the principles. I thought it was presumptuous to write the principles. Then, in 2008 we anticipated the world financial crisis when others didn’t. We have an unusual culture, an idea meritocratic culture, and because of that, we got a lot of attention for what this is like, and people didn’t understand it.

How did you do it?

Yeah, so I put these principles that I accumulated over that period of time, online, they were in a PDF file. They were downloaded 3.5 million times. I got lots of thank-you notes, and so on and so on.

Then, now, today, I’m at a stage in my life where I’m going from what I consider my second phase in my life to my third phase in my life. I think life pretty much exists in three phases. In the first phase, you’re learning from others and you’re dependent on others. In the second phase, you’re working and others are dependent on you, and you’re trying to be successful. As you go from that second phase to the third phase, you get to a certain age where your kids are grown up, or the people you care about, you’re no longer trying to be more successful, you’re trying to help other people be more successful. This collection of these principles were things that took me from having nothing …

Which we learn along the second phase.

Which I learned along the way. It took me from having nothing to having what people conventionally think of as success, and so on, and helped a lot of people. I wanted to put them together in one place.

You initially started off with a PDF that got viral, presumably, and then you moved on to this. Let’s break it apart. You’ve broken it up into two parts, this book. Why don’t you talk about how you formulated it, and we’ll talk about some of the individual principles you think are critical.

Yeah, well, there’s this book, and then there’s one other book that will come.

Oh, there’s two?

I only have one now. In another year and a half.

Okay.

When I learned … This book is about life and work principles. The next one will be economic and investment principles. Then, anything that I have of value in my thinking will be in those, and I could pass that along. In this book, it was this collection of experiences, and mostly the appreciation of the failures and how to learn. I think there’s a process of learning and it goes through it. I think that in a nutshell, I think there’s only two things people have to do in order to be successful. They have to know what the right decisions are, and they have to have the courage to make them.

Yeah, just that.

That’s it, but the biggest tragedy of most people is that they think that the right decisions are in their heads. They have opinions that they’re attached to, and that I learned over … I learned through experiences, and I learned humility, the market teaches you humility, and I learned then that, how to go beyond that to create an idea of meritocracy. That’s explained in the book, in brief, and an idea of meritocracy. There are three things you have to do. First is, you have to put your honest thoughts on the table for everybody to see, and the people have to do that. Then, you have to have … know the art of thoughtful disagreement.

Right, which is a big topic these days.

It’s a good thing, it’s a big topic, because that’s an important thing.

It is. The lack of … There was a very good article yesterday by Bret Stephens in the New York Times about the dying art of disagreement. It was really …

I saw that, I saw that. Right.

We’ll get to that in a second, but go ahead.

That art of thoughtful disagreement, to find … Being beaten around and making mistakes taught me that one of the smartest things I could do is find the smartest people who disagree with me, and to understand their perspective, and engage in that art of thoughtful disagreement.

There are protocols to do it right and wrong. First, you have to put your honest thoughts on the table with others. Second, you have to execute that art of thoughtful disagreement. Third, then you have to have idea meritocratic ways of getting past your disagreement. In other words, a vote or something that’s going to get you … If we all disagree, we could still have a relationship, but we have to get past our disagreement and get on to do things, and the way of doing that is idea meritocratic. Our culture, this idea meritocratic culture has been mind-blowingly effective.

When it’s effective.

It has been mind-blowingly effective. I’ll tell what it’s like.

All right.

In one sentence, what we want, what I want, and what we’ve been striving to build out, and largely built out …

This is at Bridgewater?

Yeah, and I think it should be … I would encourage it everywhere. Here’s the sentence and you’ll see whether it’s the right thing. First of all, idea meritocratic thinking, so the best idea wins out, in which the goals are to seek meaningful work and meaningful relationships, they’re both equally important. The meaningful work is being on a mission that you’re excited about and that does great things. The meaningful relationships mean that you are there for each other, and that you get rewards out of those. The work and the relationships will reinforce each other if they’re operating well.

Then, in order to get those things to have radical truthfulness and radical transparency, when I mean radical truthfulness is just, put everything on your table and get past it. Radical transparency is to make it that virtually everybody can see virtually everything for themselves. We record things. Almost every conversation is all recorded for everybody to listen to. It’s not surveillance, it’s so everybody can form their own opinions and not have spin.

Know what happened. Yeah, right.

Because when you go to radical transparency, then people get to see things for themselves, which is, if they don’t, they can’t be part of that idea meritocracy, because it’s not transparent. And also, bad things happen in the dark, where good things happen in the light of day.

I’ll repeat that sentence. The goal is to have real idea meritocracy in which we’re trying to have … Our goals are to have meaningful work and meaningful relationships through radical truthfulness and radical transparency. That is a magic formula. It’s been a magic formula, knowing what we don’t know and how to get past that to be independent thinkers, that has been the formula that has worked for us. In other words, it’s taken me from being that lousy student and whatever, to what has happened in terms of those types of successes. It’s been applied, increasingly, in a lot of other places, and I think that that’s important for me to pass along.

We’re here with Ray Dalio, he’s the co-chairman of the Hedge Fund Bridgewater. When we get back, we’re going to talk more about his book, “Principles: Life and Work,” and how to do it, because a lot of people — we aim for a tech audience here — think they have the best way of running companies. They have various and different schemes, and I’d love to talk about those when we get back.

Great.

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Today we are talking to Ray Dalio, the co-chairman of hedge fund Bridgewater Associates, which he co-founded in 1975, but he’s here because he’s talking about a new book he’s written, called “Principles: Life and Work.” An enormous amount of people are recommending it, including a lot of tech people, Bill Gates, Reed Hastings and others.

Tech has always thought of itself as a new way of managing, and they do it by various ways, each of them has a different thing, but a lot of it has to do with the idea of meritocracy, the idea of transparent decision-making, and other things that you’ve talked about here. It doesn’t always … It’s not always true, necessarily, because it seems to me a that a lot of … I’m just going to use tech companies, because we can talk about those first, but it applies to all companies. There’s a lot of top-down at these companies, there’s a lot of celebration of a single CEO genius, and that they know best, essentially.

A lot of these companies are run … They also talk a lot about meritocracy, within a lot of cases, it’s a meritocracy, it’s a lot of the same people talking about things. These are things you talked differently about in your book, that you wanted people who are different. You wanted thoughts that were different. Can you talk a little bit about that? Because I think a lot of people talk about putting these things into practice, and they don’t actually happen. They create these, almost empires. I’m not sure how to describe it.

Yeah, there’s two ways of making it. You’re either going to have autocratic, and that’s bad, and/or you’re going to have democratic.

Right, you talked about that, that was interesting to me, because those are the two ways companies are set up in a lot of times.

Yeah.

Talk about autocratic first.

The boss is right.

Right.

Okay. Look, no human being has anywhere near the capacity to make the great decisions, as great collective decision-making. If you know how to tap the boat the best, and how to stress test those ideas, you’re going to get radically better decision-making …

Than a top-down?

Than a single person making a decision, a top-down decision-making. You can do that now with technologies. I hope we’ll get into this, because we’ve done a lot of these.

Yeah.

It’s not sensible. It’s arrogant. It won’t last. It’s not effective. I think, by the way, a lot of tech people … I get to speak to most of the people who are running most of the big tech companies, and I think there’s a real appreciation for that issue of collective decision-making, of getting data on people and doing that idea meritocracy.

And how to do it effectively.

The question is, how to do it effectively so that’s what we talked about, but … Idea meritocratic decision-making is great. Then, in addition, today, we have data, so we can know everything about what everybody’s like. It’s easier than ever to know what everybody is like.

If you have a group of people who want to do that, who want to be a participant in that, who themselves want and know what it’s like, then, what they’re like, that you can do that in partnership with this radical transparency so they can know their strengths and weaknesses, and that you can put together teams of people better. They know how to develop. They know how to guardrail themselves better. If somebody’s weak at something and somebody else is strong, that makes them better, so that’s better.

We’re in the world of this radical transparency, and radical knowing what it’s like. It’s only a question of how that’s used to produce …

And how you apply it.

… and use that idea meritocratic process. In addition, if you take your criteria for decision-making and you write them in an algorithm, so that everybody can see, okay, not only does that make better decision-making, but it creates more of an idea meritocracy because they can see it and they can be part of building that.

Now, imagine that you can have a better idea meritocracy, you could have more buy-in, you could have better decision-making, you have that transparency, you can do that. The great thing about Silicon Valley is that there’s open-mindedness to what is the new and better ways, and there’s an appreciation for those kinds of things. Yeah, there’s great receptivity in pursuing those things. Now is the time for the debate on that. How far do you take it, what does it look like, all of that. That’s what we’re getting into.

What are the challenges? The second part you talked about … I don’t want to get away from it, is the democratic, explain that, because that’s another type of Silicon Valley company. I remember being at a meeting for a company that’s now, of course, fell apart, because there’s so many of them, but everybody was deciding at the same time. They even had the janitor give an idea of, which I think their idea is that everybody has a good idea, and you don’t know where it’s from. They have this flat kind of structure.

Well, the problem with the democracy is that it assumes at equal … Everybody’s views are equally valuable. Okay, that’s just not the case, right? In order to do this properly, the best way is to do believability weighted decision-making.

You talked about this. Can you go into this?

Sure. I want to explain the concept first, and then we’ll get the mechanics of how you get at it.

Sure, please.

Let’s say you have an illness, and okay, what do you know about the illness? You don’t know much about it. Then, what you do is you can go to three — here’s, by the way, the path for anything — three experts, three believable people who will argue with each other to try to find what the right answer is. Then, you hear those, is there triangulation that that’s a good path or is there disagreement? When you bring up the disagreement, you get a hell of an education, because you see what the disagreeing points are. You work those things through, and then at the end of the day, when you’re going to make your decision of what you’re going to do, you will make a believability weighted decision.

You’re going to think, “That guy knows more about this, and that guy there,” and if I have triangulations, that’s what believability weighted decision-making is. Then, the question of how to do it within an organization, and that’s where really the beauty of the algorithms and the computer decision-making can come in, because what happens is you can get to know what people are like. We have, literally, believability weighted decision-making.

For every one of your employees?

Yes.

Okay, based on, how does that input in?

Let me first touch on what that looks like.

Okay.

Okay. There are many different dimensions, something like, think of it as 50 different dimensions that a person might be believable in, right? You might have an expertise in one area, somebody else might have something else.

Be specific, for example.

Well, it’s either … It could be either a subject matter or it could be a thinking quality. Let me give you a thinking quality. Somebody is very creative, a big-picture thinker, but they’re not reliable. Somebody’s really reliable, pays attention to detail, let’s say.

But not creative.

But not big picture, so maybe big picture, maybe detail-focused, maybe reliable, maybe creative. They are all different qualities.

Can I ask you … Sorry to interrupt. Who determines that?

We determine that by mutual … It’s shown in the TED talk, how that happens, so it would be easy to show the gadget that we have to do that, but each one, it’s a mutual voting in a sense of each other. Then, it comes through a process of the higher ones …

This is this app that you have …

It also comes through tests. Sometimes there are personality tests, if you’re faced with this, what does that happen. It is based on the decisions that you’re making over a period of time, so all those decisions are recorded. In the app …

Right, and assessed then.

By the computer, so think of it this way. If people were successful here in making a decision, and you said that they typically answered the questions this way, or that you produce the data … So imagine in school, if you had tests in which, rather than the professor assuming he’s got the right answer for the test, that what you did is you did all of the profile of the most knowledgeable, those who have had the most success and least success, and you had them all take the test, and you see who is most correlated with those who did the test, so you don’t have one professor deciding that this is the right answer, but because you have triangulation of a number of people who took the test. Maybe you might range from Nobel Prize winners to X, Y, Z, and you have that … You can get at, “Okay, who is better at making those …”

Then, you get scored on that, that attaches itself to you.

Right, and because the data is constantly being accumulated in that way, and the computer is going through that process, it will then bring that out. Then, you have conversations, you get in sync. Is it right, is it wrong? In other words, let’s say we’re assessing how you’re doing. Okay, here’s the evidence. It’s not a person making that classic wage, it’s one person, there’s this evidence.

Like a boss says, “I think you’re difficult.” Or, “I think your argument …”

Right, it doesn’t mean … Yeah, who gives a damn? Okay, somebody thinks that, somebody else thinks something else.

Right, right.

How do you get at what’s actually the case?

The actual truth.

How do you get at truth? Now, if you have a relationship in which we can all agree on the criteria by which we get at truth, then it’s not the boss just pronouncing you that way.

Right, which happens in workplaces, doesn’t it? To people who have a reputation, I guess, or they have an image.

The question is, I don’t think it’s bad if it’s right. In other words, it’s great if it’s right, because what happens is, in this discovery process, most … Generally speaking, it’s not like we’re going to … If the person themselves doesn’t believe it’s right based on looking at the evidence, we assume it may not be right until at … but then, there’s a body of evidence that builds up of showing people’s strength and weaknesses, and that’s something that’s built on. So many people are so defensive.

Yes, that’s what I … Yeah, that’s my next question.

Well, that’s why it’s so important to understand essentially that that’s the greatest problem, one of the greatest problems you have, because if you can just get past that and know what your strengths and weaknesses really are, and deal with them effectively, you can be super effective.

Absolutely.

If the person comes into a place like that, people come in because they want to do this. I’m not saying it’s easy, but they come in because they say, “I want to do that. I want to do that. I want to know what my strengths and my weaknesses are.”

You want a workforce that is willing to … I just remember a visit I had Zappos, you’ve seen their principles. They are very strict in how they bring people in. Then, they pop people out who are not willing to be part of the way they’re managing there. They have a whole bunch of various principles, but they don’t want anyone in it that doesn’t accept it.

Ours is basically an idea meritocracy, right? Whatever the evidence is, if you want to have that self-discovery …

Right or not.

Right.

Or not. Is that hard to change?

It’s the opposite of a culture. A culture is like somebody is going … Excuse me, a cult, the people who follow one doctrine.

Right.

No, no, this is the opposite. We like independent thinking. We like the differences in agreement, we just have to manage them all.

How do people then change within that structure? What if they actually change or … It then becomes reflected, then it becomes reflective.

It’s much easier to change in that structure than a traditional structure, because if you’re having this evidence and you’re looking at … Think of it like biofeedback. If you were having biofeedback, what’s your calorie counting, you lose your energy, and whatever it is …

Right, this is … Yeah, you have …

Whatever it is, and you’re constantly looking at that, and …

Then you could adjust it.

Then, you have a culture that is encouraging that. If you want to get fit, you have the biofeedback and you go to, I don’t know, a fit camp. If you’re in the people who want to do this way, then, you’re going to get fit.

Or, to change …

If you don’t, if you’re blind to it, you’re not going to get fit, right?

Do you imagine people are a certain way, and then can’t … With weight, you can stop eating. You can do lots of things to shift. But there are certain types of people that are in a workplace. Is that changeable?

It’s been such an interesting subject to me, because I’ve spent time with neuroscientists and psychologists and so on, and what we find out, and I think this is just the fact, it depends on … Generally speaking, it’s like the body. Meaning, there’s a certain structure that you have. You’re either born, I don’t know, big-boned and tall and strong, or whatever, you have the physiological thing. Then, there are parts of it that can change, and usually, it can change on average, within something like one standard deviation of a population. In other words, there’s an ability to create some element of change. You can have some significant change, but if you’re not, one way as much …

Yes, if you’re not athletic, you’re just not going to be. I will not be playing basketball.

Right, neither will I.

Yeah.

The thing about it though, that you have to get is it doesn’t matter, and the reason it doesn’t matter is when you start to understand that you don’t have to be good at everything, that you have to know what you’re not good at and work well with people who are good at what you are. That’s why the collective decision-making is so much more powerful than the individual decision-making. If you do that, well, it’s not a problem. You can get to your goal. The key problem of mankind is that people have stuck in their heads these opinions or their … it has to come from them thing, really, and where they can get past it if they can embrace the fact …

Opinions about themselves, more than anything.

Yeah, or even opinions about things, opinions about themselves, opinions how to do these things. In other words, all I’m saying is, you just have to come up with the best opinions but they’re probably not in your head. You just have to come up with the best …

Does it help that you’re saying the computer says it too, because I think if you did among … that you need this data that shows successes and decision-making, does it help convince people?

It does help. It does help. When we say convince people …

Oh, I can imagine resistance.

They have partners.

Right, right.

The struggle of people is between their two yous, I call it, okay? There’s the intellectual thoughtful prefrontal cortex you, that when you say, “Would you like to know your weaknesses? Would you like to know what I think? Would you like to say what you think?” You get yes, yes, yes. Everybody agrees.

Then there’s the emotional you, the subliminal, emotional you, that’s the amygdala, that is that emotional thing, that becomes a difficulty. When people realize that everyone has their two yous, that one is struggling with the other, then it helps them through it, because they say, “What is going on here?”

If we’re just gathering the evidence and we’re looking at that, I can understand that my emotional me is standing in the way of looking at that evidence. They have to understand, there’s two thems in there, and that real struggle. When you say, how do we approach it in an evidence-based way, and are we doing that, and have that triangulation? It helps them.

This isn’t for everyone, by the way. People come, about third of the population, it doesn’t work out for them the first 18 months or so, and then you get to the point where … but other people can’t work anywhere else, because they love the idea meritocracy, they can’t go back to the politics, and so on. That’s the struggle, the struggle that people have is between their two yous.

Between the two yous, the emotional and the intellectual, I guess.

That’s right.

When we get back, I want to talk a little bit about the modern workplace and how we change it, because I think there’s a lot of discussion about how we create innovation, how we come up with innovation, and how we get to the new work environment, which I think everyone feels like there is one coming. It has a lot to do with automation, with AI, with robotics, and all kinds of things.

We’re here with Ray Dalio, and we’re going to talk about that and more. He’s the author of the book “Principles: Life and Work.” At the end, he’s going to give us the key principles, I think, if he wants to think about it.

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We’re here with Ray Dalio. He’s the chairman of hedge fund Bridgewater Associates, which he co-founded in 1975, but he’s also the author of “Principles: Life and Work,” which seems like, kind of a bible of management. I don’t know how else to think about it, or instruction book, how do you think of that?

Bible and instruction book.

There’s been a lot of these, let me just say.

Yeah, let me say it. It’s so much the, that’s like followed instruction. This is a thing for independent thinkers.

All right, okay.

Okay? These are a bunch of principles that I had written down …

That you’ve gotten over the years.

That what happens is, I like them stress-tested. As a matter of fact, I’m going to be putting together an app, we have an app.

It’s called the Dot app? Is that right?

Well, it’s a different one.

Okay.

We have a bunch of them.

All right, okay.

It’s called, the one I’m referring to is called The Coach. What it does is it takes …

There was a guy here in Silicon Valley called The Coach, remember Bill Campbell? Did you ever meet him?

Okay, no, I don’t.

Everybody hired him to be the coach, but go ahead. He was a person, not an app.

Okay, so let’s take that, and let’s imagine Bill wrote down, “When you encounter this situation, here’s my suggested recipe for that,” that would be the principles, right?

Sure.

Then, this will be to bring together other people like Bill and other fabulously successful idea people to put in principles, so you could look them up whenever something of a certain type comes up, it says …

“Here’s how Reed Hastings handles it. Here’s how Bill Gates handles it.”

Exactly. Here would be his helpful principles, and then you write in your own principles.

Oh, I see. You’re crowdsourcing principles.

Yes, and writing in your own principles. Then, when something comes along, don’t just jump to handling it, and you reflect and you think, “How can I do that?” The important thing is that you make the decisions yourself, that you don’t follow instructions.

You’re asking me about what the most important principle is, in a sense. One of the most important principles is …

Is don’t follow the principles.

Is to think for yourself, recognizing that you don’t have anywhere near enough knowledge in your head to make those decisions well, and so to be radically open-minded to take those in and weigh those decisions well. That’s the key to life. Only you know what you’re going after. Only you know how to get that, but you have to do that with radical open-mindedness.

At the same, you are trying to standardize them in a way, too, at the same time that it can’t … because one of the things, I think there’s … First of all, there’s a million management books out there, and they all have a very different take on how to best be successful, and not just that, how to create innovation. That’s the biggest topic here, is how do you continually keep a corporation innovative? I think you’re talking about innovation here, the idea of being fresh decision-making.

Yes, well, look, I’m saying, I did this for 40 years, I went from nothing to here.

Right.

This is just what it is.

It worked for me.

You take it or leave it.

I get that. I get that.

Just be like … I don’t know if Steve Jobs went … He wrote down his thing, or Bill Gates, or X, Y, Z, or Harry Schultz, X, Y, Z. This is just what those things were.

I get that.

If everybody does that, that’s cool.

You want to have an app called The Coach. Well, talk about your app in the company, what you guys use.

Well, we have a number of them, but I think you’re referring to the Dot Collector, which is what was shown in that TED talk.

Yes.

It’s an iPad app. In the iPad, everybody brings in the room the iPad, and it captures what everybody’s thinking about people and things as the meeting is going on and it lights all of that up. When you look down on the screen, it comes in colors, like if something’s … If you think somebody is doing a really good job, it’s in bright green. If you think somebody is doing a bad job, it’s in red.

Real time?

Real time, it’s as this thing is happening, and so you start to see that. Something lights up, so you’re seeing what everybody is thinking. You tap on it, and you could see what anyone is thinking at that particular time about each other in there.

As long as they’re being honest, yeah.

Yeah, in that process. Then, what it does, so it does a lot more than I’m just describing, but what it means is that it highlights different people’s ways of thinking. It transforms their way of thinking, because they see that they’re just one of those squares looking at others, and that everybody is seeing it differently. They ask their selves, “How do I know I’m right?”

The big transition, the big transition to make is going from a mindset in which you say, “I’m right,” to asking yourself, “How do I know I’m right?” Because if people disagree, somebody must be wrong, and how do you know that wrong person isn’t you? So that by going above that, and you look at the screen, you say, “Wow, all these people are different things.”

Saying the same thing.

They’re all saying all those different things, and how do we sort out who’s right? That’s where then the algorithms and the process is, so you view that as a common question that we have to solve together, and you say, “How do we determine who was more believable and how that works?” It also, because it knows, because the computer knows all about what you’re like and so on.

Each person is like.

It deals with them individually in terms of giving interactions, so that as the meeting is progressing, and it’s saying, okay, he knows what not only everybody’s thinking, but what your inclinations are to see things one way or another, that comes through, and it gives coaching. Then, okay, in that situation you might be aware of this, blah, blah, blah, that kind of thing. Then, when a decision comes to be made, rather than just talking and so on, the question is, what should this decision be? Then, everybody gives that, and their decisions on what that is, and there’s believability weighted decision-making, so that you can look at that …

Based on each person.

Okay, based on each person’s believability and the weight, we talked about that a minute ago.

Certain people get more weight than others?

It’ll show both. It shows equal weights and it shows believability-adjusted weights, so that you can look at those two things, because I find … Look, I started the company, and I think, if I’m in a situation in which I have a belief, and those other believable people, that there are those number of believable people who disagree with me, there’s a good chance I’m wrong. I don’t want to just go on. Creating that translation, I would rather defer to the other person.

If I will struggle to make sense, will go the back and forth, I’ll try to understand why, but it’s like you and the doctor example I gave, if you’re not well, and you say, “I have to be the one who makes my decision.” Well, I’d rather have the three doctors agree on my path than for me to follow that path, and that will be the path that I’ll go down. By being able to do that, that’s great. It will also collect the data on your decision-making.

Once you’ve made it.

Once you’ve made it, and to … and it pops up a little screen, and it says, “People who made that decision in this group tend to have the following characteristics, tend to have the following strengths and weaknesses.” In other words, if you take a group of people, let’s think about that group, and you say, let’s imagine there’s 20 people in a room, and you were to say, “Those that are rated highest on this thing made this decision. Those who rated lowest on that thing, made that decisions. Here are the quality that would be behind it.”

Maybe it’s creativity. Like, for example, a lot of people pay a lot of attention … Some people have more imagination than others. Some people, that’s not … There’s a correspondingly good quality to somebody who might have … that are more reliable, but they may not have as much imagination. If you’re having a decision, and you’re looking at that, and you can start to say, “Oh, I see that.” Because there’s communication and that helps move you toward the idea meritocratic decision-making. You get the idea.

Right. What you’re talking about, though, it’s so appealing to people in technology — and again, I’m focusing on technology — but a lot of them seem to be in this myth of, innovation is an idea popping into your head, that it’s “Larry and Sergey were sitting in a room and thought about this,” or Mark Zuckerberg. All the stories, the narratives are not about that.

Well, I do believe it’s popping in your head a lot.

No, but I’m saying, but it’s something that’s ingrained into the concept of where innovation comes from, and a lot of technology people, once they get to somewhere successful, they worry about keeping innovation alive, and keeping a staff that is not political, bureaucratic and slow.

I share those worries. I think those are good, valid worries, and I also think that a lot of innovation comes from innovative people and it’s subliminal. I meditate, that’s how to … that’s been beneficial, because ideas sometimes are not just a conscious engineering, that the subconscious, the subliminal mind, is where a lot of creativity, imagination, intuition, those things are very valid.

Then, when you take those things and you then bring them to the surface and match them with logic so that you triangulate that, okay, those subliminal ideas, then, triangulate with logic, then, you’re probably good to go, and that’s the most successful process.

That’s the idea.

That’s the process, right, but not everybody does that equally well, for whatever their reasons are, and so that’s true. Then the question is, how do you do that in an idea meritocratic way? Okay, you do that by knowing what people are good at and bad, and you tried, and everybody works together, because a lot of people who may think one way don’t really understand what it’s like to think the other way.

They get very frustrated with the other person. They think the other person is wrong. The person who’s paying a lot of attention to the detail, by way of example, thinks that you’re not paying … that imaginative person is not paying attention to the detail, they’re skipping over the important things, their head is in the clouds. The other person is saying, “Get with it. Can’t you imagine this and that?” They’re at odds. When they understand each other and how they think differently, there’s a greater appreciation for those types of ways of thinking, and a greater working together.

Does it seem, though, in the workplace that doesn’t … it doesn’t actually happen that way. Usually, someone does something that’s successful, and then they keep doing it that way. They keep moving in the same direction.

I don’t think most innovators are going to do that because …

Well, I’m thinking of something I’ve covered recently. Uber, very … a certain way of getting somewhere, it’s not working anymore, and they’ve brought in someone who’s very different.

Well, then that’s not a really innovative person. First of all, a lot of this comes within the person, and what is the nature of the person. We put labels on companies, but the reality is, it’s the people. Forget the labels. You can’t say, “Uber is a …”

Or any of the companies, they’ve done it in a certain way, and …

I’m saying, forget the companies. It’s the people that matter. We call this thing company, and they say, “Okay, the company does something.”

Yeah.

The reality is, how the people who are making the decisions behave. I’m saying that, just following through on that point, a really innovative person just loves innovating. They don’t like, they get bored with it, in other words … I know myself and the people I enjoy being around with, something like, “Okay, get the idea. Get it going, and make it happen, and so on.”

Going from visualization to actualization, there’s a section in the book on shapers. We’d had personality tests, and so on, taken by … I did. I asked them, Elon Musk and Bill Gates and a number of … Reed Hastings, and a number of those people, and deal with the question of, what is the shaper’s mentality? There’s a section in the book on what do they go after? You deal with the personality test and so on, and by and large, it is this … What is a shaper? A shaper is somebody who can take something from visualization to actualization, and build it up.

Right, which is a problem of a lot of people, they can’t do that.

Well, but you can do it collectively. All of those people, they have the audacious goals, and they have great imagination, and that’s important, but the one thing that you see about them pervasively is that there’s this full range, and it may not be just within themselves, the attention to the big picture and the attention to the detail. In many cases, it’s within them, themselves, that they can go full range.

I’m thinking Reed Hastings probably fit that.

Okay, yeah.

He’s full range.

You go full range, but also, you see … but Reed …

He has a team.

He has Ted [Sarandos], and if you speak to Reed about that, he knows what Ted is good at and he says, “That’s not my thing.” They know how to work together. The key is to also pick the talent in other people, and when they’re strong where you’re weak, to make sure that you as a team go full range, and you have that appreciation.

Absolutely.

That’s basically what it’s like. There are many of those things. I won’t rattle off all the qualities, but they have patterns in those cases. One of the things is that when you have the visualization, and you compare it with the reality, there’s a gap. When you can see that gap, that gap is painful, almost. It’s such a pleasure to fill that gap, and then when you fill the gap, you want to go on to the next gap, because you keep seeing those gaps. As long as you see those gaps, that’s what it’s about. Nobody, that I know who’s really creative likes to do the same things over and over again.

Right. Let’s finish up talking about cohesion, because it’s something I think about a lot, with a lot of companies that I cover, at least. You can iterate this to banking, or Hollywood, or wherever. I’ve noticed that a lot of what you’re talking about is cohesion. Whether you like each other or not, there’s a cohesion amongst a group of people, and every successful company I’ve seen is cohesive. They may not like each other, they may not get along, they may personally dislike each other, but there’s a certain level of cohesion among the group. They’re not doing it to this extent, this much discovery of each other, which is interesting — the idea that you could standardize it and make it almost into an app is really interesting, the concept of what they’re already doing naturally.

How do you create a workforce that understands how to do this? Because that’s not how it’s been done in this country or in many places. How do you get people thinking, in the modern workplace, especially with incursions from robotics and automation and the changing job force?

Well, a lot of that stuff, robotics enhances these things. I think it’s like playing great jazz together.

You mentioned that in the book, yeah.

Yeah. The key is, you play together and you do that radically transparently, and you see what is painful, and you see what’s good. Then, you look at what’s painful and you look at what’s good, you talk about it, and so on, and that’s the key, I think, to a good relationship, right, and without being tough with each other.

In other words, being in high standards. You only want to … You want to be great together, but you can’t be afraid of talking about, like, “You’re off-key,” and that kind of thing. It’s like a great team, you have to be … When you get that great team thing going, so that you’re transparent, and you …

If you had a team and somebody’s not doing their job, or whatever in that feedback loop, you have to keep moving on, and so it’s that being among that elite and excited about that, but being like a great jazz group together, when they have all those musicians and they know how to work together. It’s a magical thing. I think you have to do it, have the emotions, and be in sync. There’s big principles about, “How do you get in sync?”

Right.

That’s with the radical transparency, you know after a while whether you’re playing great jazz or not together.

Right, right. Absolutely. Do you imagine our workforce is ready for thinking like this? Like thinking in this way and changes, because it has been a top-down, it’s mostly … It’s not democratic, it’s mostly autocratic, a lot of companies. Again, this single … It’s like a Jesus-like figure.

I’ll never forget Steve Jobs once said to me, he got a lot of the attention because he was Steve Jobs. Someone was saying something to him, I think he said something like, “It’s not like they’re all Oompa Loompas in the back making my ideas. They’re all contributing to it.” He created that myth, and at the same time disdained the myth, that there was a great team behind him, a group of people. Do you imagine our workforce is ready to understand that, or do we like the autocratic?

I think it’s almost a bad subliminal thing, this heroic thing. It’s a load of bullshit.

People love it, though.

Yeah, but that’s what they like, the saga, they like the story.

The struggle, yeah.

They like those things, okay? Let’s be clear. First of all, it’s not going to work. That doesn’t mean great independent thinkers are not going to have an important thing. Oh my God, a limited number of people have changed the world, but if you put together a team of great independent thinkers, and a great idea meritocracy, its evolution will mean that it will drive it in this direction. We know what works works, and at the end of the day, this type of approach, of being able to have that kind of triangulation at the best, and then that idea meritocracy is going to have a pull. I think the natural force is there.

If you’re looking at what we can collect in data now, so we can make those distinctions, so that we could be evidence-based, and I think that there’s a desire. We’re in a crowdsourcing environment. People like it. They understand the value of it. This is what this is about. I think this approach is for this time.

For this time. I’m going to put you on the spot. Our presidency is not like that right now. We’ve elected an autocratic personality, obviously. Is that the last gasp of that or is it … because nothing’s getting done, like, nothing is getting passed.

Yeah, I’m not going to get into the politics. If you’re asking me to opine on the …

I’m saying, people like that.

Yeah, but here’s what it really is like. If the president could make his principles clear and known, and if you could have an idea meritocracy, principles that bind us together as a country, what are our principles? We have to articulate that and be clear about what is being … because the biggest risk to me is the fragmentation.

Right, exactly. That’s what I want to get at. I don’t want to necessarily talk about what the president is doing, but the political process seems very broken right now.

We have a political process, but even more importantly, we have this fragmentation that’s due to a number of thing. There’s a wealth fragmentation and there are two economies. We talk of the economy, recognize that you can’t talk of the economy about the economy, that there were two economies, that the … Let’s call it the top 40 percent and the bottom 60 percent. If you look at the economy of the bottom 60 percent, it is a miserable economy. Not only hasn’t it had growth and economic movements and so on, it has the highest rising death rates.

It’s the only place in the world where death rates are rising because of a combination of opiates, other drugs and suicides. The top one-tenth of 1 percent of the population has a net worth that is equal to the bottom 90 percent combined. We have existence. There’s two parallel existences that are taking place and we have that kind of split. If you’re the president of the United States …

Or the Congress.

Yeah, or whatever, you have to think about, okay, the country as a whole. Okay, this is an issue, that’s an economic issue. What we’re having … I think Donald Trump’s election is a manifestation that somebody else would have gotten elected, or at some point, on that bottom 60 percent, it’s a populism of sorts.

Study populism in history. If you go back in terms of the ’30s, or periods of time, we’re in a position that’s very similar to 1937 in a lot of ways, not just politically, economically, for a variety of different ways. Everything that’s happened has happened before.

Absolutely, I get that.

It’s that pattern. I’m saying, now, if you could have thoughtful disagreement …

Right, that’s why I want to apply your book’s principles to this, because it seems like that’s precisely what’s not happening.

What he could do, and I’m not … What one could do is first, have thoughts put on the table, clearly. If I was taking the people around him, that would be a good way to do it. I’m not saying he’s not doing it, I’m just commenting on what’s good. Second is, then, to know the art of thoughtful disagreement, okay? How we, together, however that’s extended, I would say, bipartisan, we have to work together but … to find out how you have thoughtful disagreement, and then have idea meritocratic ways of getting past that disagreement, that keeps us together, rather than at each other’s throats, because I do believe that this split in the country is the greatest problem of our time.

Not just economically, socially, politically, and that it’s going to worsen, because technology is a fantastic way of raising productivity by also reducing the need for people in a lot of ways. People are going to, by and large, either know how to code or be increasingly unemployed because they were being replaced by the product of that.

We have to deal with it, that issue, so collectively. I think if you understand the important principles, you understand a quality collective decision-making, idea meritocratic decision-making, it would be great for our country, and it would lead to better decisions and greater cohesiveness.

Well, let’s hope. It works for companies, but let’s see if it works for the group as large … because it’s really an interesting time, and there’s so many … much innovation in how we run corporations and companies, and so little in how we run our society, which is interesting, which is an interesting thing. When are your books coming out on investing in the economy?

Probably not for 18 months or two years.

Ray, lastly, if you had to pick one of the things that’s most critical to begin this process — I get that all the parts are very important, the disagreement, the knowing yourself, the algorithmic, the data around it, the data around this issue, and I assume there’s also data around whether decisions were successful, too, which also plays into whether the decision is successful. Which is the most important part, do you imagine, of the process?

Well, I would say there are five things you need to do in order to be successful.

First, you have to have your audacious goals.

Second, as you go to those, you’re going to encounter your failures, your mistakes. You have to identify those and not tolerate them.

Third, you have to get the diagnosis to the root cause of them, which could be that you have a weakness, or everybody has a weakness.

Fourth, once you have that, you have to design what you’re going to do about it to get around it.

Fifth, then, you have to push through to results.

If you keep doing that over and over again, you will inevitably succeed. Let me say, in order to have a successful life, the only thing you need to do is have great dreams. Then, embrace reality, and know how to deal with it well. Then, have determination, because if you have those things, you have your dreams, and then you encounter your realities and you learn, and you do it over and over again, because you have determination, you’ll inevitably succeed. Just recognize it’s not all in your head. Be radically open-minded and recognize that you don’t have to have everything in order to succeed.

Well, I appreciate that. That’s a good message for the many egomaniacs at Silicon Valley who do think it’s the case. In any case, this is a really fascinating talk. I’m talking with Ray Dalio, he runs a multi-billion dollar hedge fund on the side, but it seems like he’s the author of “Principles: Life and Work,” which the New York Times describes as part memoir and part how-to guide, where he shares the lessons and processes that have guided him throughout his career. Ray, it was great talking to you. Thanks for coming to the show.

I appreciate it. Thank you.


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Ethereum’s Co-Founder Just Unveiled His Plan for the Future of Cryptocurrency

Solving the Scalability Problem

When it comes to hosting secure transactions, blockchain continues to be an attractive option for a number of industries. Arguably, the top blockchain option for enterprise and app use is Ethereum — and its co-founder Vitalik Buterin, wants to keep it that way. At Devcon3, Ethereum Foundation’s third developer’s conference in Cancún, Mexico, Buterin presented what he called a “modest proposal” for the future of the Ethereum blockchain and cryptocurrency.

On Thursday, Buterin discussed a three to four year long-term plan for Ethereum. The roadmap primarily covers technical improvements and changes designed to facilitate scalability, i.e. Ethereum’s capacity to handle transactions. “The amount of activity on the blockchain is orders of magnitude larger than it was just a couple of years ago,” 23-year old Buterin told the audience, as reported by Coindesk. The daily transaction rate on the Ethereum network has gone up to more than 20,000 nodes.

To keep up with and to continue this growth, Buterin’s priority is to come up with solutions that mitigate the cost of expanding storage as the system continues to hold more transactions. “Scalability is probably problem number one […] There’s a graveyard of systems that claim to solve the scalability problem but don’t,” he pointed out. “It’s a very significant and hard challenge. These are just known facts.”

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Encouraging Ethereum’s Growth

For Buterin, the most probable solution is a technical improvement he calls “sharding” or the partitioning of data into subsets, where each node would only have to store a small part of the entire Ethereum network. The idea has been around for a while now, and it looks good in theory. Each node is able to, supposedly, rely on other nodes for data to keep the entire system accountable — despite being kept in subsets.

For sharding to work and keep the network secure by preventing nodes form sending false information to other nodes, Buterin proposed a new sharding infrastructure that’s different from other ideas developers have been considering. The new proposal involves partitioning Ethereum into different types of shards, where the main shard would be the current Ethereum network, and other shards (which Buterin called other “universes”) would hold other transactions.

“Other universes where all this stuff we’ve been working on these last few years can be rolled out much much faster,” Buterin said, according to Coindesk. This means changes can be easily implemented on these other shards, while keeping the main Ethereum network secure and intact. Difficulties in scaling were a contributing cause of Bitcoin’s recent blockchain troubles, meaning solving the scalability problem is of the essence for other cryptocurrencies in the market who want to avoid a similar fate.

Apart from sharding, Buterin also presented a number of other improvements as part of Ethereum’s new roadmap. There would be upgrades to the ethereum virtual machine (EVM), which is the technology that compiles smart contracts. Then there’s project eWASM, which would allow for running Ethereum on a web browser, as well as plans to help clients sync more quickly to the network. Details on each of these, including the research behind each, are available in Ethereum’s Github page.

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