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Jack Ma’s Keys to Success

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It takes a rare person to accumulate a total net worth over $40 billion through a devoted work ethic while maintaining a sense of perspective. Jack Ma is one of those people. The founder and CEO of Alibaba, one of the world’s leading e-commerce web portals, is one of the world’s richest men, but he has not let success cloud his vision for the future or his acknowledgement of where he came from. Jack Ma’s keys to success are true and inspiring for everyone from aspiring billionaires to owners of the smallest businesses.
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1. He Values Attitude
When Jack Ma talks about the biggest mistake he ever made he describes how when he founded Alibaba he told his team that the highest level they could achieve would be that of managers, and that executives should be hired from the outside. Ma has learned his lesson and now stresses the importance of attitude and passion over theoretical skills.
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2. He Unites People under a Single Goal
Ma understands that no matter how hard you try you will never be able to convince every single employee, business partner, and potential investor to trust you or believe what you say. Accepting that and changing your approach is another key to his massive success. Rather than uniting his company under the vision of one person, he unites them under a common goal. The vision is more important than the leader.
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3. He has Foresight
Jack Ma believes that a good leader should have foresight. He should try to stay one step ahead of the competition and anticipate how decisions will play out ahead of other people. Taking time to develop creative thinking skills and following informed intuition is a hallmark of any great business leader.
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4. He Hires People with Superior Skills
When asked what separates a leader from an employee Ma has gone on record saying “Your employee should have superior technical skills than you. If he doesn’t, it means you have hired the wrong person.” Focusing on the skills of employees and hiring people with the know how to carry out your vision is an important pillar of any great company.
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5. He is Tenacious
In addition to foresight Ma says leaders should be tenacious and have a clear vision. Knowing what you want to achieve and having the drive to chase it down will not only put you on the path to success, it will inspire those around you to work hard for that common goal. Taking pride in your work and not taking no for an answer are keys to Ma’s business philosophy.
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6. He Defines Failure as Giving Up
According to Ma, “giving up is the greatest failure.” If you go out, try your best and fail to achieve your goal but see it through to the end you are a success. Like all great leaders, Ma recognizes that a person is able to learn the most from obstacles and hardships. They key to success is persevering and learning from your mistakes.
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7. He Loves Life
“I always tell myself that we are born here not to work, but to enjoy life. We are here to make things better for one another, and not to work. If you are spending your whole life working, you will certainly regret it.” This sentiment lies at the heart of Jack Ma’s lifestyle. Life is for experiencing the world and helping out other people. If money is your goal, you have to change your mindset.
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8. He Doesn’t Make Enemies
One the most unique aspects of Jack Ma’s business philosophy is the idea of friendly competition. Ma does not see his competitors as his enemies, rather they are friends whom he can learn from and who challenge him to achieve his full potential.
It is clear that Jack Ma’s philosophy is built for success in a rapidly developing world. We can all learn a thing or two from this self-made billionaire.
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About the Author
This article was produced by Norms Man of Dramadunia.

Startups

The Most Important Tech Job that Doesn’t Exist

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Yesterday I asked a prominent VC a question:

“Why is it that, despite the fact that so many successful startup ideas come from academic research, on the investment side there doesn’t seem to be anyone vetting companies on the basis of whether or not what they’re doing is consistent with the relevant research and best practices from academia?”

His response was that, unlike with startups in other sectors (e.g. biotech, cleantech, etc.), most tech startups don’t come out of academia, but rather are created to fill an unmet need in the marketplace. And that neither he nor many of his colleagues spent much time talking with academics for this reason.

This seems to be the standard thinking across the industry right now. But despite having nothing but respect for this investor, I think the party line here is unequivocally wrong.

Let’s start with the notion that most tech startups don’t come out of academia. While this may be true if you consider only the one-sentence pitch, once you look at the actual design and implementation choices these startups are making there is typically quite a lot to work with.

For example, there is a startup I recently looked at that works to match mentors with mentees. Though one might not be aware of it, there is actually a wealth of research into best practices:

  • What factors should be used when matching mentors with mentees?
  • How should the relationship between the mentor and mentee be structured?
  • What kind of training, if any, should be given to the participants?

That’s not to say that a startup that’s doing something outside the research, or even contraindicated by the research, is in any way suspect. But it does raise some questions: Does the startup have a good reason for what they’re doing? Are they aware of the relevant research? Is there something they know that we don’t?

If the entrepreneurs have good answers to these questions then it’s all the more reason to take them seriously. But if they don’t then this should raise a few red flags. And it’s not only niche startups in wonky areas where this is an issue.

For example, I rarely post to Facebook anymore, but people who follow me can still get a good idea of what I’m up to. Why? Because Facebook leverages the idea of behavioral residue to figure out what I’m doing (and let my friends know) without me having to explicitly post updates. It does this by using both interior behavioral residue, e.g. what I’m reading and clicking on within the site, and exterior behavioral residue, e.g. photos of me taken outside of Facebook.

To understand why leveraging behavioral residue is so important for social networks, consider that of people who visit the typical website only about 10% will make an account. Of those about 10% will make at least one content contribution, and of those about 10% will become core contributors. So if you consider your typical user with a couple hundred friends, this translates into seeing content from only a tiny handful of other people on a regular basis.

In contrast with Facebook, one of the reason why FourSquare has yet to succeed is due to significant problems with their initial design decisions:

  • The only content on the site comes from users who manually check into locations and post updates. This means that of my 150 or so friends, I’m only seeing what one or two of them are actually doing, so what’s the value?
  • The heavy use of extrinsic motivation (e.g. badges) has been shown time and again that extrinsic motivation undermines intrinsic motivation.

The latter especially is a good example of why investing on traction alone is problematic: many startups that leverage extrinsic rewards are able to get a good amount of initial traction, but almost none of them are able to retain users or cross the chasm into the mainstream. Why isn’t it anyone’s job to know this, even though the research is readily available for any who wants to read it? And why is it so hard to go to any major startup event without seeing VCs showering money on these sorts of startups that are so contraindicated by the research that they have almost no realistic chance of succeeding?

This same critique of investors applies equally to the startups themselves. You probably wouldn’t hire an attorney who wasn’t willing to familiarize himself with the relevant case law before going to court. So why is it that the vast majority of people hired as community managers and growth marketers have never read Robert Kraut? And the vast majority of people hired to create mobile apps have never heard of Mizuko Ito?

A lot of people associate the word design with fonts, colors, and graphics, but what the word actually means is fate — in the most existential sense of the word. That is, good design literally makes it inevitable that the user will take certain actions and have certain subjective experiences. While good UX and graphic design are essential, they’re only valuable to the extent that the person doing them knows how to create an authentic connection with the users and elicit specific emotional and social outcomes. So why are we hiring designers mainly on their Photoshop skills and maybe knowing a few tricks for optimizing conversions on landing pages? What a waste.

Of all the social sciences, the following seem to be disproportionately valuable in terms of creating and evaluating startups:

  • Psychology / Social Psychology
  • Internet Psychology / Computer Mediated Communication
  • Cognitive Development / Early Childhood Education
  • Organizational Behavior
  • Sociology
  • Education Research
  • Behavioral Economics

And yet not only is no one hiring for this, but having expertise in these areas likely won’t even get you so much as a nominal bonus. I realize that traction and team will always be the two biggest factors in determining which startups get funded, but have we really become so myopic as to place zero value on knowing whether or not a startup is congruent or contraindicated by the last 80+ years of research?

So should you invest in (or work for) the startup that sends text messages to people reminding them to take their medicine? How about the one that lets you hire temp laborers using cell phones? Or the app for club owners that purports to increase the amount of money spent on drinks? In each of these cases there is a wealth of relevant literature that can be used to help figure out whether or not the founders have done their homework and how likely they are to succeed. And it seems like if you don’t have someone whose willing to invest a few hours to read the literature then you’re playing with a significant handicap.

Investors often wait months before investing in order to let a little more information surface, during which time the valuation can (and often does) increase by literally millions. Given that the cost of doing the extra research for each deal would be nominal in the grand scheme of things, and given the fact that this research can benefit not only the investors but also the portfolio companies themselves, does it really make sense to be so confident that there’s nothing of value here?

What makes the web special is that it’s not just a technology or a place, but a set of values. That’s what we were all originally so excited about. But as startups become more and more prosaic, these values are largely becoming lost. As Howard Rheingold once said, “The ‘killer app’ of tomorrow won’t be software or hardware devices, but the social practices they make possible.” You can’t step in the same river twice, but I think there’s something to be said for startups that make possible truly novel and valuable social practices, and for creating a larger ecosystem that enables them.

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This article was written by Alex Krupp. see more.

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Entrepreneurship

How Google’s AI Mastered All Chess Knowledge in Just 4 Hours

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Chess isn’t an easy game, by human standards. But for an artificial intelligence powered by a formidable, almost alien mindset, the trivial diversion can be mastered in a few spare hours.

In a new paper, Google researchers detail how their latest AI evolution, AlphaZero, developed “superhuman performance” in chess, taking just four hours to learn the rules before obliterating the world champion chess program, Stockfish.

In other words, all of humanity’s chess knowledge – and beyond – was absorbed and surpassed by an AI in about as long as it takes to drive from New York City to Washington, DC.

After being programmed with only the rules of chess (no strategies), in just four hours AlphaZero had mastered the game to the extent it was able to best the highest-rated chess-playing program Stockfish.

In a series of 100 games against Stockfish, AlphaZero won 25 games while playing as white (with first mover advantage), and picked up three games playing as black. The rest of the contests were draws, with Stockfish recording no wins and AlphaZero no losses.

“We now know who our new overlord is,” said chess researcher David Kramaley, the CEO of chess science website Chessable.

“It will no doubt revolutionise the game, but think about how this could be applied outside chess. This algorithm could run cities, continents, universes.”

Developed by Google’s DeepMind AI lab, AlphaZero is a tweaked, more generic version of AlphaGo Zero, which specialises in playing the Chinese board game, Go.

DeepMind has been refining this AI for years, in the process besting a series of human champions who fell like dominoes before the indomitable, “Godlike” neural network.

That victory streak culminated in a startling success in October, in which a new fully autonomous version of the AI – which only learns by playing itself, never facing humans – bested all its former incarnations.

By contrast, AlphaGo Zero’s predecessors partly learned how to play the game by watching moves made by human players.

That effort was intended to assist the fledgling AI in learning strategy, but it seems it may have actually been a handicap, since AlphaGo Zero’s fully self-reliant learning proved devastatingly more effective in one-on-one competition.

“It’s like an alien civilisation inventing its own mathematics,” computer scientist Nick Hynes from MIT told Gizmodo in October.

“What we’re seeing here is a model free from human bias and presuppositions. It can learn whatever it determines is optimal, which may indeed be more nuanced that our own conceptions of the same.”

But things are moving so fast in this field that already the October accomplishment may have been outmoded.

In their new paper, the team outlines how the very latest AlphaZero AI takes the self-playing reliance – called reinforcement learning – and applies it with a much more generalised streak that gives it a broader focus to problem solving.

That broader focus means AlphaZero doesn’t just play chess. It also plays Shogi (aka Japanese chess) and Go too – and, perhaps unsurprisingly, it only took two and eight hours respectively to master those games as well.

For now, Google and DeepMind’s computer scientists aren’t commenting publicly on the new research, which hasn’t as yet been peer-reviewed.

But from what we can tell so far, this algorithm’s dizzying ascent to the pinnacle of artificial intelligence is far from over, and even chess grandmasters are bewildered by the spectacle before them.

“I always wondered how it would be if a superior species landed on Earth and showed us how they played chess,” grandmaster Peter Heine Nielsen told the BBC.

“Now I know.”

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This article was produced by Grendz. Grendz is the definitive place for new mind-blowing technology trends, science breakthroughs and green and positive ideas and news. Sign up is Free and special services are available. see more.

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