Steve Jobs, Crack Cocaine and Predicting the Future

  • A Ding in The Universe: One scene sticks out in my mind from the new Steve Jobs movie…
  • Driverless Cars and Crack Cocaine: At first, Google laughed at this innovation, and now they’re using it to beat the competition…
  • Alan Turing and the Talking Paper Clip: How a single simple theory has revolutionized the world…
  • How Kissinger Predicts the Future: Jim Rickards learned something very valuable from Henry Kissinger, revealed…

“Every time I see an adult on a bicycle, I no longer despair for the future of the human race.” -H.G. Wells


“I want to put a ding in the universe.”

I just saw the new Steve Jobs movie yesterday. (It’s much better, by the way, than the version with Ashton Kutcher.)

When I walked out of the theater, one scene stuck out in my mind.

Jobs and Apple CEO John Sculley were sitting across from one another in the restaurant of Jobs’ (unwitting) father.

STEVE JOBS: What if the computer was a beautiful object? Something you wanted to look at and have in your home. And what if instead of it being in the right hands, it was in everyone’s hands?

JOHN SCULLEY: We’d be talking about the most tectonic shift in the status quo since…

STEVE JOBS: … ever.

During that conversation, Steve called the computer a “bicycle for the mind.”

A human by itself, in terms of efficiency of locomotion, he explained, is a very inefficient creature. Embarrassingly so. But when you put a human on a bicycle it all of a sudden becomes the most efficient creature on Earth.

And just imagine, he said, what happens when you give the same to the mind.

Since that conversation, amazing, incredible and fantastic things have happened in the field of computer science.

But, despite his deification, they can’t all be attributed to Steve Jobs (not even a fraction, in fact). You have to go back a little further to suss out the source.

Most of them are due to innovative thinking giants with broad shoulders — the very same shoulders Steve Jobs tap-danced on.

In today’s episode, we’ll discuss one of these giants specifically.

Not just that, we’ll also show you the ways this man’s nearly 200-year-old idea has radically changed the world and is, currently, even outsmarting the NSA and transforming the way some average Americans invest.

Read on…


A fleet of driverless robotic cars whiz through the streets of northern California.

Since they first hit the pavement in 2011, they’ve driven hundreds of thousands of miles. Not once, though, have they struck a pedestrian, run a red light, or had to stop and ask a gas attendant for directions.

And here’s the most incredible part…

The car — microsecond to microsecond — must analyze mindbending amounts of data. Cameras, sensors, lasers and radars all work in unison to help the car navigate itself nearly flawlessly.

How is this possible? Well, it begins in the 1700s with an obscure English statistician who, apparently, looked like this…

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Take a wild guess…

After conducting a simple thought experiment with billiard balls, this man came up with a wild theory. One that, little to his knowledge, would change the entire world in ways he couldn’t have possibly imagined.

Stifled, vilified and even suppressed by its creator, this theory became one of the most controversial and marginalized ideas in history.


Over the span of 150 years this idea was defamed, denigrated, forgotten, revived for a moment, then disregarded and denounced.

 

In the end, though, it didn’t just survive… it thrived. And it’s a good thing it did.

For example, once set free, this idea single-handedly made the following things possible…

  • It became a game changer for the Allies in WWII and arguably saved the Allies from losing the war…
  • The Navy used it successfully to hunt down Soviet submarines and a missing H-bomb…
  • It saved the Bell Telephone System during the financial panic of 1907…
  • Seismologists used it to spot the epicenters of earthquakes for the first time…
  • Chicago researchers used to to verify the authorship of the Federalist Papers…
  • It allowed one prominent French mathematician to discover why there are more girls than boys born in the world…
  • And it helped to pave the way for modern electronic computers and software…

If you don’t already know what I’m talking about, it’s called the Bayes’ theorem.

And it was first stated by Reverend Thomas Bayes (pictured above).

Despite all that this theorem has given us though, it still, to this day, reeks of controversy.

For example, Google representative, according to author Sharon McGrayne, once called it “the crack cocaine of statistics… seductive, addictive and ultimately destructive.”

Even so, he later began recruiting Bayesians for Google.

And these specialists, using Bayes’ theorem as their mathematical dowsing rod, are responsible for getting Google’s aforementioned driverless cars on the road. (Let’s hope, therefore, the Google rep is wrong about Bayes’ theorem.)


“Today,”
 Sharon Bertsch McGrayne writes in her book, The Theory That Would Not Die, Bayesian spam filters whisk pornographic and fraudulent e-mail to our computers’ junk bins.

 

“When a ship sinks, the Coast Guard calls on Bayes and locates shipwrecked survivors who may have floated at sea for weeks. Scientists discover how genes are controlled and regulated. Bayes even wins Nobel Prizes. Online, Bayes’ rule trawls the web and sells songs and films. It has penetrated computer science, artificial intelligence, machine learning, Wall Street, astronomy and physics, Homeland Security, Microsoft, and Google.”

“It helps computers translate one language into another,” she goes on, “tearing down the world’s millennia-old Tower of Babel. It has become a metaphor for how our brains learn and function. Prominent Bayesians even advise government agencies on energy, education, and research.”


“It’s been incredibly important in the realm of computer science,” Jim Rickards chimes in.

“Alan Turing relied on it in his work to break German codes in World War II. According to Bill Gates, Microsoft software uses it to help anticipate what its users want. If you remember Microsoft Office’s ‘talking’ paper clip that would pop up offering to help you, that was Bayes’ theorem in action. It used certain cues to figure out what you were trying to accomplish.

“More recently,” Rickards reveals, “I’ve had success adapting this theorem for the financial markets.”

And not just hypothetical success, mind you. He’s even shown a small group of interested participants how to pull profits out of the markets using it.

In a relatively short amount of time, in fact, this group had the opportunity to see gains of 140%… 150%… and 162%. (Back-testing showed they could’ve seen gains as high as 1,616%.)

It works because it gives you three advantages over other investors. (You’ll see what these advantages are in a moment.)


Today, if you’re interested, Jim wants to reveal how the Kissinger Cross works.

First thing, “There are many ways to represent Bayes’ theorem,” says Rickards. “For instance, you may see it written like this:

LFT2

“Now, don’t worry,” Jim assures, “you’re not expected to memorize it or calculate it on your own. I just want you to know there is a solid mathematical foundation backing my analysis. To put it into English, the formula means:

LFT3
In short, instead of thinking in terms of cause to effect, you instead think in terms of effect to cause.

It sounds weird at first. But because you’re reversing your thinking process, you don’t need nearly as much data as you would otherwise to reach the same conclusion.

Contrary to the NSA’s method of pulling infinite piles of data together and trying to pick through to reach a conclusion, Bayes’ theorem works the other way around — with small amounts of data. And, surprisingly, it is, in many cases, more effective.

Don’t worry… it’s not as mind-bending as it seems right now.

“I’ll try to break that down as best I can.”

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Click here to see Jim’s full presentation… and see how it gives you THREE big advantages over other investors…

Until tomorrow,

Chris Campbell
Managing editor, Laissez Faire Today

P.S. Have something to say? Say it! Chris@lfb.org.

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