Capitalogix

Wealth Formula - Howard Getson and Buck Joffrey Talk The Future of Trading

I'm excited ... because I've been at Joe Polish's Genius Network Annual Event this weekend.

Genius Network is a business group that also serves as an advisory board, counselor's office, and idea factory. 

It brings brilliant minds and industry transformers together in a forum focused on innovation, creative disruption, and possibility. 

Peer groups, like this, help you set (and raise) standards. 

They help bring new capabilities, but also new possibilities, new found energies and a reconnection to your purpose, mission, and values. 

This is a great place to meet extraordinary people. 

Buck Joffrey is one of them. He is a doctor, an international best selling author, member of Genius Network, and host of WealthFormula (which is a podcast where he educates professionals on how to build lasting wealth). 

 

Buck recently interviewed me for WealthFormula.  We talked about old-world trading versus new-world trading ... and where I think A.I and Machine Learning have the best opportunities to add alpha and help investors make and keep more money.

You can listen to it below (or subscribe to his podcast on iTunes, Android, or RSS).

WFP-077-Howard_Getson

 

What Do You Buy Someone Who Has Everything?

I'm getting cynical, I understand planned obsolescence ... but has it occurred to you that Apple could make their phones act sluggish just before the launch of a new version?  

My phone has been driving me nuts.  So, (as I write this) I'm up at 2 am to place my order for the new iPhone X.

On one hand, it satisfies my desire for the new and shiny ... but, on the other hand, it makes it harder for my wife.

Buying gifts is often hard. But it gets harder when the giftee already has everything (or buys it himself).

That is where Neiman Marcus comes in.

Every year since 1959, Neiman Marcus has published a Christmas Book. Primarily comprised of normal Neiman Marcus offerings ... the book also contains pretty amazing "fantasy" gifts.  For example, who doesn't want a rose-gold Cobalt Valkyrie-X private plane (worth $1.5 million) ...

 

Neiman Marcus

 

I don't know about you, but it's a little feminine for me.

Or, there is a private Submarine (worth $20,000,000). 

 

Neiman Marcus

 

But that is only good if you don't have one already.

You can check out NM's 2017 Fantasy Gift List, here, and get a personal trip to Champagne, France or a pair of specially commissioned His and Hers Rolls Royces. 

Let me know if you have any good gift ideas.  I'm always looking for them.

The Next Gilded Age ... This Generation's Carnegies, Rockefellers and Vanderbilts

The world's super-rich hold the greatest concentration of wealth since the turn of the 20th century. 

According to The Guardian, there are now 1,542 billionaires in the world.  Meanwhile, last year, the collective wealth of billionaires increased almost a fifth – to six trillion dollars.  For context, that's more than almost every country's GDP... except the top 4 (China, United States, India, and Japan). 

The first Gilded Age was established by monopolies in US rail, oil, steel, and banking.

 

 

Income equality was extreme with the Vanderbilts being worth $185 billion due to his railroad empire, Andew Carnegie being worth $309 billion due to his steel empire, and John D. Rockefeller built an Oil empire (it controlled about 90% of the American oil business) that netted him $336 billion. 

It's interesting to look at the transition from the richest in the late 1800's to the richest in 2017 ... the transition from industries like Steel, Oil and Rail, into companies like Amazon, Microsoft and Walmart. 

While there are more "super-rich" today than before, our wealthiest individuals don't compare to before. Jeff Bezos is worth approximately $90 billion, Bill Gates is worth approximately $90 billion, and the Walton family has a combined net worth of about $149 billion. You can check out a full list of the top 10 richest people here.

Let me know when your name makes that list.  I'll do the same.

Ryan Deiss on AI and Its Intersection With Humanity

This is the golden age of Artificial Intelligence, machine learning, and process automation.  It is beginning to affect everything.

But, what it means is up for interpretation.  For example, one of the top digital marketers remains largely unfazed. Below is a video I did with Ryan Deiss, who has a different perspective on AI than I do.  

Check it out:

 

Ryan understands that marketing relies heavily on data-analytics and automation ... but he believes that it is also reliant on the personal touch.

Similarly, a friend and advisor sent me a link to a post where a fund manager made a similar argument about trading.

I agree that people are still a vital aspect of many businesses, and can't be fully replaced. However, I am dramatically more bullish on AI and its future and impact.

In many instances, today, what passes as AI is just an elegant use of brute force.

Nonetheless, AI is great at solving problems ... and is becoming increasingly able to digest and perform complex tasks (including tasks formerly thought of as done exclusively by humans). 

Ryan believes that the best AI makes a conversation more human (in regards to selling and retail) and allows humans to be more human.  In other words, as technology frees people up – they are free to spend their time on more valuable tasks and processes.

This has happened many times in society.  Fewer people work in farming or manufacturing ... and yet there are more people doing more jobs. 

So, obviously, in the same way that mechanization freed up workforces for better jobs, AI can do the same. 

Realize, however, that human perception is linear ... while technological growth is exponential.  Consequently, we probably do not know what AI will give (or take from) humans.

Only time will tell.

Meanwhile, some of the biggest companies are making big bets on R&D.

 

via Bloomberg

A reminder ... the best way to predict the future is to invent it.

Onwards!

How Much Debt Does Your Country Have Per Person? An Exercise in Understanding Large Numbers

Debt often enables governments to run smoothly. But sometimes you can have too much of a good thing.

The US recently passed $20 trillion in debt for the first time.  To put that in perspective, I am going to reference an article I wrote in 2011 ... when the debt was approaching $15 trillion. 

Here is what the $15 trillion U.S. debt looked like when it is piled up in stacks of $100 bills.

To put it in context, do you see the tiny tractor trailer?  Squint, and you can see the barely visible human in front of it. 

via WTFNOWAY

The United States has a net wealth of approximately $300 trillion.  Nonetheless, the statistics are sobering. 

Take a look at the list of country debt as a percentage of GDP.   Apparently, Japan has embraced its inner borrower. 

OECD via World Economic Forum 

According to the World Economic Forum, if the Japanese wanted to pay off their national debt, each individual would owe approximately $90,345. For comparison, US citizens would owe $61,539 a person. 

It's also worth noting that lower debt levels don't translate to safety on a global scale. Yugoslavia had very low government debt until its breakup. 

If you want to see an updated, interactive version of the U.S. Debt Clock, just click here.  It is worth spending a little time to watch the pace the numbers turn.

Here Are Some Links For Your Weekly Reading - October 15th, 2017

Here are some of the posts that caught my eye recently. Hope you find something interesting.

 

 

Lighter Links:

• Radical Candor Will Help Managers Balance Accountability and Empathy. (SmallBizTrends)
• Pretending to Be Batman Helps Kids Stay on Task. (Digest)
• The Secrets of Disneyland: a Company Vet Explains How the Magic Happens. (FastCompany)
• What Actually Happens When You Pull a Muscle? (Popular Science)
• Now that Anyone Can Hack BiologyShould We Be Afraid? (SingularityHub)

Trading Links:

• How to Destroy Our Economy. (Forbes)
• Bulldozers Can Show You Where the Economy's Going before the Official Data Do. (Bloomberg)
• JPMORGAN: Here's What Could Cause the next Financial Crisis. (BusinessInsider)
• Goldman Sachs to Explore Starting Bitcoin Trading Venture. (Bloomberg)
• AI Will Eliminate 1.8M Jobs but Create 2.3M by 2020, Claims Gartner. (TechRepublic)

Here Are Some Links For Your Weekly Reading - October 8th, 2017

 Old people and their joints ... it's becoming an issue. 

 

Here are some of the posts that caught my eye recently. Hope you find something interesting.

Lighter Links:

• Why Culture Doesn't Just Beat Strategy, It Must Be the Strategy. (Inc)
• Google Reveals the Top Things People Want to Find out How To' Do. (TechCrunch)
• Pain Leads to Empathy and Self-preservation: Should We Make Robots Feel' It? (Aeon)
• Gartner's Hype Cycle for Emerging Technologies Adds 5G and Deep Learning. (Forbes)
• Hostile Terrain: Tank Traps, Fake Towns & Secret Tunnels of the Korean Borderlands. (99PercentInvisible)

Trading Links:

• Seventy-Eight Billion Reasons Why Bitcoin Is the New Gold. (Globe&Mail)
• Amazon Wants to Open a $5 Billion Second HQ in North America. (CNN)
• Has Disruption from E-commerce Run Its Course? (Latest)
• Who Vladimir Putin Thinks Will Rule the World. (CNN)
• Employees at the World's Largest Hedge Fund Use iPads to Rate Each Other's Performance in Real-Time – See How It Works. (Insider)

Gartner's 2017 Hype Cycle for Emerging Technologies Identifies Innovations Worth Monitoring

There's a lot of "hype" these days.  Social media and tools like Kickstarter would have you believe that every new idea is the "next big new thing".

In contrast, Gartner's Hype Cycle Report is a considered analysis of market excitement, maturity, and the benefit of various technologies.  It aggregates data and distills more than 2,000 technologies into a succinct, contextually understandable, snapshot of where various emerging technologies sit on the hype cycle.

Understanding this hype cycle framework enables you to ask important questions like "How will these technologies impact my business?" and  "Which technologies can I trust to stay relevant in 5 years?"

 

What's a "Hype Cycle"?

 

As technology advances, it is human-nature to get excited about the possibilities we imagine ... and then to get disappointed when those expectations aren't met. 

At its core, the Hype Cycle tells us where in the product's timeline we are, and how long it will take the technology to hit maturity. 

At this point in time, Machine Learning/Deep Learning and Connected Homes are at the peak of their hype cycles ... Meanwhile, Augmented Reality and Blockchain have matured past the hype phase (with Self-Driving Cars following close behind).  

This year, according to Gartner, there are three overarching "mega-trends" to watch. 

• AI Everywhere shows the transition towards a ubiquitous AI experience, from self-driving cars, to machine learning, and to smart robots.  Consider the impact on traffic/accidents with the adoption of autonomous vehicles, or the ability of machine learning to process more data faster. 
• Transparently Immersive Experiences shows our transition towards human-centric contextual and fluid technological experiences.  - like Connected Homes or Virtual Reality. Consider the impact of Augmented Reality on advertisements or gamification. 
• Digital Platforms shows the transition of emergent platforms into adoption. Platforms like Blockchain, IoT,  and Quantum Computing. Consider the effects of bitcoin and other blockchain initiatives, as well as the opportunity for new business models centered around these platforms.

 

Here is the chart. You can click the image to see it larger. 

 

via Gartner

For comparison, here is the chart from last year; and you can check out my article on 2015's hype cycle here.

via Gartner

The hype cycle gives us an idea of which of these technologies will likely survive the market hype and have a potential to become a part of our daily life. 

Here are the five regions of Gartner's Hype Cycle framework:

1. Innovation Trigger (potential technology breakthrough kicks off),
2. Peak of Inflated Expectations (Success stories through early publicity),
3. Trough of Disillusionment (waning interest),
4. Slope of Enlightenment (2nd & 3rd generation products appear), and
5. Plateau of Productivity (Mainstream adoption starts). 

  

Which technologies do you think are over-hyped ... and which ones might survive the hype?

I find this stuff fascinating.  Consider some of the interesting technologies just starting their hype cycle:

• Human Augmentation has the potential to enhance our bodies and minds using electrical currents, chips, or exoskeletons, but also raises ethical and legal questions. 
• Quantum Computing is still in its infancy, but could theoretically solve certain problems far faster than classical computers. 
• Smart Dust opens up the possibility of monitoring essentially everything by creating a vast network of minuscule sensors that can detect various inputs. 
• 4D Printing would theoretically allow us to print objects that reshape or self-assemble over time. 

We live in amazing times! 

Onwards. 

Yom Kippur: A Day of Atonement

Yesterday was Yom Kippur, one of the High Holy Days for Jews, otherwise known as the Day of Atonement.

As part of the holiday, we read down a list of sins (text available here), apologizing for the ones that we committed, and asking forgiveness.  In addition, we promise to do better next year.  

It's really interesting how little human nature has changed in the past several thousand years. The list of sins is just as relevant today as I imagine it was back then.  

via Dry Bones

Equally important to recognizing and repenting for your sins, is what comes after.

Remembering all the good you did as well ... for yourself, your friends and family, or your community. 

It's an important framework that highlights how you have grown; and, it also shows where you have room to grow. 

Hoping you all experience growth in your mental states, your relationships, and in your businesses. 

What Is Machine Learning?

Machine Learning is a broad term ... Essentially, it's a method of data analysis that automates the process of building models.

That means instead of having a programmer figure out how to solve a problem, you have the program figure out how to solve the problem. 

While you probably know the basics, wisdom comes from making finer distinctions. 

So, here is a chart that sheds some light on the current state of Machine Learning.

 

via techleer

Also, if you are interested, here is a list of some other good visual summaries and articles about AI and Machine Learning:

• Understanding Machine Learning (Futurism)
• Machine Learning Cheat Sheet (DataScienceCentral)
• The Periodic Table Of AI (XPrize)
• Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics (DSC)
• A Visual Introduction to Machine Learning (r2d3)