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Here Are Some Links For Your Weekly Reading - February 4th, 2018

Cloning primates ... What could go wrong?

 

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

Lighter Links:

• U.S. Soldiers are Revealing Sensitive and Dangerous Information by Jogging. (WashPo)
• Billionaire Saudi Prince, Alwaleed Bin Talal, Freed from Detention. (New York Times)
• Science You Might Have Missed in 2017. (Bloomberg)
• Yale's Most Popular Class Ever: Happiness. (New York Times)
• Machiavelli's Advice for Nice Guys. (YouTube)

 

Trading Links:

• Apple Buying Tesla Doesn't Sound like a Crazy Idea Anymore Here's Why. (Insider)
• Every One of the World's Big Economies is Now Growing. (New York Times)
• We are on the Verge of a Consumer M&A Avalanche. (TechCrunch)
• Blockchain Will Transform and Reinvent Organizations, Ecosystems and Economies. (Forbes)
• One Brutal Chart from the Biggest Hedge Fund in the World Explains Everything. (BusinessInsider)

Scientists Have Just Cloned Monkeys

Do you remember Dolly the Sheep?

She was the first mammal cloned "from an adult somatic cell, using the process of nuclear transfer."

Dolly was cloned from a mammary gland and was named after Dolly Parton ... for obvious reasons.

Since then, many other large mammals were cloned, including pigs and horses. 

 

TIME via Youtube

It was just announced that Chinese scientists have cloned two long-trailed macaques using the same technique that produced Dolly. 

Since humans are primates as well, this is an exciting, and mildly terrifying, step towards cloning humans. 

Pragmatically, this bolsters medical research by making it possible to study diseases on uniform subjects, but it also raises tough questions on human cloning. 

As A.I. and cloning advance, some tough bio-ethic issues will take front stage.  It is time to start thinking about what defines a person (or even a living creature) and what rights they have.

Innovation stops for no one ... and Nature finds a way.

Onwards!

 

Here Are Some Links For Your Weekly Reading - January 28th, 2018

 

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

Lighter Links:

• Trump Reportedly Uses an Indian Accent to Mimic Modi at Meetings. (Quartz)
• Statistician is One of the Fastest-growing Jobs for the Future. (Qz)
• Compare Your Fears against Reality. (FlowingData)
• Vladimir Putin Takes Dip in Freezing Water to Mark Epiphany. (CNN)
• China, Russia and the U.S. are Running Neck-and-neck in an AI Military Arms Race. (Latest)

Trading Links:

• How Blockchain Could Radically Alter Global Finance. (Insight)
• Davos: a Rough Guide to the World Economic Forum. (BBC)
• Are Google and Facebook Monopolies? (Review)
• 10 Charts that Will Change Your Perspective on Artificial Intelligence's Growth. (Forbes)
• Apple Rises to Become World's Fourth-Largest PC Maker with around 20M Macs Sold Last Year. (MacRumors)

What Does The Average NBA Player Look Like?

Each sport has a different ratio of ethnicities. You might expect more Pacific Islanders in Rugby or Caucasians in Golf. 

So what happens when you average the top players' faces in various sports?

As you might expect, you get very different results depending on the sport.  See what I mean?

  osmutiar via Reddit

Not particularly surprising.

What is worth noting, however,  is that while you may be thinking "this player must be unstoppable" ... statistically, he's average.

The "composite" NBA player would be the 112th best player in the league. He's the fourth best starter on an okay team. 

We found the same thing with our trading bots.  The ones that made it through the most filters weren't the star performers.  They were the average bots that did enough not to fail (but failed to make the list as top performers in any of the categories).  The survivors were generalists, not specialists.

The reminder is that you won't find exceptional specialists if your focus is on generalized safety.

Onwards.

Which Industries are Prime for Disruption?

Last year, I talked with the CEO of CB Insights about how Fintech was disrupting the value chain of financial services. 

Since then, it's become even easier to see how disruptors are changing every industry, and becoming leaders in their fields.

 

via McKinsey

 

Companies like Lyft, Tesla, and Netflix changed paradigms and are now leading the pack, but what industries are next?

Looking at a report by McKinsey&Company, we find that the 5 industries with the least digitization account for 34% of GDP and 42% of all employees. 

 

1. Agriculture and Hunting
2. Construction
3. Hospitality
4. Healthcare
5. Government

via Quora

But, being less digitized than competitors, alone, isn't enough to indicate it's ready for disruption: 

 

How Regulated Is The Industry?

Heavily regulated industries mean that any company that can find a way around current regulations and tax structures can become an effective competitor fast ... i.e Lyft and Tesla

Is There Too Much Competition Already?

How many competitors are in the space? Is there spare capacity, or does the current model waste resources? Think taxis waiting for customers or empty seats on airplanes. 

Can it Be Automated?

Lot's of industries and tasks are ready and waiting to be automated - and only haven't been due to the cost of switching to new technology. 

 

To put it another way - are you solving a customer headache while lowering costs for you and the customer? 

The only constant is change, and digitization and automation are only increasing the rate of change. The type, quality, and the number of jobs being offered are changing rapidly. 

As digitization increases so does adoption of AI-related technologies. 

McKinsey Institute via Vox

AI is coming, disruption is coming.

It's no longer possible, it's not even just probable, it's inevitable

This interactive graph tells you if your job is automation proof, and what percentage of your job can be automated.

What industry do you think is next?

Here Are Some Links For Your Weekly Reading - January 21st, 2018

It's day 2 of the government shutdown; but what does that actually mean?

In short: 

• "Essential" government services will still run even if employees aren't getting paid - USPS, TSA, Social Security
• Other "non-essential" government employees will be "furloughed" and told to stay at home. 
• Military will be required to work, but won't be paid until Congress comes to an agreement
• Employees will be paid retroactively once an agreement is met. 

 Efficiency at its finest ... or a force function to get the children to play nicer with each other?

 

 

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

Lighter Links:

• Want to Get Wisdom? Be Your Own Crowd. (Bloomberg)
• NASA Just Proved It Can Navigate Space Using Pulsars. Where to Now? (Wired)
• It's So Cold in Russia that Thermometers are Breaking. (BGR)
• What Robot Strippers Say about Sexism, Tech and the Future. (AP News)
• Benjamin Franklin Built His Character around 13 Virtues and Following His Weekly Plan Could Change Your Life. (BusinessInsider)

Trading Links:

• How Donald Trump Has Remade the Rules for Business. (Wall Street Journal)
• Fed Paid $29.3 Billion to Banks 'Not' to Lend in 2017; Gave $80 Billion to Treasury. (ZeroHedge)
• One Person is Probably Responsible for Almost 600 Percent of Bitcoin's Price Rise. (Mashable)
• Kodak's Pivot to Crypto Seems to Be Working out Quite Nicely. (FastCompany)
• These are the Biggest Risks for Businesses in 2018, According to the World Economic Forum. (Fortune)

Some Things Never Change ...

This week I went to Chicago to speak at my old alma mater - Kellogg.

It was great to talk with professors and spend time with MBA students interested in trading and how the business of trading is changing. 

I plan on spending more time there to benefit research and recruiting.

 

 

Unsurprisingly, deep dish pizza is still delicious.  We were going to eat at a steakhouse.  However, Jennifer and I remembered that the only thing better than gorging on meat ... is gorging on meat and cheese. 

While some things haven't changed, others have.

The Universe must be trying to tell me something.  The day I got back, I found my old ID card ... and, apparently, some things have changed in the past thirty years. 

 

 

Onwards.

Algorithms are Watching: How Machines Learn

Machine Learning algorithms are everywhere.

They're helping you pick out your next gift on Amazon, controlling what you find on Google, they're suggesting new music for you on Spotify, and they're doing their best to keep you on their website.

When trying to explain how machines learn we tend to try and describe it in human terms. Unfortunately (or fortunately) machine learning isn't based on how we teach humans.

The video is a bit simple in its explanations, but it describes some important concepts. So, watch how machines learn.

 

CGP Grey via Youtube

The video focuses on Genetic Algorithms, which is one type of machine learning, and neglects some of the other more complicated approaches.

As machine learning gets more complicated and evolved, it gets harder for a human to understand what makes it good ... and that's okay. 

It's human nature to feel safer when we understand something. It's human nature to envision machines as making human-like decisions, just faster.

Of course, just because it suits human nature to believe something, that doesn't make it true. 

Part of what makes machine learning exciting is that it can do a lot of things well that humans are really bad at. 

In reality, it doesn't matter why a bot is making a decision, or what inputs the bot is making the decision on. What matters is the performance and level of decision-making in relation to itself and to other options.

One of the lessons I teach when I speak publically is that in trading, caring about the markets is a weakness.

It's a distraction. 

I don't care how markets are doing.

I care how my systems are doing. I care how my portfolio is doing.

There's too much data for me to try and care about anything else. 

It's a brave new world, and not only is big brother watching, but algorithms are too.

Here Are Some Links For Your Weekly Reading - January 14th, 2018

 

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

Lighter Links:

• Tesla Model 3: the First Serious Review. (The Drive)
• How Religion Made a Global Comeback in 2017. (The Atlantic)
• New Year's Fitness Resolutions: the Smartest Way to Keep Them. (WSJ)
• How Kaspersky's Software Fell under Suspicion of Spying on America. (Wall Street Journal)
• Could Your Apple Watch Save Your Life?: How Smartwatch Sensors Could Help Tackle a Dangerous Heart Condition. (ZDNet)

Trading Links:

• Kodak Announces Blockchain Plan, Share Price Soars. (FinExtra)
• Here's Why Spotify is Bypassing the Normal IPO Process and Why More Companies Don't Do It. (BI)
• As Dow Tops 25000, Individual Investors Sit It Out. (Wall Street Journal)
• Amazon Has a Master Plan to Turn Alexa into a Full-fledged Economy All on Its Own. (Insider)
• A Crypto Expert Explains the Difference between the Two Largest Cryptocurrencies in the World: Bitcoin and Ethereum. (BusinessInsider)

Ultra Spiritual Wisdom on Bitcoin

Seemingly everywhere I go, someone asks me about Bitcoin.

Clearly, there are speculators and day traders banking coin. 

I am a little surprised by how fast it captured the cultural zeitgeist.

Here's a clever spoof ... worth watching.

  

 AwakenWithJP via Youtube

I'm sure we'll talk more about Bitcoin ... but, more importantly, Blockchain (which is the technology that Bitcoin and other cryptocurrencies were built upon).

I am currently investigating and planning how we'll use Blockchain.

Onwards.

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