Capitalogix

This Week in AI: AI's Weaknesses

AI has plenty of weaknesses - I've talked about some before, and I'll continue to talk about them in the future, but two specific weaknesses were brought to my attention this week. 

AI Portraits - Won't Steal Your Data, But Might Steal Your Soul Dorian Gray-Style

I assume most of you have seen the FaceApp trend - people age-ifying their photos and unwittingly giving the rights to their photos to a shadowy Russian tech company.  You've also likely seen AI paintings selling for ridiculous money. 

But have you seen their lovechild AI Portraits - a more wholesome experiment run by the MIT-IBM Watson AI Lab. AI Portraits uses approximately 45,000 different Renaissance-esque 15th-century portraits and General Adversarial Networks to translate your selfie into an artistic masterpiece. It's novel because instead of simply drawing over your face it's generating new features and creating an entirely new version of your face.

 

Mauro Martino via YouTube

It's impressive because it determines the best style for your portrait based on your features, your background, and more. 

However, it's not without "flaw". The choice of 15th-century portraiture creates a couple of clear biases. At the time, portraits of smiling or laughing individuals were rare, so your smile will likely not transfer. As well, there's a clear bias towards anglo-saxonification. 

via AI Portraits

My son got excited while playing with the app and sent several of his coworkers, friends, and family through the app. If you look at the bottom right, you'll see my lovely wife Jen's portrait. 

Most of you have seen my wife and know that she is Indonesian, something that is very much removed from the translation. 

You can also see it in Beyonce's AI portrait. 

via MyModernMet

All photos are immediately deleted from their servers after creating your image, so your privacy is safe (this time!)

All biases can be considered quirks of this current iteration of the program - which I do earnestly believe is interesting. 

Later, you can imagine an AI choosing between various different styles of art based on a cornicopia of factors - or off human selection - but you have to walk before you can run, and this is a fun way to get people excited about AI. 

Computer Answering Systems - No, The Answer Isn't 42

“Yes…Life, the Universe, and Everything. There is an answer. But I’ll have to think about it...the program will take me seven-and-a-half million years to run.” - Deep Thought, Hitchhiker's Guide To The Galaxy

Think of the global excitement when IBM's Watson first beat Ken Jennings in Jeopardy ... it's widely considered one of the holy grails of AI research to create a machine that truly understands the nuances of language and human thought. Yet, if you've talked to Alexa recently, you know there's a long way to go. 

Today's question answering systems are basically glorified document retrieval systems. They scan text for related words and send you the most relevant options. Researchers at the University of Maryland recently figured out how to easily create questions that stump AI (without being paradoxical, impossible to answer, requiring empathy etc.) in order to enhance those systems.

A system that understands those questions will be a massive step toward a real understanding and processing of language. 

So what's the secret to these "impossible" questions?

From the University of Maryland article: 

The questions revealed six different language phenomena that consistently stump computers. These six phenomena fall into two categories. In the first category are linguistic phenomena: paraphrasing (such as saying “leap from a precipice” instead of “jump from a cliff”), distracting language or unexpected contexts (such as a reference to a political figure appearing in a clue about something unrelated to politics). The second category includes reasoning skills: clues that require logic and calculation, mental triangulation of elements in a question, or putting together multiple steps to form a conclusion [...]

For example, if the author writes “What composer's Variations on a Theme by Haydn was inspired by Karl Ferdinand Pohl?” and the system correctly answers “Johannes Brahms,” the interface highlights the words “Ferdinand Pohl” to show that this phrase led it to the answer. Using that information, the author can edit the question to make it more difficult for the computer without altering the question’s meaning. In this example, the author replaced the name of the man who inspired Brahms, “Karl Ferdinand Pohl,” with a description of his job, “the archivist of the Vienna Musikverein,” and the computer was unable to answer correctly. However, expert human quiz game players could still easily answer the edited question correctly.

 

The main change is increasing the complexity of the questions by nestling another question. In the above example, the second question forces the AI not only to decide the composer inspired by Karl Ferdinand Pohl, but also to decipher who is inspiring (hint: It's Karl Ferdinand Pohl). 

AI isn't great yet at mental triangulation; at putting together multiple steps to form a conclusion. While AI is great at brute force applications - we're still coding the elegance. 

 

via Gaping Void

Here Are Some Links For Your Weekly Reading - August 9th, 2019

 

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

 

Lighter Links:

• How to Prioritize When Everything Feels Important. (Zapier)
• DNA Data Storage is Closer Than You Think. (Scientific American)
• The Man Who Can Remember Every Day of His Life. (BBC)
• How the West Got China's Social Credit System Wrong. (Wired)
• Scientists are Making Human-Monkey Hybrids in China. (TechReview)

 

Trading Links:

• First Spotify, Now Slack: Wall Street May Be Losing Its Iron Grip on Silicon Valley. (Vox)
• The Tokenization of Securities is Happening Right Now and No One is Noticing. (VB)
• 5 Big Breakthroughs to Anticipate in 3D Printing. (SingularityHub)
• How the State Runs Business in China. (TheGuardian)
• Researchers Map Global Economy in Collaboration with LinkedIn. (Phys)

Here Are Some Links For Your Weekly Reading - August 4th, 2019

 

 

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

 

Lighter Links:

• Being and Drunkenness: How to Party Like an Existentialist. (Aeon)
• When Navy Sailors & Marines Share a Ship, Karaoke Night Gets Complicated. (WSJ)
• Fewer American Women are Working Than Two Decades Ago. (Economist)
• Now Calling Balls and Strikes: Robot Umpires. (Wall Street Journal)
• The State of AI in 2019: Breakthroughs in Machine Learning, Natural Language Processing, Games, and Knowledge Graphs. (ZDNet)

 

Trading Links:

• This VC Firm Just Raised More Than $1 Billion to Invest in Moonshots: Term Sheet. (Fortune)
• Pentagon Puts $10B Contract on Hold After Trump Swipe at Amazon. (Politico)
• The Two Times in History Stocks Have Been this Expensive: 1929 and 2000. (Fortune)
• Stocks Plunge After Fed Cuts Rates for First Time since 2008. (CNBC)
• Opinion: This Highly Accurate Stock-Market Predictor Just Hit Its Most Bearish Level since the Internet Bubble. (MarketWatch)

Fixing Capitalism’s Oligopoly: A Response to Ray Dalio and John Mauldin

Recently, Ray Dalio released a letter "Why and How Capitalism Needs To Be Reformed, Parts 1 and 2." 

I believe that all good things taken to an extreme can be self-destructive and that everything must evolve or die. This is now true for capitalism. In this report I show why I believe that capitalism is now not working for the majority of Americans, I diagnose why it is producing these inadequate results, and I offer some suggestions for what can be done to reform it. 

In it, he outlines what he thinks the problem with our current capitalist system is, and offers some solutions. My friend and great economist, John Mauldin entered into a fun dialogue with Ray about where they agreed and disagreed.

Before anyone gets up in arms without even having read their treatises, both are staunch capitalists and believe strongly in America and Capitalism. 

Fundamentally, they shared a lot of opinions, but some key differences in takeaways, specifically around Modern Monetary Theory.  They agree that the existing system isn't producing equal opportunity and that equal opportunity is an important aspect of capitalism. Here's their discussion if you want to do your full due diligence. 

• It's Time To Look More Carefully at "Monetary Policy 3 (MP3)" and "Modern Monetary Theory (MMT)" - Ray Dalio
• Ray Dalio Is Kinda, Sorta, Really Wrong - John Mauldin
  
  • Part 2
  • Part 3
  • Part 4
  • Part 5
  • Part 6
• Clarifying What John Mauldin And I Agree And Disagree On About How Capitalism Is Working - Ray Dalio

Instead of trying to fully encompass and summarize their bodies of work, I encourage you to do your own research. 

I am, however, sharing a response written by our CIO, John DeTore. I first met John DeTore and John Mauldin at Camp Kotok, which I've written about many times. 

Last year, I brought John DeTore in to talk to my data science team and put them through the wringer. He had years of experience at several large firms and taught Active Management at MIT. He was scheduled for two hours. He stayed for eight. He was impressed by what we'd accomplished with a pure data science background and was excited to add his quantitative expertise. I knew I needed him on the team, and the rest is history. 

Here's his full response to Ray and John on their takeaways and the idea that "this time it's different":

___________

Dear John,

The latest writings you have produced have been fun and illuminating … some of the most hard-hitting economic analysis I’ve read lately.  The back and forth with Ray Dalio effective and entertaining!  I appreciate that you are not just discussing what has been happening, and why you think it’s happening, but what we should do about it.

Thesis:

As seasoned observers, I think you both would agree that “this time it's different” is a phrase to use with caution.  We have all seen this expression invoked … just to be proven wrong.  We need to be judicious in our observation of phenomenon that means that the “usual order” needs to change.  This is the exception, not the rule.

I believe, however, that there are significant structural issues that are different this time … and that it is important to deal with these issues to get to effective policy to properly respond to our current economic situation.

In brief: 1) The Fed is lost as to why they don’t need to tighten.  Tightening is a crude and imperfect, and possibly dangerous, way to slow the economy when inflation is a threat.  Inflation is not a threat.  2) Long rates are too low.  (This leads to the conclusion that the federal debt must not be that much of a problem.)  So Dalio’s QT3 is not to be feared … and is probably needed.  Somewhat higher long rates might be a good thing.  3)  If we want the strong economy and just freedom that capitalism can bring, we need to fear structural issues that threaten good capitalism. The enemy is concentration:  too few people with power, too many monopolies and too little intervention to keep capitalism working.  Big Technology, Big Finance, and Big Pharma come to mind.

Discussion:

The supply-side shock

In the first year of the current administration, we enacted a huge change in the corporate tax rate and enacted sweeping change to regulatory burden.  This represents a significant supply side shock.  (Typically, I believe we ascribe too much importance to the effect White House policy has on the economy.  I mean, the economy is big and diverse, and most administrations bogged down in grid-locked political administration.  This time might just be different.)

As I remember from college economics, this pushes the supply curve out while leaving the demand curve untouched.  The effect is to increase output and decrease prices.  I believe that we are in the midst of this big shock with its impact on both output and prices.  (It is as if the classic lemonade stand one day learned how to make the same glass of lemonade that cost $0.25 for a cost of $0.05.   One way or the other, we will end up with more lemonade at lower prices.)  At the aggregate level we end up with GDP growth and disinflationary forces.

Corporations, due to significantly lower taxes, have more to spend on operations, and are free to both invest and compete for scarce labor and bid up wages. This is OK … it was overdue and can be somewhat offset by the disinflationary impact of the supply shock.  It isn’t inflationary if stimulated by a supply-side shock.

This produces the wonderful holy grail:  more output, price stability and growing wages inside that price stability.  How confusing this must be for the Fed!  We make both of their objectives easy for them, then ask what policy changes they need to make.   (Of course, there is little for them to do except enjoy their good fortune!!)

In particular, we should not misunderstand the Phillips curve … even Alban Phillips agreed the curve moves all the time.   (It represents only the current, short-term trade-off between wage inflation and unemployment.  But since it moves all the time, it is not a good forecasting tool for wage inflation — or inflation in general).  Often, I think the Fed believes low unemployment portends general inflation in the near future.  This is not a good conclusion today …  perhaps why we keep waiting for inflation that doesn’t materialize.

Where is all the employment coming from??

It is fair to ask how we can be at full employment yet growing monthly employment at numbers greater than 200K a month.   If we are essentially out of unemployed people, where are all the jobs coming from?

The question is an important one.  If we are out of people, we are due for an accelerating labor shortage and possible inflation and growth limits.  If not, labor will not be a limiting factor anytime soon.

To me the ingredients of macro growth are 1) labor, 2) capital and 3) animal spirits.  With rates this low, and the enthusiasm of the policies of the current administration, we have 2 & 3 in bountiful supply.  But with regards to labor, consider long-term payrolls in the US economy:

U.S. Bureau of Labor Statistics via FRED

The point of this chart:  the total employment we lost in the 2008 crisis has never been made up.  The green line helps see that this crisis was quite different with its permanent destruction of jobs.  We permanently wrote off what appeared to be almost 10M people.  Some of these are lost to retirement as the baby-boomers are approaching that age, but it’s possible there are many people who can still return to the economy … and others that can upgrade their position.  Part of the strength we see now may be the final recovery from the financial crisis … delayed in part through the policies of the last administration and other issues that left corporate management with more pessimism than would normally be seen in a recovery.

High Federal Debt

Our debt binge started with a gambit by George W. gone bad:  reduce gov’t revenue and eventually spending will be reduced to match it.  This didn’t happen of course, and the Federal debt accelerated.  Bring on an economic collapse in 2008, and we doubled down with a Keynesian debt expansion to aid the recovery.  Of course, to be Keynesian about it, we should have run a surplus as the danger of economic collapse passed.  What to make of our runaway debt today?

John, one lunch at Ocean Prime we went over the absurdity that QE3, in fact, essentially monetized a chunk of this debt.  To me, admitting that QE3 was monetization is step one of understanding the issue.  (I wonder if it was a test run for Dalio’s MP3.)   How could we have monetized $4T of government debt — and see interest rates fall?  Shouldn’t our rates accelerate?  Our currency fall? 

In part, we might argue governments all over the world are doing this, so as all our currencies fall together, we don’t notice movement in exchange rates.  If this is true, gold would be rising rapidly and to some extent this has been true recently.  But a significant percentage of OECD debt is now at negative rates.  We can make no other conclusion that investors desire government debt, and capital is very cheap and available — perhaps more now than ever.

Perhaps the experiment of QE3 should be repeated, at least as long as the markets do not punish us.  Has the Fed continued to buy up long-dated treasuries?  Call the bonds from the Fed and pay for them with IOUs of some sort.  The IOUs will revert to the treasury where they will be shredded.  Voila!  Debt is gone.  Last year I spent hours discussing this at Camp Kotok with people who should know Fed accounting and methods better than anyone.  I got no pushback.  In fact, this is on Dalio’s table of example MP3.

 

Of course, were this to work, we need not go through with it.  We only need to acknowledge that the debt is not a problem.  In fact, that is what the current low rates are telling us right now — no sovereign risk for OECD.

The role of long rates

To me, one key role of long rates is to set a fair price between borrowers and lenders.  For instance, it's common for retirees to hold bonds for income, and for young families to borrow long-term through mortgages to purchase houses.  Though there are of course intermediaries, I find it helpful to see long rates as an inter-generational negotiation.  Long rates govern retirement rates of return, pension liability calculations, and mortgage rates (which drive housing prices).  

Typically, these rates are set through the invisible hand, but what happens when the government intervenes and lowers long-rates artificially:

• Mortgages become artificially too low, perhaps driving housing prices too high (we are not subsidizing young families, we are having them incur more debt when buying their homes from long-term owners).
• Pension liability calculations are too high, causing significant funding shortfalls. Yes, too low long rates are one culprit to the underfunding problem.
• Corporate bond yields are too low, boosting EPS, but also leading to potentially aggressive spending decisions.
• Particularly weak companies hang on instead of folding (“zombie companies”).
• Retirees who desire the financial stability of liability immunization find that even significant savings produce a surprisingly small income. Millionaire retirees might not even have the income of the maid that helps them in old age.

My point is not to argue about all these policies.  It is only to say that pushing rates away from the natural equilibrium to stimulate the economy can unfortunately also have some serious side effects.  At a minimum, it distorts housing prices and retirement programs in significant ways.  It is not hard to surmise that these inefficiencies might slow the economy in some way — counteracting the simplistic notion that artificially low long rates stimulate the economy.

Income inequality

We hear a lot of discussion about social unrest coming due to a supposed unjustly large spread in incomes. 

Some economists attribute this, to some degree, to easy Fed policy.  It stimulates big business and tends to inflate asset prices, both of which could be argued to most benefit those at the top.  I’d just like to point out that many people have done versions of the long-term inequality graph and credible efforts look particularly like income concentration is inversely correlated to interest rates.  These graphs all show that the most “equal” time coincides with interest rate peaks in 1980.   Most of the most inflaming graphs depicting growing inequity start in 1980 — those with a long-term perspective show the level of equality now approaching pre-WWII levels. 

If solving “income equality” requires returning to late 70’s macroeconomic conditions, I am not in favor.

For the moment, I’d like to suggest another culprit for the disruption of our income distribution harmony...  There is a peculiar fall-off in the number of listed companies in the US:

The Incredible Shrinking Universe of Stocks via Credit Suisse

 

This trend started in the late ’90s and could potentially be caused by a number of factors, and it could result in a number of impacts.  The phenomenon is under-researched, but the papers that have been done look at issues like 1) impact of Sarbanes-Oxley (SOX), 2) growth of private equity capital, 3) the growth of M&A activity on Wall St and its need to keep the pipeline growing, and 4) a number of structural issues (like SOX) hurting small company formation.

While it is tempting to immediately blame SOX, the research I have seen seems to support that the larger impact is a birth of large pools of private equity capital, the resultant fueling of corporate shopping through increased M&A activity, and the simultaneous birth of alternatives to the IPO.  In summary: as we have chosen to allocate institutional assets away from public stocks and towards private equity, the M&A industry has provided means. 

Of course, this could have a number of impacts. It's reasonable to think that it drives inequity.  I think it could drive other things, many of which are counter to the free market capitalistic society.

As our corporate base consolidates, we concentrate more power in fewer management teams … and fewer CEOs.   We likewise have fewer CFOs and COOs, but those that remain might earn particularly high incomes, or may benefit from the M&A spoils to pad their wealth.  It's easy to see how this causes income inequality, specifically in corporate senior management.

But consolidation means fewer payroll departments, more consolidation in rank and file operations, and less breadth of competitors.  All of these may have an effect on our economy.

When I was a child, but old enough to ask, my parents explained competition to me.  They said any industry requires several companies in it, and if too much consolidation occurs the Department of Commerce steps in.   (They also said it was quite illegal to charge different process to different customers.)    Capitalism works, but over-consolidation leads to monopoly or oligopoly profits. 

The current political debate over capitalism is wrong-headed.   We need to reacquaint ourselves with its principles … pay more attention to keeping markets free and agile.  Consolidation in tech companies, banking and healthcare have yielded industries that are too profitable, and the elite leaders of these organizations (Facebook, Google, Microsoft, Goldman Sachs, other large banks, the large drug companies) with paychecks that drive the “income inequality” statistics.  Sure, the top 10% is doing well, but careful analysis will show this is almost entirely driven by how well the top 1% are doing.  (John, you showed this chart, but I am choosing a graph that adds the 5% and 10% curve for comparison.)

Striking it Richer: The Evolution of Top Incomes in the United States by Emmanuel Saez

 

Rockefeller, JP Morgan, Zuckerberg, Bezos.  They represent their eras, and each provided great insight and value to the American economy.   But it’s hard to argue that they do not benefit from some degree of monopoly profits.

Conclusion

This time it is different:

• Conventionally, we expect that such low rates of unemployment should cause wage inflation, but that isn’t happening
• Conventionally, we believe unprecedented levels of government debt will create problems for markets, or at least higher rates, but that isn’t happening

There seems to be an economic quagmire:  we worry about inflation acceleration; long rates keep falling.  The Fed pushes short rates up, but even at full employment or beyond, we have trouble observing anything that looks like persistent inflation.

Time to at least consider:

Inflation is not going to be a problem:

• There may still be many people to join the workforce
• Structural, and very positive, supply-side shocks are working their way through the system

(Long rates seem to confirm that inflation is not a problem)

US Government debt is not a particular problem:

• I’d prefer a Dalio style MP3 that exchanges higher long rates for lower government debt, if only to correct the inefficiency of long rates that are too low (below where the invisible hand would set them)
• The real goal should be to return control of long rates to the invisible hand.

(Again, long rates seem to confirm that debt isn’t a problem)

We do have macroeconomic issues to deal with.  These are the real issues, not those above:

• There is a concentration & consolidation of our important growth industries: tech, finance and healthcare
• Additionally, finance has been targeted for significant regulatory help that benefitted large firms over small ones
• The massive funding of private equity pools, and the resulting ramping of a significant M&A business on Wall St. has concentrated power in the hands of too few. We have massively overdone mergers.  This not only adds to inequality … it imperils the agility and growth of the economy.
• This results in:
  • very high profitability of winning large companies
  • possible sidelining of a good number of our most talented senior executives at the prime of their life
  • a reduction in the number of companies
  • a reduction in small companies hurts one of the most vibrant sectors for innovation and job growth
  • this concentration also manifests as some of the drivers for income inequality
• We need to consider
  • increasing Commerce department vigor towards any monopoly
  • a national healthcare policy that restores basic competition to the industry
  • regulatory or tax changes that incent IPOs over mergers, and/or spinoffs over mergers.

A sign that policy is working here:  IPOs, spinoffs, large breakups, and eventually a return to trend number of public companies.

 

__________________________

 

There's a lot to discuss when it comes to our US and global economics. While I expound the inefficiency of economics as a driver of trading decisions, it plays a huge role in the daily and professional life of every one of us. 

Let us know what you think.

Here Are Some Links For Your Weekly Reading - July 28th, 2019

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

 

Lighter Links:

• Elon Musk Unveils Neuralink's Plans for Brain-Reading Threads' and a Robot to Insert Them. (TheVerge)
• Ethical Artificial Intelligence Becomes a Supreme Competitive Advantage. (Forbes)
• The 1 Private Thing Queen Elizabeth Insists on Doing Every Single Day. (Cheatsheet)
• The World's Best Restaurants. (Bloomberg)
• Amazon Surpasses Apple and Google to Become World's Most Valuable Brand. (MacRumors)

 

 

Trading Links:

• Microsoft's 'Blow Out' Fourth Quarter Beats Analyst Projections by $1 Billion. (CNN)
• Netflix is Losing Beloved Shows, Subscribers, and Confidence. (TheVerge)
• Market Commentary From The Rocky Mountain Summit. (CumberlandAdvisors)
• Who Will Win? Banks, FinTechs or BigTechs? (FinExtra)
• How Discount Brokerages Make Money. (Kalzumeus)

Fueling Alpha: Data is Powering the New World

Data is becoming a precious commodity.

A staggering 90% of all the world’s data (2.5 quintillion bytes per day) has been created in the past two years alone ... and its value is rapidly rising.

With IoT growing from 2 billion devices in 2006 to a projected 200 billion by 2020 you can expect to see that growth continue to explode.

Data is today’s “wild west” and the battlefield of today’s tech titans. Alphabet, Amazon, Apple, Facebook, and Microsoft all have an unprecedented amount of data (and power).

Rapid growth means little time to create adequate rules. Everyone’s jumping to own more data than the next and to protect their own data from prying eyes.

I see it in trading, but it’s pervasive in every industry and in our personal lives.  

Having basic data and basic analytics used to be enough, but the game is changing.  Traders used to focus on price data, but now you’re seeing an influx of firms using alternative data sets to find an edge. If you’re using the same data sources as your competitors and competing on the same set of beliefs, it’s hard to find a sustainable edge. Understanding the game they’re playing, and their rules are important, but that’s table stakes.

Figuring out where you can find extra insight, or where you can make the invisible visible, creates a moat between you and your competition, and it lets you play your own game.

I shot a video where I talk high-level about Data as fuel for your business. Check it out.

 

 

It is interesting to think about what’s driving the new world (of trading, of technology, of AI, etc.) and that often involves identifying what drove the old world. History has a way of repeating itself.

Before e-mails, fax machines were amazing. Before cars, you were really happy with a horse and buggy.

It’s in these comparisons that I think we can help explain the importance of data in today’s new world economics.

via gapingvoid

Data as the New Oil

Petroleum has played a pivotal role in human advancement since the industrial revolution; it fueled (and still fuels) our creativity, technology advancements, and a variety of derivative products. There are direct competitors to fossil fuels that are gaining steam, but I think it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.

The process of pumping crude oil out of the ground and transforming it into a finished product is far from simple, but anyone can understand the process at a high-level. You have to locate a reservoir, drill, capture the resource, and then refine it to the desired product – heating oil, gasoline, asphalt, plastics, etc.  

The same is true for data.

You've got to figure out what data you might have, how it might be useful, you have to figure out how to refine it, clean it, fix it, curate it, transform it into something useful, and then how to deliver it to the people that need it in their business. And even if you've done this, you then have to make people aware that it's there, that it's changing, or how they might use it. For people who do it well, it's an incredible edge.  – Howard Getson

Data can be seen as the fuel to the information economy and oil to the industrial economy. The amount of power someone has can be correlated to their control of and access to these resources ... and, leaking of these resources can lead to extreme consequences.

Why Data Is Better Than Oil

The analogy works, but it’s just that, an analogy, and the more you analyze it, the more it falls apart. Unlike the finite resource that is oil, data is all around us and increasing at an exponential rate, so the game is a little different:

• Data is – ultimately – a renewable resource. It’s durable, it’s reusable, and it’s being produced faster than we can process it.
• Because it’s not a scarce resource, there’s no urge to hoard it – you can use it, share it, transform it, infinitely knowing that it won’t diminish. Data is more useful the more you use it.
• As the world’s oil reserves dwindle, and renewable resources grow in popularity and effectiveness, the relative value of oil drops. It’s unlikely that will happen to data.
• Also, while data transport is important, it’s not expensive the way oil is. It can be transported and replicated at light speed.

Using alternative data gives traders an advantage, but it doesn’t always have to be confidential or hard to find information. Traders now have access to vast amounts of structured and unstructured data. An important source that many overlook is the data produced through their own process or the metadata from their own trades or transactions.

In the very near future, I expect these systems to be able to go out and search for different sources of information. It's almost like the algorithm becomes an omnivore. Instead of simply looking at market data or transactional data, or even metadata, it starts to look for connections or feedback loops that are profitable in sources of data that the human would never have thought of. – Howard Getson

In a word of caution, there are two common mistakes people make when making data-driven decisions. First, people often end up slaves to the data, losing focus on the bigger picture. Second, even the most insightful data can’t predict black swans.  It’s important to exercise caution.

The future of data is bright, but it’s also littered with potential challenges. Privacy concerns and misuse of data have been hot button topics, as have fake news and the ability of systems to generate misleading data. In addition, as we gain access to more data, our ability to separate signal from noise becomes more important.

The question becomes, how do you capitalize on data, without becoming a victim to it? 

Food for thought!

Taking Stealing To The Next Level: Baseball and Machine Learning

Baseball signals are purposely confusing to keep them a secret.  Attempting to decode your opponents' signals is part of the game. As it turns out, machine learning is pretty good at figuring them out. 

Mark Rober, a former NASA engineer on the Curiosity Rover, put together a good video showing its efficiency. It's an interesting application and a pretty good introduction to machine learning. It did the rounds in my office, and we liked it. 

 

via Mark Rober

So, what do you think, should we make this legal in the MLB?

Here Are Some Links For Your Weekly Reading - July 14th, 2019

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

 

Lighter Links:

• How Did NASA Put Men on the Moon? One Harrowing Step at a Time. (Washington Post)
• 55 Dr. Seuss Quotes for the Places You'll Go. (DevelopGoodHabits)
• Nick Saban on the 5 Choices We Have in Life. (LeadershipNow)
• How to Turn on Fall Detection on Your Apple Watch Series 4. (Mactrast)
• When Charlie Chaplin Entered a Chaplin Look-Alike Contest & Came in 20th Place. (OpenCulture)

Trading Links:

• Electric Vehicles are Outperforming the Traditional S-Curve Dynamics. (SeekingAlpha)
• Are Drones Really the Future of Delivery? [Infographic]. (B2C)
• The World's Biggest Potential IPO May Be on Again. (Economist)
• Moody's Economist: We'll See the Markets 'Tank' If the Fed Doesn't Cut Rates. (Finance)
• Trump Picks Another Fed Member Who Believes in the Gold Standard. this One Really Means It. (CNN)

 

 

Biohacking Gone Wild

Dave Asprey is perhaps the most well-known biohacker (he's even referenced in Merriam-Webster's definition of biohacker) and the founder of Bulletproof. For those that don't know, a biohacker is someone who uses drugs and technology to make their body/mind function better. 

Dave and I shot a video where he discusses life and provides an interesting take on algorithms. 

 

 

It's not surprising that biohacking has become as popular as it has. In a society that encourages (maybe even necessitates) an impossible balance between work, responsibilities, and self-care - it makes sense to want to increase efficiency. 

Biohacking helps you do more with less. Biohacking is popular because you're trying to get peak performance via the path of less resistance.

Having trouble with sleep, but don't want to stop using your phone before bed? Wear blue-light blocking glasses. 

Not getting enough results at the gym? Work out "smarter" not harder, by using cryotechnology and intelligent lifting machines. 

While biohacking started as tricks like that - nootropics to help your mind, light and sound machines to decrease stress - it's becoming increasingly tech-centric and augmentation based. 

Several months ago, I shared Gartner's hype cycle for 2018. Do-It-Yourself Biohacking was one of 5 encompassing trends for the year. 

The future is bringing implants to extend humans past their perceived limits and increase our understanding of our bodies; biochips with the potential to detect diseases, synthetic muscles, and neural implants. - Howard Getson

It's estimated that over 100,000 people already have various types of implants. In Sweden, thousands of Swedes are inserting chips under their skin to speed up their daily routines. They use chips to open locked doors, to store contact information, and to get on to the train. Currently, chips are limited to simple tasks like unlocking doors, holding personal data, and tracking simple to record data.

Longterm, it's likely you'll see it moving toward exoskeletons, AR/XR experiences, and unsurprisingly to sex toys. It's also being used to create artificial organs and counteract memory loss.  The two companies that are leading this movement are Neuralink,  Biohax International and Digiwell. While it's currently being adopted primarily by fast-movers and technocrats, it's pragmatic to think there will be more widely-adopted versions of this as technology gets standardized and protections are put in place. 

For all the excitement, it's necessary to remain skeptical and patient. DIY biohacking raises various ethical issues, especially around data protection and cybersecurity. As a reminder, when it comes to cybersecurity, you "the user" are the biggest weakness.

There's no stopping this train, but there is time to make sure it stays on tracks!

Onwards!

by the way, I highly recommend the Bulletproof product line!

Replicas: Deep Fakes and Voice Replication

Fake news was scary enough ... but now it is going to a new level.  Technology is going to make it harder to find the “signal” in the “noise”.

Here is a preview of tech solutions (which already exist) that are likely to create a new set of problems and challenges for us in the future.

Replica is a company whose goal is to replicate celebrity voices. They see this as enabling creative applications of their voices without the commitment of the celebrity - of course the owner of the voice that's being replicated would control when/where it could be used.

Here's a video introducing Replica. 

 

 

Combine that ability to simulate voices with deepfake technology (which can alter video in many ways, including to look like the mouth in the video is is saying the words that were simulated) and the potential for confusion or deception skyrockets. 

Here is an example.

 

 

My guess is that you will hear a lot more about this soon because of upcoming elections.  It will also become increasingly relevant in everyday life, business, trading, and legal situations.

A picture used to be worth a thousand words, but this may change that equation forever.