Capitalogix

Top 10 Most Overhyped Technologies (From 2008)

Just because something is overhyped, doesn’t mean it’s bad. Gartner's hype cycle is a great example of this. Every technology goes through inflated expectations and a trough of disillusionment, regardless of whether they're a success or failure. Sometimes a fad is more than a fad. 

Humans are pretty bad at exponential thinking. We're not bad at recognizing periods of inflection, but we're very bad at recognizing the winners and losers of these regime changes. 

 

 

There are countless examples. Here's a funny one from Maximum PC Magazine in 2008. It shows that hype isn't always a sign of mistaken excess.  This list purported to show things that were getting too much attention in 2008.  Instead of being a list of has-beens and failures, many of these things rightfully deserved the attention.

 

It's been 14 years since this came out. How did the predictions hold up?

Facebook has become Meta, and is one of the big five. The iPhone has sold more than 2.2 billion phones, and accounts for more than half of Apple's total revenue. And the list keeps going. Multiple GPU video cards, HD, 64-bit computing, and downloading movies from the internet ...

It's hard to believe how poorly this image aged. 

The trend is your friend while it continues. Just because something is overhyped - doesn't mean you shouldn't be excited about it. 

Onwards!

Here Are Some Links For Your Weekly Reading - May 15th, 2022

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

Lighter Links:

• The Rich are Not Who We Think They Are. And Happiness is Not What We Think It Is, Either. (NYT)
• Robots Show Us Who We Are. (Nautilus)
• Prepare for Arrival: Tech Pioneer Warns of Alien Invasion — But It's Not What You Think.(VentureBeat)
• China Orders Government, State Firms to Dump Foreign PCs. (Bloomberg)
• China's Leader Xi Jinping is Suffering From Brain Aneurysm and Will Snub New Medicine, Reports Claim. (DailyMail)

 

Trading Links:

• No More $27 Beer; Authorities Crack Down on Out-of-Control Prices at NYC Airports. (ThePointsGuy)
• Stablecoins are Struggling to Survive the Crypto Crash. (TheVerge)
• Dollar's Strength Pushes World Economy Deeper Into Slowdown. (Bloomberg)
• Bill Gates Says There's a 'Strong Argument' We're About to See a Global Economic Slowdown. (Insider)
• America is Running Out of Baby Formula Because 3 Companies Control the Market and Babies Aren't that Profitable. (Fortune)

The OODA Loop: Making Fast Decisions

I recently came across an interesting technique that fighter pilots use to make fast and accurate decisions in high-stakes situations. 

The Air Force calls it an OODA Loop.

It is an iterative feedback model designed by Colonel John Boyd that serves as a foundation for rational thinking in chaotic situations like dogfights.

It stands for Observe, Orient, Decide, Act. 

via Wikipedia

Why do people use decision models?  Obviously, to make better decisions.  But really, they use models to create a process that avoids many of the mistakes or constraints that prevent good decisions.

You make countless decisions every day - and at a certain point, you reach decision fatigue. It can be harder to make decisions when you are tired, after you've made too many, or when the intensity of the environment distracts or drains you. 

It's one of the reasons I rely on artificial intelligence. Here are some others. 

• Best practice becomes standard practice. 
• It accounts for signal and noise.
• It attempts to quantify or otherwise make objective assessments, comparisons, and choices. 
• And, it often gives you a better perspective by letting you apply and compare different models or decision techniques to achieve the desired outcome.

Nonetheless, many algorithms are dynamic and adaptive automation of processes or strategies that humans have used successfully before.

So, let's take a closer look at the OODA Loop, which stemmed from analyzing many interactions between and among fighter pilots during battle and training. 

Observe

The first step is to observe the situation to build the most accurate and comprehensive picture possible. The goal is to take in the whole of the circumstances and environment. It's not enough to observe and collect information, you must process the data and create useful meaning. 

It's the same with data collection for an AI system. Ingesting or collecting data isn't enough. You have to be able to apply the data for it to become useful. 

Orient

This step is less intuitive but very important. When you orient yourself, you're recognizing strength, weakness, opportunity, and threat to identify how changing the dimensionality or perspective alters the outcome. 

It's reconnecting with reality in the context of your cognitive biases, your recent decisions, and more. Have you received new information since starting?

I think of this as carrying a map and pulling out a compass while exploring new lands. Sometimes you need to remember where you started, and sometimes you need to make sure you're going where you think you are. 

Decide

The last two steps provide the foundation for taking action. When there are multiple decisions in front of you, observing and orienting help you choose wisely. 

In business and with AI, you can go through these loops multiple times. 

Act 

The best-made plans mean nothing if you don't act on them. Once you've taken action, you can reobserve, reorient, and keep moving forward. 

Conclusion

Like most good mental models, The OODA loop works in many situations and industries.

Speed is often a crucial competitive advantage. For example, knowing (and taking decisive action) while others are still guessing (and taking tentative action) is something I call time arbitrage. 

Said another way, you make progress faster by walking in the right direction than by running in the wrong direction. 

These processes (and technology) also help us grow more comfortable with uncertainty and uncomfortableness. Markets are only getting more volatile. Uncertainty is increasing. But, when you have the ability to adapt and respond, you can survive and thrive in any climate. 

The Intersection of Fintech, AI, and Analytics

At the beginning of the pandemic, I participated in a series of webinars for IBM. The focus was on building smart and secure financial services. My talk was about advanced computing and the new world of trading.

Challenging times drive advancement - and what better time to talk about advancements in technology (and their applications) than in the midst of a global pandemic. 

You can watch a replay of the Fintech webinar here. There are several interesting presentations.  If you just want to watch my presentation, it starts at the 5:16 mark.

In addition, I've uploaded a different version of just my talk that you can watch directly here.

 

IBM and Capitalogix via YouTube

In the past, trading used to be about people trading with people. Markets represented the collective fear and greed of populations. So, price patterns and other technical analysis measures represented the collective fear and greed of a population. If you could capture that data and figure out certain statistical probabilities, you might have had an edge. The keywords are "might have". 

If you had more information than your competitors - meaning, an information asymmetry - you had an amazing edge. At one time, that was being able to print out reports on stocks from that new-fangled technology called the internet. As time passed, it became harder to gain an asymmetric information advantage (because people had access to more and better data). 

Each generation of traders finds new ways to play the game and generate "Alpha" (the excess return generated by manager skill, rather than luck or excess risk). As soon as enough people adopt a strategy (or figure out a way to combat it), the edge begins to decay.

When computerized data became available, simply understanding how to download and use it generated Alpha. The same could be said for each later evolution – the adoption of complex algorithms, access to massive amounts of clean data, or the adoption of AI strategies.

Each time a new shift happens, traders pivot or fail – it's not that active trading stopped working – it's that the tools, speed, and styles necessary to play that game evolved.

Said another way, the rules, the players, and the game (itself) have all changed. Today, technological asymmetry is a significant factor, and your edges come from things like bigger and faster servers, low latency connections to markets, or the ability to calculate the odds better or faster than others.

In the future, I see those edges combining as artificial intelligence starts to leverage exponential technologies and new data sources (like alternative data and metadata feedback loops). It is easy to imagine a time when information is the "fuel," but your ability to digest and parse that information is the "engine." 

Playing a New Game

Historically, most active traders don't beat the S&P in any given year ... and even less beat it with any semblance of consistency.  But those that do – the ones that have been doing it for long enough that it's not chance ... exercise a willingness (and a skill) to adapt quickly. 

One of Charles Darwin's best-known concepts is: It is not the strongest species that survive, nor the most intelligent, but the ones most responsive to change.

While computers have made information accessible to everyone, they've also created a massive asymmetric information advantage for those who have both the access and the skill to best use the massive amounts of data now available.  This is more complicated than it seems.  You need the information, the technology, the process, and the people.  There is so much data available now that figuring out what to ignore is probably more important than what to use.  Likewise, the ability to ingest, clean, validate and curate the data is a huge hurdle that most can't clear.

I talk about much more in the video but boiling down the main points, ask yourself (in business, in trading, in life) are you separating the "signal" from the "noise?"

A technological advantage doesn't mean anything if you're plugging in inaccurate or biased data into it ... just like with the news. 

But, even with those skills, it's harder than ever to take advantage of inefficiencies (edges) than ever before.  The edges are smaller, more fleeting, and surrounded by more volatility and noise.  It's like finding a needle in a haystack.  That being said - finding a needle in a haystack is easy when you have a metal detector. 

That's where A.I. has come in for us. We use A.I. to develop algorithms, analyze markets, and create meaning where humans can't find any. 

We live in exciting times. 

Onwards!

Here Are Some Links For Your Weekly Reading - May 8th, 2022

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

Lighter Links:

• The War in Ukraine, As Seen on Russian TV. (NYT)
• Mapped: The World's Population Density by Latitude. (VisualCapitalist)
• Where Lawns are Outlawed (And Dug Up, and Carted Away). (NYT)
• Tesla's 9-Word Rule Every Employee Has to Follow is Simply Brilliant. (Inc)
• Elon Musk Says Expectations of Twitter Employees Will Be Extreme Following Takeover. (Deadline)

 

Trading Links:

• Buying Wordle Brought Tens of Millions of New Users' to the New York Times. (TheVerge)
• The Party's Ending: Silicon Valley Braces for a New Era of Financial and Political Upheaval. (NBCNews)
• Pity the Billionaire – A Profile of Marc Andreesen. (NYMag)
• Jim Bianco: The Fed Will Crush Inflation and With It, the Stock Market. (AdvisorPerspectives)
• Warren Buffett: I Wouldn't Buy All Bitcoin In the World For $25, It Has No Value. (FinBold)

Happy Mother's Day

 To those of you with young children, here's a peek into your future.

After years of hard work and your best efforts (OK, mostly your best efforts) ... I predict that your adorable bundles of joy will someday wish they could send you this card.

So, take a moment to think about your Mom ... and remember that she was very young when she did those things to you ...

... and what you make them mean is up to you.

Here's a funny clip from SNL in honor of Mother's Day.

 

via SNL

Hope you celebrated all the important mothers in your life. And, to the mothers, I hope the people around you recognize how much you sacrificed for them. 

Happy Mother's Day. 

Exposure To The Blockchain

A few months ago, I mentioned that the level of discussion around cryptocurrency and blockchain was developing. People are beginning to think about secondary and tertiary value propositions. The elevated conversations even made me think about repurposing some of our underutilized hardware in our server room for some crypto-related purposes.

While I'm still skeptical about any given currency, I believe strongly in the blockchain. Trust has been eroded. We've lost trust in our media, in big tech, and in the banks.  As a result, the blockchain economy will become more ubiquitous.

Blockchain is radically changing the future of transaction-based industries. Industry leaders are fervently evaluating and exploring blockchain to determine its potential for disruption and to create a long-term strategic advantage over their competitors.  

Blockchain is disruptive because of its ability to digitize, decentralize, and secure the validation of "transactions."  Everywhere there's a hand-off of information or goods, blockchain has the opportunity to improve that process. To not only make it safer but more efficient. 

Imagine being able to see the entire history of a property ... and know it's accurate. Not just for the property, but the land, the air rights, land rights, and more. Imagine being able to track individual shipments globally through your supply chain with ease. Imagine being able to enter/exit countries without the elongated passport check-ins or the need for a new currency.

The list goes on … Aviation, Big Pharma, Manufacturing, Finance, SaaS … In the same way that artificial intelligence is transforming what's done by humans and what's done by machines, the blockchain is transforming security and how we transfer data. If data is the new currency, blockchain is the banking system. 

Blockchain enables transparency and accountability on a radically bigger scale. 

Here are two charts that talk about the evolution of crypto and blockchain ... and various ways you can get involved. 

The first is a new graphic put together by MSCI on the rising Blockchain economy.

MSCI via visualcapitalist

It talks about the rise in crypto volume, the new trends coming to Bitcoin, and more. 

The second is a very simple chart that I first shared in 2018. It shows the non-financial uses of Blockchain. 

NewCoShift via Crowd Companies

 

I've said this before, but it's worth echoing …  Some of what was once Impossible becomes Possible.  Some of what became Possible becomes Probable. And, and some of what became Probable becomes Inevitable.

Blockchain is happening.  Technological shifts,  like this, require you to think about your industry and your potential opportunity differently.

Change is happening faster (and creating bigger edges) than ever before. 

What a great time to be an entrepreneur!

Seize the Edge!

Onwards.

 

Here Are Some Links For Your Weekly Reading - May 1st, 2022

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

Lighter Links:

• What is Web 3.0? Here's What the Internet Will Look Like In the Future. (LaptopMag)
• Amazing Video Shows a Tiny Jumping Robot Like Nothing You've Ever Seen. (BGR)
• 103 Bits of Advice I Wish I Had Known. (Kevin Kelly’s Technium)
• Does (Hand) Size Matter? Inside the NFL Draft's Fear of Tiny-Handed QBs. (GQ)
• This $2 Billion Personal Submarine is So Huge that It Can Dwarf a MegaYacht. the Vessel is Almost Three Times Longer Than a Football Field, It Has Lavish VIP Suites, a Helipad and Even an Open Deck Swimming Pool. (LL)

 

Trading Links:

• Bored Ape Metaverse Frenzy Raises Millions, Disrupts Ethereum. (Bloomberg)
• Can Capitalism Survive? 80 Years After Schumpeter's Answer. (AIER)
• Americans are Showing Inflation Fatigue, and Some Companies See a Breaking Point. (FoxBusiness)
• Foreclosure Filings are Up 132% From a Year Prior. Here's What that Means for the Housing Market (And It's Not What You Might Think). (MarketWatch)
• Warren Buffett and Charlie Munger Called Out Stock-Market Gamblers, Dismissed Bitcoin as Worthless, and Underlined the Risks of Inflation. Here are Their 12 Best Quotes from Berkshire Hathaway's Annual Meeting. (Markets)

How Tech Giants Make Their Money

In 2021, the Big Five – Alphabet (Google), Amazon, Apple, Meta (Facebook), and Microsoft - generated over $1.4 trillion in revenue.

How did they generate that revenue? We know they sell products ... but we also know that we're often the product they sell. 

Google and Facebook each make a lot of money selling you (or data about you) to advertisers. 

The image below shows how Alphabet generated its revenue.   The full infographic shows that breakdown for each of the Big Five.

Click to view the other companies via visualcapitalist

Apple, Amazon, and Microsoft, primarily sell products (like more traditional businesses). On the other hand, almost 98% of Meta's revenue (and 81% of Google's revenue) comes from advertising. 

Unsurprisingly, all five companies saw significant growth during the pandemic. 

Though the economy shrank in the past two years, societal changes continued to push demand for big tech's products and services. 

Will growth continue or slow down? 

I'm curious what you think.

How I Got Started In Artificial Intelligence

Recently, I've had several people ask about how I got into AI. 

There are a couple of different answers, but I shot a video to go through the main points. 

 

Click here for a transcript

You could argue that I got my start in AI with my most recent company - Capitalogix - which started almost 20 years ago. You could also say that my previous company - IntellAgent Control - was an early AI company, and that's where I got my start.  By today's standards, the technology we used back then was too simple to call AI ... but at the time, we were on the cutting edge.

You could go further back and say it started when I became the first lawyer in my firm to use a computer, and I fell in love with technology. 

As I look back, I've spent my whole life on this path.  My fascination with making better decisions, taking smarter actions, and a commitment to getting better results probably started when I was two years old (because of the incident discussed in the video).

Ultimately, the starting point is irrelevant. Looking back, it seems inevitable. The decisions I made, the people I met, and my experiences ... they all led me here.

However, at any point in the journey, if you asked, "Is this where you thought you'd end up?" I doubt that I'd have said yes. 

I've always been fascinated by what makes people successful and how to become more efficient and effective. In a sense, that's what AI does. It's a capability amplifier. 

When I switched from being a corporate securities lawyer to an entrepreneur, I intended to go down that path. 

Artificial Intelligence happened to be the best vehicle I found to do that. It made sense then, and it makes sense now.

I wouldn't have it any other way. 

Onwards!