Capitalogix

Can AI Be Curious?

“Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.” —Sebastian Thrun

We often use human consciousness as the ultimate benchmark for artificial exploration. 

The human brain is ridiculously intricate.  While weighing only three pounds, it contains about 100 billion neurons and 100 trillion connections between them.  On top of the sheer complexity, the order of the connections and the order of actions the brain does naturally make it even harder to replicate.  The human brain is also constantly reorganizing and adapting.  It's a beautiful piece of machinery.  

We've had millions of years for this powerhouse of a computer to be created, and now we're trying to do the same with neural networks and machines in a truncated time period.  While deep learning algorithms have been around for a while, we're just now developing enough data and computing power to change deep learning from a thought experiment to a real edge. 

Think of it this way, when talking about the human brain, we talk about left-brain and right-brain.  The theory is that left-brain activities are analytical and methodical, and right-brain activities are creative, free-form, and artistic.  We're great at training AI for left-brain activities (obviously with exceptions).  In fact, AI is beating us at these left-brain activities because a computer has a much higher input bandwidth than we do, they're less biased, and they can perform 10,000 hours of research by the time you finish this article.

It's tougher to train AI for right-brain tasks.  That's where deep learning comes in. 

Deep learning is a subset of machine learning based on unsupervised learning from unstructured/unlabeled data.  Instead of asking AI a question, giving it metrics, and letting it chug away, you're letting AI be intuitive.  Deep learning is a much more faithful representation of the human brain.  It utilizes a hierarchy of convolutional neural networks to handle linear and non-linear operations so it can think creatively to better problem-solve on potentially various data sets and in unseen environments. 

When a baby is first learning to walk, it might stand up and fall down.  It might then take a small stutter step, or maybe a step that's much too far for its little baby body to handle.  It will fall, fail, and learn.  Fall, fail, and learn.  That's very similar to the goal of deep learning or reinforcement learning. 

What's missing is the intrinsic reward that keeps humans moving when the extrinsic rewards aren't coming fast enough.  AI can beat humans at many games but has struggled with puzzle/platformers because there's not always a clear objective outside of clearing the level. 

A relatively new (in practice, not in theory) approach is to train AI around "curiosity"^[1].  Curiosity helps it overcome that boundary.  Curiosity lets humans explore and learn for vast periods of time with no reward in sight, and it looks like it can do that for computers too! 

OpenAI via Two Minute Papers

Soon, I expect to see AI learn to forgive and forget, be altruistic, follow and break rules, learn to resolve disputes, and even value something that resembles "love" to us.

Exciting  stuff! 

_______

[1] - Yuri Burda, Harri Edwards, Deepak Pathak, Amos Storkey, Trevor Darrell and Alexei A. Efros.  Large-Scale Study of Curiosity-Driven Learning
In ICLR 2019.

Here Are Some Links For Your Weekly Reading - July 17th, 2022

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

Lighter Links:

• Biden is Very Unpopular. It May Not Tell Us Much About the Midterms. (FiveThirtyEight)
• The 23 Best New Productivity Apps for 2022. (FastCompany)
• Meet the Man Keeping Blockbuster Alive. (DallasNews)
• Was Warfare Responsible for the Origin of Complex Civilisation? (NewScientist)
• Create an Action Figure Version of Yourself With Hasbro's "Selfie Series". (Hypebae)

 

 

 

 

Trading Links:

• Does Elon Musk Have a Strategy? (HBR)
• JPMorgan CEO Dimon Sums up U.S. Economy in One Paragraph And It Sounds Bad. (CNBC)
• Where Did the Stock Market's $7 Trillion Loss in Value Go? (Marketplace)
• The Speedy Downfall of Rapid Delivery Startups. (Wired)
• Why Hasn't the Russian Economy Tanked Yet? Putin Has Been Preparing for this Moment for Years. (Fortune)

 

 

 

Reinventing The Wheel

When I think about the invention of the wheel, I think about cavemen (even though I know that cavemen did not invent the wheel).

Lots of significant inventions predated the wheel by thousands of years.  For example, woven cloth, rope, baskets, boats, and even the flute were all invented before the wheel.

While simple, the wheel worked well (and still does).  Consequently, the phrase "reinventing the wheel" often is used derogatorily to depict needless or inefficient efforts.

But how does that compare to sliced bread (which was also a pretty significant invention)?

Despite being a hallmark of innovation, it still took more than 300 years for the wheel to be used for travel.  With a bit more analysis, it makes sense. In order to use a wheel for travel, it needs an axle, and it needs to be durable, and loadbearing, requiring relatively advanced woodworking and engineering. 

All the aforementioned products created before the wheel (except for the flute) were necessary for survival.  That's why they came first.

As new problems arose, so did new solutions.

Necessity is the mother of invention. 

Unpacking that phrase is a good reminder that inventions (and innovation) are often solution-centric. 

Too many entrepreneurs are attracted to an idea because it sounds cool. They get attracted to their ideas and neglect their ideal customer's actual needs. You see it often with people slapping "AI" on to their product and pretending it's more helpful. 

If you want to be disruptive, cool isn't enough. Your invention has to be functional, and it has to fix a problem people have (even if they don't know they have it.) The more central the complaint is to their daily lives the better.  

Henry Ford famously said: “If I had asked people what they wanted, they would have said faster horses.”

Innovation means thinking about and anticipating wants and future needs.

Your customers may not even need something radically new. Your innovation may be a better application of existing technology or a reframe of best practices. 

Uber didn't create a new car, they created a new way to get from where you want with existing infrastructure and less friction. Netflix didn't reinvent the movie, they made it easier for you to watch one. 

As an entrepreneur, the trick is build for human nature (meaning, give people what they crave or eliminate the constraint they are trying to avoid) rather than the cool new tech that you are excited about.  

Human nature doesn’t seem to change much … Meanwhile, the pace of innovation continues to accelerate. 

The challenge is to focus on what people want rather than the distraction of possibility.

It gets harder as more things become possible.

We certainly live in interesting times!

Americans' Top Financial Concern

It's no secret that the economy is slowing - with high inflation rates and rising interest rates. 

According to Mohamed El-Erian, from Queens College at Cambridge University, we're experiencing stagflation - which is when inflation is high but growth is slowing significantly. Theoretically, that leads to recession. 

via visualcapitalist

The Consumer Price Index has also grown by over 8% in the past year, so the American household is facing financial threats from many angles. 

Many feel that the Fed has responded disappointingly recently, and their response (or lack thereof) will be a major dictator of whether we enter a recession. 

I believe that emotions play a role too. When people are afraid, they spend less and hoard what they can to save themselves from an unknown future. They feel anticipatory grief.  And their fear, uncertainty, and doubt ripple through society and our lives. 

Personally, I've weathered my heaviest storms by sailing toward the future regardless of the threats. An abundance mindset is a powerful tool, and as more people feel confident it becomes a macroeconomic trend with real influence. 

I'd encourage you to think about what opportunities there are and will be. There are always seasons of change … Winter eventually comes – and goes. Nevertheless, winter can be a great opportunity to plan your next moves and build the infrastructure to sow more seeds in the coming spring. 

As well, unlike nature, you can personally have springtime while the majority are in winter. We're currently in an A.I. springtime - and I believe that will continue regardless of economic trends. 

Happy to talk about this … Let me know what you are thinking and feeling!

Here Are Some Links For Your Weekly Reading - July 2nd, 2022

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

Lighter Links:

• Musk Breaks 9-Day Silence on Twitter, Posts a Picture With the Pope. (Reuters)
• Your Internet Life Needs a Feeds Reboot Here's How to Do It. (TheVerge)
• Analysis of Compound Curse Words Used on Reddit. (FlowingData)
• The Track Record of Futurists Seems ... Fine. (Cold-takes)
• How Netflix Grew from DVD Service to a Hollywood Disruptor with Over 200 Million Subscribers That is Now Losing Customers. (Insider)

 

Trading Links:

• Here's How Long Bear Markets Last And How Stocks React When They End. (ComplianceX)
• Families May Be Offered Mortgages of 50 YEARS that They Can Then Pass to Their Children. (DailyMail)
• Amazon Delivers Some Bad News for the Economy. (TheStreet)
• Crypto's Domino Effect is Widening, Threatening More Pain. (Wall Street Journal)
• 'A Lot of People are Just Not Understanding What's Going On': A 30-Year Market Vet Lays Out 7 Reasons Why a Recession is Imminent And Says Stocks Will End the Sell-Off Down 60%. (Insider)

 

 

How Bad Were The Markets In The First Half Of 2022?

The S&P 500 has had its worst first half performance since 1970. 

via AXIOS

But, the S&P's performance isn't the only danger indicator. 

via Fortune

Stocks, bonds, crypto, and more, all saw rapid declines in the first half of 2022. 

It's hard to pin the blame on any one factor. Was it the result of the actions we took to stabilize the economy during the throes of Covid? Is it the runaway inflation, Russia, or the continuing supply-chain issues? 

It feels like everything that could go wrong – is going wrong. I mean, how often do stocks and bonds fall at the same time?

On a positive note, bear markets are often much shorter than bull markets.  Also keep in mind that while global growth is slowing, innovation isn't!

Don't forget, “Winter” for the economy or a particular industry doesn't have to be winter for you. 

Onwards! 

Companies With The Most Patents in 2021

Intellectual Property is an important asset class in exponential industries.

Why?  Because I.P. is both a property right (that increases the owner's tangible and intangible value) and a form of protection.

They say good fences make good neighbors.  But you are also more willing to work to build an asset if you know that your right to use and profit from it is protected.

As a result of that thinking, Capitalogix has numerous patents - and we're developing a patent strategy that goes far into the future.  So, it's a topic that's front of mind for me.

Consequently, this visualization of which companies got the most patents last year caught my eye.  In 2021, the U.S. granted over 327,000 patents.  Here is who got them.

 

Raul Amoros via VisualCapitalist

While IBM isn't the public-facing industry leader they once were, they've been topping the list for most patents for the past three decades.  Their patents this past year cover everything from climate change to energies, high-performance computing, and A.I.. 

What ideas and processes do you have that are worth patenting?  And, what processes are worth not patenting - to keep from prying eyes?

Food for thought ... Onwards!

Thoughtful Entrepreneur Podcast

Recently I had a chance to talk with Josh Elledge on his Thoughtful Entrepreneur podcast. We talked about AI's inevitable influence on trading as well as my experience as an entrepreneur. 

Despite mis-spelling Capital Logix ... it's Capitalogix ... the conversation we had is worth a listen. 

Check it out.  

Visualizing Oil Prices in Response to Economic Events

In the past, I've talked about where America gets its oil, and how data is more than just "the new oil". 

During the worst of the pandemic, oil prices dropped almost 40%. They've now risen 216% from that pandemic low. With gas prices skyrocketing, it's probably time to look at historical oil prices.

Visual Capitalist put together a simple infographic. 

via visualcapitalist

So why are prices so high? Unfortunately, large portions of the world's oil reserves are in regions prone to political conflict.

Currently, the Russia-Ukraine conflict is leading to supply uncertainty and rising prices.

Meanwhile, oil companies are bringing in record profits. 

Oil prices are a complicated topic because supply and demand aren't particularly responsive to price changes in the short term. Regardless of price, people need to drive. And, regardless of demand, it takes time and money to drill new oil wells. 

As a result, you can see mismatches, like today, where uncertainty has raised prices, but oil companies are doing tremendously well. 

The question now becomes ... where does it end? Does it take a resolution to the current conflict? Or, will prices reach a ceiling and fall back down based on other factors?

Dall-E .... Not Wall-E: AI-Generated Art

Neural networks creating images from text isn't new.  I wrote about it in 2019 when AI self-portraits were going viral. 

 

Mauro Martino via YouTube

Just like VR is getting a new lease on life, despite its age, AI-generated art is getting another 15-minutes of fame. 

This past week, a new model called Dall-E Mini went viral.  It creates images based on the text prompts you give it – and it's surprisingly good.  You even can give Dall-E absurd prompts, and it will do its best to hybridize them (for example, a kangaroo made of cheese). 

Unfortunately, like our current reality, Dall-E may not be able to produce cheap gas prices.  Nonetheless, it is fun to try.  Click the image to enter the concepts you want Dall-E to attempt to represent.

via Dall-E mini

While the images themselves aren't fantastic, the tool's goal is to understand and translate text into a coherent graphic response.  The capabilities of tools like this are growing exponentially (and reflect a massive improvement since I last talked about AI-generated images).

Part of the improvement is organic (better hardware, software, algorithmic evolution, etc.), while another part comes from stacking.  For example, Dall-E's use of GPT-3 has vastly increased its ability to process language. 

However, the algorithms still don't "understand" the meaning of the images the way we do ... they are guessing based on what they've "seen" before.  That means it's biased by the data it was fed and can easily get stumped.  The Dall-E website's "Bias and Limitations" section acknowledges that it was trained on unfiltered internet data, which means it has a known, but unintended, bias to be offensive or stereotypical against minority groups. 

It's not the first time, and it won't be the last, that an internet-trained AI will be offensive. 

Currently, most AI is essentially a brute force application of math masquerading as intelligence and computer science.  Fortunately, it provides a lot of value even in that regard. 

The uses continue to get more elegant and complex as time passes ... but we're still coding the elegance. 

 

Onwards!