“Challenges make life interesting. Overcoming them makes life meaningful.”
One of the biggest and most talked about trends today is Artificial Intelligence and its ‘coming of age’.
I say ‘coming of age’, because Artificial Intelligence, in various forms, has been with us for some time.
Do you use a voice assistant such as Alexa or Siri? You are using AI technology.
How about customer service chatbots that seem to be everywhere? AI!
Artificial Intelligence was first discussed in 1950 with the publication of Alan Turing’s paper “Computing Machinery and Intelligence”.
Turing, a mathematical genius, is famous for building a ‘computer’ that could break the Nazi code called Enigma during WW2 and saving the lives of millions of people as a result. He envisioned a day when computers could do even more amazing things.
The term Artificial Intelligence was coined in 1955 by John McCarthy of Dartmouth.
In 1980, the first meeting of the Association for the Advancement of Artificial Intelligence (AAAI) was held at Stanford and continues today.
Standing on the shoulders
It feels as though AI has come into our lives at warp speed. Yet, from AI concept to ChatGPT has taken 72 years!
AI stands on the shoulders of a long list of technology enablers.
These include massively parallel processing computers operating on super high-speed networks in data centers around the world requiring terabytes to petabytes to exabytes of storage capacity.
An Exabyte is 1 Billion Gigabytes!
In 1969, the year men walked on the moon, a 10,000 sq. foot data center could not hold even 1 Gigabyte of data due to the size of the data storage units themselves, as well as the electrical power and cooling units required to support a Gigabyte of storage.
In 1969 dollars it cost more than $5M for all of the peripherals mentioned.
Today an iPhone 12 can hold 256 GB and costs $749 + the cost of the phone!!
It has taken considerable time for all the supporting technologies to develop and be in place for AI to be successful including a significant reduction in costs.
An excellent time line of the evolution of AI to the present can be found here.
But nothing stands still, especially technology innovations.
In the interim, much success has taken place in the development and enhancement of algorithms, which can be simple or quite complex requiring thousands of lines of code.
According to the Wall Street Journal, “A trading algorithm can be fundamentally driven – meaning it is based on old fashioned company metrics –or based on quantitative signals such as a sweep of buying interest known as momentum [aka trend following] or technical factors like a particular stock breaking through a 30-day average price. Or, it can be all three.” The Wall Street Journal
How is AI unique?
According to consulting firm, McKinsey, “AI is a machine’s ability to perform the cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with an environment, problem solving, and even exercising creativity.”
AI is also an umbrella term that includes machine learning.
“Machine learning is a subset of AI that uses algorithms trained on data to produce models that can perform complex tasks.”
Trending Stocks has developed highly complex algorithms to analyze raw stock market data in order identify trending stocks.
It then utilizes additional proprietary algorithms to rate and rank each trending stock.
We do not use algorithms to make future stock predictions.
In our view, the state of the art is not there yet, and may not be for some time, to accurately predict the future of price movements.
The downside risk of rushing a solution could be very great.
However, algorithmic trading is very common. In fact, 60% to 75% of trading is done algorithmically to execute specific, split-second trades to gain price advantage.
Here are two ways to think about investing in AI –
1. The companies who are providing the AI infrastructure such as Nvidia;
2. The companies that will benefit the most from the use of AI potentially providing competitive advantage.
Industries interested in AI include, but not limited to: health care, financial services, retail and e-commerce, manufacturing.
The functions seem endless including: HR, customer service, driver assist systems, GPS, fraud detection, product design and quality, robotics, etc. etc.
The opportunities will continue to grow as more functionally specific applications are developed for each industry.
The biggest initial constraint and limitation may be trust.
That Pesky Word – Trust
As I read more and more about the complexities and the potential benefits of AI and ChatGPT I am reminded of the caveat by McKinsey:
“Generative AI is not without its risks. Generative-AI models [such as ChatGPT] will confidently produce inaccurate, plagiarized, or biased results, without any indication that its outputs may be problematic. That’s because the models have been trained on the internet, which is hardly a universally reliable source. Leaders should be aware of these risks before turning to generative AI as a business solution.”
A study by University of Chicago, Booth School of Business*, researchers Alex Kim, Max Muhn and Valeri Nikolaev concluded, “It [ChatGPT] could save [investors] the time and effort of poring over complex documents [Annual and Quarterly Reports, Earnings Calls] and help them to better process the most important information.” (Chicago Booth Review 2023)
They can follow a Trend Following strategy and let Trend Stocks provide them all the data they need in seconds at the touch of a button!
We look forward to the evolution of this incredible new technology and the opportunity to bring it to the DIY retail investor.
*My alma mater
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