“I was asked twice. [by members of Parliament]’Mr Babbage, if you put the wrong number into the machine, will it give you the right answer?’ I don’t quite understand the kind of confusion of ideas that would lead to such a question.”
– Charles Babbage, Passages from the Philosopher’s Life (1864)
Press the AI button
Do you put glue on your pizza to keep the cheese from slipping?
It was pizza making guideline Provided by Google’s AI Overview tool.
When making pizza: “You can also add about 1/8 cup of non-toxic glue to the sauce to make it stickier.”
The origin of artificial ‘intelligence’ was an 11-year-old Reddit comment from a Joker whose username is too vulgar to be published on this page. Hint: It starts with the letter F.
Any reader who has tried to learn a new language as an adult will know that slang and humor are often the most difficult aspects to understand. AI tools also seem to struggle with this.
In this example, even the most ignorant aspiring chef can easily figure out that the instructions to add glue to the pizza sauce were clearly intended as a joke. No one, not even a child, would take this seriously.
But the AI bots didn’t get the joke. They thought it was valid, practical advice.
The promise of AI is that it can be better, smarter, and faster than humans. With enough graphics processing units (GPUs), people don’t have to think anymore. They can let AI do the thinking for them and focus on more satisfying activities in life, like sitting around and watching TikTok videos all day.
Don’t want to pay taxes? Too lazy to write a research paper on a 5th century monk? Want to know the top 10 biotech stocks with the biggest moonshot potential? Want to use AI to execute leading market wave patterns?
Don’t think about it. Just press the AI button.
Stitching sentences
From what we can tell, generative AI uses prompts to create a collage of search engine results. It then uses common connectives or transition words to connect sentences. The output is pretty ordinary.
You may have noticed that Amazon has included AI-generated reviews at the top of their customer reviews. They start with the words “What our customers say.” The content is an official summary of the review.
The first sentence tells what the customer likes about the product. Then comes a sentence that starts with “for example” and lists several features and benefits. Then comes another sentence about what the customer “also likes.” Then comes a transition sentence that says “you said so,” followed by a common customer complaint.
The content reads like a jumble of nouns, verbs and adjectives. It also has a very synthetic and unorthodox – artificial – look and feel.
Amazon has added these AI-generated summary reviews as a solution. Review fatigue. It’s such a shame that AI-generated review collages are such a waste of time. Why rely on AI vomit when you can quickly read real reviews from real people?
The pizza glue example illustrates a common shortcoming of AI-generated text: AI in its current state lacks a true understanding of context, sarcasm, nuance, and ultimately the quality and accuracy of its output.
Perhaps, if not already, AI will derive content from previously generated AI content. Are you prepared for the jobberworship? The output will be a deeply hierarchical cluster of Lewis Carroll-like gibberish and nonsense without any charm.
Where is the value?
The future is so bright
The supposed value of AI is not what it is today. Rather, it is a promise of what it could be tomorrow.
Bulls love stories, especially stories centered around new technologies.
The automobile, the telephone, moving pictures, radio, and aviation were the vehicles that drove the boom of the 1920s. Whatever captivated investors in the late 1990s was the dot-com.
These new technologies proved to be real. But many of the companies that pioneered them quickly failed. And even those that lasted, such as Radio Corporation America (RCA), experienced volatility, with stock prices soaring and then crashing, leaving investors devastated.
Have you heard of the Pierce Arrow Motor Car Company? On January 12, 1928, the company’s president, Myron E. Forbes, said: “Our eternal prosperity will not be interrupted.”
Unfortunately, the permanent prosperity was severely disrupted within 24 months. Within 10 years, the luxury car manufacturer was insolvent and its assets were auctioned.
Like the late 1990s, investors in the 20s thought they were getting rich. They drove stock prices way higher than corporate earnings could justify. Eventually, the bubble burst and a brutal bear market ensued.
The promise of AI has provided a fertile technology story for bullish sentiment. It’s been 21 months since OpenAI released its ChatGPT chatbot, and it’s been incredibly exciting.
Real tech companies with real products and services like Microsoft, Google, Apple got into the game. They didn’t want to be left behind. It didn’t matter how good the AI application was, if you had enough GPUs, it would be good in the end.
How to catch a falling knife
At Economic Prism, we don’t ignore AI. We believe that AI applications will become widespread quickly, whether you like it or not. They already are. We believe that the value lies in focused applications, not in designing AI bots to think and act like humans.
But that doesn’t mean investors shouldn’t try to understand the value of what they’re investing their hard-earned capital in. Since ChatGPT launched, many investors have been blinded by the bright lights of easy money and have recklessly put their capital at risk.
NVIDIA, a company that supplies cutting-edge GPUs that enable AI processing, has become a leading player in the AI bull market.
Investors are hooked. On June 18, NVIDIA’s market cap hit $3.3 trillion. If NVIDIA were a country, it would be the world’s sixth-largest economy.
There has been some gas in the tech sector over the past seven weeks. As of the close of trading on August 8, and despite a significant market rally, NVIDIA’s market cap was $2.6 trillion. That’s more than $700 billion in investor capital wiped out in less than two months.
Likewise, NVIDIA’s stock price peaked at $135.58 on June 18 and then fell to $104.97, a loss of 22.5%. Should you buy when it’s down?
We have no doubt that NVIDIA is a great technology company, but as investors, we need to ask ourselves what stock price is worth our capital.
Like Buffett, we want to buy great companies at fair prices. And as far as we know, the AI story is way ahead of the AI reality. In other words, AI alone doesn’t justify NVIDIA’s peak valuation of $3.3 trillion.
Would $80 a share be okay? How about $60 a share?
Not for our money.
We expect a 70% top-to-bottom decline before interest levels spike, which would put NVIDIA’s entry price at around $40 per share.
To put it another way, considering the 10:1 stock split that took place on June 7, NVIDIA’s stock price would be where it was on October 31, 2023, or last Halloween night.
At $40 a share, Nvidia’s market cap would be $984 billion. By comparison, that’s significantly higher than Exxon Mobility’s market cap of $523 billion. Does that seem a bit exaggerated?
Maybe so. But at that price, and assuming earnings don’t decline much, we’re willing to take the risk and apply dollar-cost averaging when the stock bottoms around $20.
In the meantime, try to catch the falling knife. With a little luck, your finger won’t get cut off.
[Editor’s note: It really is amazing how just a few simple contrary decisions can lead to life-changing wealth. And right now, at this very moment, I’m preparing to make a contrary decision once again. >> And I’d like to show you how you can too.]
thank you,
MN Gordon
For Economic Prism
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