- Artificial intelligence (AI) has become the tech world’s golden child
- Some companies have struck it rich in this AI boom
- AI boom isn’t limited to established tech giants
By Antony Muchiri, Founder and Editor in Chief Tech with Muchiri
Artificial intelligence (AI) has become the tech world’s golden child, attracting unprecedented hype and funding in recent years.
And while AI isn’t exactly the new kid on the block, OpenAI’s dramatic entrance with ChatGPT in November 2022 sparked a veritable gold rush. Suddenly, everyone and their grandmother seemed to be jumping on the AI bandwagon.
Some companies have struck it rich in this AI boom. Take NVIDIA, for instance. They’ve ridden the wave to become the world’s most valuable company, outshining even tech titans like Microsoft and Apple.
But as I watch this AI frenzy unfold, I can’t help but wonder: are we witnessing the inflation of an AI bubble that’s destined to pop?
The parallels to the dot-com bubble are hard to ignore. If you’re an old folk like myself, you’ll remember that wild ride – a period of irrational exuberance over internet-based companies in the late ’90s and early 2000s.
That bubble swelled to dizzying heights around 2000 before bursting spectacularly. The aftermath? A trail of defunct “dot-coms” and a sea of red in investors’ portfolios.
In my quest to answer the AI bubble question, I stumbled upon an intriguing Investopedia article. It outlines the five stages of a financial bubble: displacement, boom, euphoria, profit-taking, and panic.
Let’s play detective and see how closely the AI craze matches this pattern.
Act I: Displacement
Every bubble needs a catalyst, a disruptive force that captures the public imagination and rewrites the rules of the game. For the AI bubble, that moment came on November 30, 2022, when OpenAI unleashed ChatGPT upon an unsuspecting world.
The impact was immediate and profound. People were captivated by the ability to engage in seemingly intelligent conversations with a machine. It was a “seeing is believing” moment that crystallized the potential of AI for the masses.
To truly appreciate the significance of this moment, we need to draw a parallel to another technological watershed: the launch of Mosaic, the first user-friendly web browser, in 1993.
Just as Mosaic suddenly made the abstract concept of the “World Wide Web” tangible and accessible, ChatGPT did the same for AI.
It was the moment when the penny dropped, and the world collectively realized, “So this is what all the fuss about AI has been about!”
Act II: Boom – The AI Arms Race Begins
With the cat out of the bag, thanks to ChatGPT, the tech industry found itself in a frenzied state of FOMO (Fear of Missing Out).
It quickly became apparent that all the major players had been quietly developing similar technologies for years, but had been too cautious (or perhaps too wise) to release them to the public.
Microsoft, in a stroke of strategic brilliance, had already positioned itself at the forefront of this new AI landscape through its investment in OpenAI.
This move gave the tech giant privileged access to the powerful GPT-4 model, leaving competitors scrambling to catch up.
Google, long considered a leader in machine learning, found itself in the uncomfortable position of playing catch-up.
In a hasty attempt to assert its AI dominance, the search giant rushed out its Bard chatbot before it was truly ready for prime time.
The result? A chorus of derision from tech enthusiasts and a blow to Google’s reputation as an AI innovator.
But the AI boom wasn’t limited to established tech giants. Just as the early days of the internet saw a proliferation of startups, the AI revolution sparked a new generation of entrepreneurial ventures.
These nimble startups saw the potential to build innovative applications on top of the “foundation” models created by bigger players, much like how early internet entrepreneurs-built businesses on the infrastructure of the World Wide Web.
Venture capitalists, always on the lookout for the next big thing, were quick to open their checkbooks. But it wasn’t just traditional VC firms fueling this boom.
Tech behemoths and hardware manufacturers like NVIDIA also jumped into the fray, pouring vast sums into promising AI startups.
Act III: Euphoria – When AI Dreams Take Flight
As we survey the current AI landscape, it’s clear that we’ve entered the euphoria stage of the bubble. This is the point where caution is thrown to the wind, and even normally level-headed business leaders seem to lose touch with reality.
Take, for example, the ambitious plans of OpenAI’s CEO, Sam Altman. He’s been floating the idea of raising a mind-boggling $7 trillion (yes, trillion with a “T”) from Middle Eastern petrostates to fund the development of AGI (Artificial General Intelligence) – the holy grail of AI that would match or surpass human-level intelligence across a wide range of tasks.
Not content with just one moonshot project, Altman is also collaborating with Microsoft on the “Stargate” supercomputer, a venture with a price tag of $100 billion.
These astronomical figures are predicated on a simple, yet potentially flawed, assumption: that creating superintelligent machines is merely a matter of amassing more data and more computing power.
The strange thing is, at least for now, the world seems to be taking these grandiose visions at face value.
It’s reminiscent of the dot-com era when any business plan, no matter how far-fetched, could attract millions in funding as long as it was sufficiently “internet-y.”
Act IV: Profit-Taking – The First Signs of Doubt
While we haven’t fully entered the profit-taking stage of the AI bubble, some cracks are beginning to show in the façade of unbridled optimism.
This is typically the point where savvy investors, sensing that the party can’t last forever, start to quietly cash out their chips.
The challenge with the current AI boom is that, outside of hardware manufacturers like NVIDIA, very few companies are actually turning a profit from AI technology.
Even the poster child of the AI revolution, OpenAI, is reportedly facing financial difficulties. A recent report by The Information suggests that OpenAI could be racking up bills of at least $8.5 billion this year, leading to speculation about potential bankruptcy.
This stark reality check highlights a fundamental truth about the current state of AI: it’s incredibly good at spending money, but not so great at generating returns on investment.
It’s a sobering reminder that even the most revolutionary technology needs a viable business model to survive in the long term.
Act V: Panic – The Burst on the Horizon?
While we haven’t yet reached the panic stage of the AI bubble, history suggests that it’s not a matter of if, but when.
The final act of a bubble is typically characterized by a rapid downturn as investors and companies frantically try to minimize their losses.
Several factors could potentially trigger the bursting of the AI bubble:
- Government Intervention: As AI’s influence grows, regulators may step in to impose stricter controls on its development and deployment.
- Shareholder Pressure: Investors may eventually tire of pouring money into AI projects with no clear path to profitability.
- Environmental Concerns: The massive energy consumption required for AI development and deployment could face increasing scrutiny in an era of climate consciousness.
- Technological Limitations: We may hit unforeseen roadblocks in AI development that temper the current sky-high expectations.
The Million-Dollar Question: Are We in an AI Bubble?
After examining the evidence, it’s hard to escape the conclusion that we are, indeed, in the midst of an AI bubble.
The patterns of irrational exuberance, massive investments, and unrealistic expectations bear a striking resemblance to previous tech bubbles.
However, it’s crucial to remember that the existence of a bubble doesn’t negate the transformative potential of the underlying technology. The internet, after all, did go on to reshape our world even after the dot-com bubble burst.
The challenge for investors, companies, and society at large is to navigate this period of intense innovation and speculation without losing sight of AI’s long-term value and potential risks.
We need to strike a balance between enthusiasm for AI’s possibilities and a clear-eyed assessment of its current limitations and challenges.
As we marvel at the latest AI breakthroughs and ponder the possibility of artificial general intelligence, we must also remain vigilant.
History teaches us that periods of rapid technological change are often accompanied by financial instability. The key is to learn from past bubbles without stifling the innovation that drives progress.
In the end, the AI revolution is undoubtedly reshaping our world in profound ways. But as we ride this wave of technological change, we’d do well to remember the lessons of the dot-com era. Excitement is warranted, but so is caution.
After all, in the world of tech bubbles, what goes up must eventually come down – the only question is how soft (or hard) the landing will be.
