Trillion Dollar Tech: Riding the AI Wave or a Looming Bubble

I'll never forget someone explaining the difference between a million and a billion in a way that shattered my perception of scale. They said: a million seconds is just 11 short days. But a billion seconds? That's a whopping 31 years! 🤯

It blew my mind. Even though I knew, intellectually, that a billion was bigger, I hadn't truly grasped the exponential leap. Adding a few zeros might seem insignificant, but it creates a universe of difference.

Taking the next leap in scale means adding a dozen zeros – that's a trillion, a number so vast it pushes the boundaries of human comprehension. While we can grasp millions and even billions to some extent, trillions become an abstract concept. A trillion seconds? That's a mind-boggling 31,000 years!⏳

So why this fascination with a trillion and what has it got to do with AI? Well as of this week the top five companies in the US based on market capitalisation are:

Fuelled by AI announcements at its developer conference, Apple briefly reclaimed the world's most valuable company title, though Microsoft quickly regained the top spot. This trillion-dollar club is seeing explosive growth – just six years ago, Apple became the first member in 2018! What's driving this surge, and can it last?

Beyond their excellent products and services, these trillion-dollar companies have also thrived due to the recent AI boom. This boom is fuelled by several key factors:

• Surging computational power: Cloud computing and powerful chips provide the muscle for AI to run complex tasks.
• Big Data: Social media and internet activity generate massive datasets, the lifeblood of AI training.
• Smarter algorithms: Advancements in algorithms enable AI systems to learn and perform tasks with ever-greater effectiveness.
• Innovation on overdrive: Increased investment in AI research and development has accelerated breakthroughs and brought new technologies to market faster.

This AI boom creates a steep entry point. The above factors all require hefty investments. Traditional fundraising simply can't keep up. Even affluent investors like hedge funds, billionaires, and established corporations struggle to compete in this resource-intensive race. The capital needed to train complex AI models, like ChatGPT, is out of reach for many.

How do the valuations look in comparison to traditional financial metrics? Without going too deep into earnings, margins or cash reserves I am going to keep it relatively simple and focus on Revenue and Employee numbers.

💲Revenue

While NVIDIA* stands out, the revenue compared to market cap for most companies on this graph seems relatively balanced. This suggests that, despite heavy R&D investments in AI infrastructure, valuations might be justified based on their future potential, not just current revenue.

* NVIDIA has experienced remarkable growth over the past 12 months. Specifically, its stock has surged by 222.59%, outperforming the broader market (S&P 500) by a significant margin (which grew by 26.72% during the same period). NVIDIA's GPUs (graphic processing units) are essential for AI development and they dominate the data centre market.

👩‍🏭👨‍💻👨‍💼👩‍💼Employees

Employee headcount across these tech giants is surprisingly similar, with NVIDIA the only outlier. This reflects a broader shift in the industry – from labour-intensive to capital-intensive.

Compared to the top 5 US companies in 1960, we see a dramatic decrease in workforce size, highlighting the move away from reliance on physical labour.

While the investment required in tech is substantial, the returns are enormous. The lack of variable labour costs dramatically reduces marginal costs, even approaching zero in some cases. This generates super-profits unlike anything we've seen before, placing immense responsibility on these trillion-dollar companies to act ethically.

The comparison between these tech giants and the top 10 economies by GDP underscores the urgent need for the need for mechanisms to hold these companies accountable for their actions.

Collectively, the trillion-dollar club trumps the economies of all but two nations (with some overlap from US tech giants, of course). Even individually, some of these companies surpass the GDP of most countries, wielding unimaginable power and influence.

The recent surge in tech stock valuations reflects a belief that AI will drive massive economic growth. However, this investment boom is limited to a select few. To ensure societal benefit, the rewards need to be more widely shared. Unchecked dominance by a handful of West Coast US companies (three Californian and two Seattle-based) could lead to a dystopian future with stifled competition, unrestricted data sharing, and widening economic disparity. Proactive regulation that addresses these concerns can ensure everyone enjoys the potential of AI, not just a privileged few.

What are your biggest concerns about the trillion-dollar club? Does concentrating AI power in the hands of a few tech giants pose a risk?