FFor more than a decade, the technology industry has been defined by two economic zeroes. “Zero Interest Rate Policy” (ZIRP) across the Western world caused the price of money to plummet, allowing startups to run at a loss for years and giving investors a massive appetite for risky bets. that could bear great fruit. At the same time, the software industry’s “zero marginal cost” generated huge returns on effort, enabling situations like WhatsApp: 55 employees serving 420 million users selling Facebook for $19 billion.
But both conditions are coming to an end. Governments around the world have raised interest rates in a desperate bid to keep post-pandemic inflation in check, while the rise of AI technologies threatens the production model that brought the sector to its current dominance. . And because of that, the next decade could be very different from the last.
‘A ZIRP phenomenon’
Most of the Western world didn’t actually see interest rates go to zero, but as inflation and growth stalled after the Great Recession, rates fell enough to make no difference. In the United States, the Federal Reserve cut rates to “0.25%” in 2008 and kept them there for seven years, before gradually raising them to 2.5% in 2018 and then cutting them to near zero amid the pandemic. . In the UK, the rate was reduced from 1% to 0.5% in 2009 and did not rise again for the next 13 years.
An economic interlude: Central bank interest rates have two main effects on the economy. For one, they are effectively the “cost of money”. If you need cash, you can borrow it and pay interest on it; If the interest rate is low, you pay less for your money and can borrow more for the same price. On the other hand, they also provide investors with a “risk-free” benchmark rate of return. By lending to a central bank, you are guaranteed your money back, which sets a floor for possible investments. In fact, a zero interest rate is a low floor, leading investors to seek riskier bets that could pay off.
In the broader economy, then, low interest rates stimulate more investment, free up credit, and hopefully revive a stagnant economy.
In the technology sector, however, that general push had very specific results. With low rates of return on conventional investments, the venture capital ecosystem, one of the few legitimate financial products that attempts to offer a thousand times higher return on investment, became cash-rich. Yes, the risk was high, but with such low rates it was a risk worth taking.
And that rush of inward investment was patient. Rates were low, so it didn’t matter if the payoff was a year or a decade away: A company that could promise mega-dollars five years from now was much more compelling than one that would simply make a modest sustainable profit next quarter.
The after effects of that didn’t just change the tech sector. They defined it. Everything from “Blitzscaling” (the Uber-like practice of growing so fast that your competitors simply run out of money and go broke trying to compete with you) to seven-figure starting salaries (while bidding for engineering talent against a group of competitors who have access to the same infinite capital as you) has its roots in ZIRP.
And the effects go even further. Facebook’s huge annual profits are due in large part to its huge ad revenue, and much of it that revenue comes from venture capital-funded startups that pay big bucks to acquire customers at a loss, while competing to grow.
But ZIRP is over. Interest rates are through the roof and the cash reserve is running low. We’re already seeing some of the short-term effects of this on the industry, in the form of industry-wide layoffs and start-ups panicking to preserve their “runway”, the length of time they can survive without additional investment.
Free sushi lunches? That’s a ZIRP phenomenon. Big discounts for new users? ZIRP phenomenon. Burn money in a metaverse? Defined ZIRP phenomenon. In Silicon Valley, it has even become a vaguely fashionable insult. Does your friend not have so many dates anymore? Maybe all those Tinder swipes were a ZIRP phenomenon.
Free as in beer
Then there’s the other zero: marginal cost. The marginal cost of a product is the cost of manufacturing one more unit. It does not take into account high fixed costs, such as research and development, factories, or the salary of the CEO. But in economics textbooks, it is the cornerstone of basic pricing and supply and demand theories.
Again, the simple economic explanation is that marginal cost sets a floor for prices: if you sell a product for less than it costs to make it, you are out of business extremely quickly. And once you’ve invested the fixed cost of creating your product, it’s always worth selling more at any price above marginal cost. So, in the long run, output expands and prices fall until price equals marginal cost.
But the software messes it up. Because the marginal cost of almost anything in the world of software is so close to zero that it doesn’t make any difference. Signing up for a Facebook account, downloading an app, or reading an article on a newspaper website—all of these things have zero marginal cost.
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That means they can be, and often are, offered for free, with fixed production costs recovered in other ways: often advertising, but also revenue streams such as donations, merchandise sales, or the sale of customer data to hidden.
And then came the AI. There’s a lot to be said for the rise of generative AI like ChatGPT and Midjourney, but one of the important undertones is that it’s significantly expensive. The fixed cost of training the models has been well covered, with GPT-scale AI costing billions to train, but even getting results from a trained model is expensive, between the electricity required to operate and the risk of congestion on the data centers.
As a result, it has been estimated that a single ChatGPT indicator costs around a hundred times more than a web search, and that was before OpenAI released GPT-4, a substantially larger model that is consequently more expensive. to execute.
That’s why so much of the cutting edge in this field is subscription based. ChatGPT Plus charges users for access to GPT-4 and still limits them to one hundred queries per day, while Midjourney allows free users just 24 minutes of processing time before being prompted for a monthly subscription starting of $10.
If you want to offer generative AI to your users, in other words, you have to charge them. But that’s hard to do: We’ve spent a decade waiting for consumer technology to be free at the point of use, perhaps with some fees for extra features like ad removal.
Unlike ZIRP, zero-mark cost death is not guaranteed. There’s a push to run some cutting-edge AI “on the device,” scaling it down slightly to the point where it can use the powerful processors in an iPhone or laptop instead of relying on expensive data centers.
But that’s a technical challenge, and it seems likely that the most powerful AI models will always be those that are centrally hosted and cost huge sums of money to run.
We can’t know for sure what the next decade holds, and it’s tempting to think that the massive economic shift of the death of the two zeroes will be rendered moot by the even bigger technological shift of the rise of AI. But I’m not so sure. The shape of the last tech boom was fundamentally set by these two economic facts: what will the next one look like without them?
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