Accountants call it marginal cost. Economists often discuss it through the lens of unit economics. Whatever discipline you choose, the underlying question is the same: what happens to the cost of producing one more unit as scale increases?

Traditional software companies enjoyed one of the most beautiful economic characteristics ever discovered in business. Once the software has been built, the cost of serving an additional customer approaches zero. As users increased, the marginal cost curve moved closer and closer toward zero, creating a near-asymptotic relationship. This economic structure enabled extraordinary operating leverage and helped create some of the most valuable companies in history. In practical terms, adding more customers often made the business stronger, more profitable, and more efficient.

That is why software produced something Adam Smith never truly experienced in his era: accelerating returns. The fixed asset, the software platform, could continue serving increasing numbers of users while variable costs grew only marginally. The result was a business model where scale itself became a competitive advantage.

Artificial Intelligence changes that equation. Unlike traditional software, AI often behaves more like a classical industrial enterprise. Every new user may trigger additional inference costs, computing costs, storage costs, model-serving costs, and infrastructure expenses. As usage scales, costs do not naturally collapse toward zero. In many cases, they rise alongside demand. The economic profile begins to resemble manufacturing more than software.

This introduces the old economic reality of diminishing returns. If not carefully managed, each additional customer may contribute less value than the previous one. In extreme situations, growth itself can become expensive. Yes, more customers can actually push an AI company toward financial distress if the unit economics are poorly designed!

This challenge explains why nearly every serious AI company is attempting to build proprietary inference infrastructure, optimize models, develop custom chips, or reduce dependence on third-party providers. The battle is no longer merely about intelligence; it is increasingly about economics.

Simply, without solving the inference-cost problem, AI businesses may follow the economic trajectory of traditional industrial companies rather than the trajectory of software legends like Facebook. Put differently, without strong inference economics, AI begins to look more like a cement factory than a social network or software operating system.

And that is why the race to reduce inference costs may become one of the most important competitions of the AI age. It is also one of the reasons Tekedia Capital invested in Piris Lab. We believe the future of AI will not be determined solely by who builds the smartest models, but also by who can run those models most efficiently. Intelligence without economical delivery remains a constrained opportunity. And before AI models can evolve, hardware must have emerged to power them. That conviction is what led us to write the cheque for Piris Lab.

Piris Lab is developing a next-generation photonic computing system designed to perform AI inference at the speed of light. By leveraging photons rather than relying solely on traditional electronic architectures, the company seeks to dramatically reduce latency, improve performance, and lower the cost of deploying AI at scale.

Good People, if AI is to become truly ubiquitous, powering everything from personal assistants and autonomous systems to healthcare, manufacturing, and scientific discovery, the economics must improve. The industry cannot sustainably scale if every additional user significantly increases computational costs.

We see photonics as one of the most promising pathways to solving that challenge. In many ways, future AI winners may emerge not only from advances in algorithms, but also from breakthroughs in the physical infrastructure that makes intelligence affordable and accessible.

We believe the company is helping build the foundational infrastructure required to advance the next phase of the AI revolution.

The future of digital money may not belong to stablecoins after all.

While stablecoins have emerged as one of the fastest-growing segments of the cryptocurrency market, a growing debate among policymakers and financial institutions suggests that tokenized bank deposits could eventually eclipse them, reshaping how digital payments and financial transactions are conducted over the next decade.

That debate came into sharp focus at a financial conference in Croatia on Sunday, where Bank of England policymaker Megan Greene argued that tokenized deposits, rather than stablecoins, are likely to become the dominant form of digital money.

“I think tokenized deposits are probably going to take over from stablecoins and five years from now, I suspect we might wonder why we were talking about stablecoins,” Greene said.

There has been a growing divide among regulators and central bankers over the future architecture of digital finance, particularly as governments, commercial banks, and technology firms race to develop alternatives to traditional payment systems.

The debate hangs on three competing forms of digital money: stablecoins, central bank digital currencies (CBDCs), and tokenized bank deposits.

Stablecoins are privately issued digital tokens, typically backed by assets such as U.S. Treasury securities or cash reserves, designed to maintain a stable value. They have become increasingly popular for payments, cross-border transfers, and cryptocurrency trading.

Tokenized deposits, by contrast, are digital representations of traditional bank deposits issued directly by commercial banks on blockchain-based networks. Because they remain liabilities of regulated banks, proponents argue they combine the efficiency of blockchain technology with the safety and regulatory protections of the existing banking system.

Greene believes commercial banks have been slow to embrace tokenized deposits largely because they fear losing lucrative fee income and disrupting existing business models.

“Digital deposits haven’t taken off because commercial banks don’t want to lose the fees,” she said. “But they’re going to lose them anyhow and when they realize this, they will put more effort into developing these.”

Major lenders in Europe, the United States, and Asia have accelerated experiments with tokenized deposits as they seek to modernize payment infrastructure while retaining customer funds within the banking system. The issue has become important because stablecoins are increasingly viewed as a potential threat to banks’ traditional deposit base.

If consumers and businesses begin holding significant portions of their cash in stablecoins rather than bank accounts, lenders could lose a key source of funding used to support lending activities.

Greene also raised concerns about stablecoins themselves, questioning both their reliability and broader economic impact.

She argued that stablecoins are “not so stable,” citing ongoing questions surrounding reserve backing, regulation, and their use in illicit financial activities. She further warned that a migration of deposits from banks into stablecoins could weaken the effectiveness of monetary policy by reducing the influence central banks exert through the banking system.

Yet not everyone shares that view.

Joining Greene on the same panel, Christopher Waller offered a strong defense of stablecoins, describing them as a legitimate financial innovation that could increase competition and lower costs in the payments industry.

“I’ve always just looked at stablecoins as a payment instrument; there’s nothing evil about it, nothing dangerous about it,” Waller said. “They are just bringing competition into the payments world.”

Waller argued that the market’s enthusiasm for stablecoins reflects genuine demand for faster and more efficient payment systems, particularly for international transactions.

“These things are used for cross-border payments, and they are scaring the banks,” he said. “If you think banks don’t think this is a threat, then why are they lobbying so hard to stop it?”

In the United States, lawmakers have increasingly sought to establish frameworks that would allow stablecoins to operate within a regulated environment. Supporters contend that properly supervised stablecoins could improve payment efficiency, reduce transaction costs, and challenge entrenched financial intermediaries.

Global stablecoin circulation has grown into the hundreds of billions of dollars, and many analysts expect further expansion as tokenized finance becomes more mainstream.

At the same time, central banks continue exploring their own digital alternatives. The Bank of England, the European Central Bank, the People’s Bank of China, and numerous other monetary authorities have studied or tested central bank digital currencies, though most projects remain in pilot stages.

Greene used an analogy to describe the competition among these different forms of digital money.

“I like to think of it as a massive race between the tortoise, the hare and the rhino,” she said.

“The tortoise is the central bank digital currency. The hare is stablecoins and the rhino is tokenized deposits. We’ll probably end up with all three, but if I had to put money in one, it would be the rhino, tokenized deposits, which I think will probably take off.”

The outcome of that race remains uncertain. Stablecoins currently enjoy a significant first-mover advantage and growing adoption in payments and digital asset markets. CBDCs carry the backing of sovereign governments. Tokenized deposits offer the trust and regulatory framework of traditional banking.