The artificial intelligence (AI) industry is currently at the peak of its hype. Major technology companies (Big Tech) are racing to pour hundreds of billions of dollars into building the infrastructure of the future. However, behind that optimism, a stern warning has come from Tether CEO Paolo Ardoino.
Ardoino believes that the business model being pursued by today’s AI giants is on an unsustainable path. Why is that so? Here are three key factors underpinning his analysis.
1. Infrastructure Costs That Burn Money
To train and run the latest-generation Large Language Models (LLMs), thousands of advanced GPUs, massive data centers, and enormous energy consumption are required. Big Tech is willing to “burn money” to secure this infrastructure so it won’t fall behind in the competition. The problem is that these operating costs are ballooning far faster than the real revenue growth generated by the AI products themselves.
2. Shrinking Margins, Delayed Profits
Unlike traditional software businesses (SaaS) with very high profit margins, AI is an industry that is “hungry” for computation. Every time a user enters a prompt, there is a real computing cost that must be paid by the service provider. With increasingly intense price competition to attract users, profit margins keep shrinking, while the break-even point (return on investment) continues to be pushed into an uncertain future.
3. The Real Threat from Open-Source Competition
This is the most compelling point in Ardoino’s view. While closed (proprietary) AI companies spend billions of dollars to monopolize technology, the open-source community is moving at extraordinary speed.
More efficient, flexible, and free open-source models are now able to match the capabilities of the paid models owned by technology giants.
Ardoino believes that the business model being pursued by today’s AI giants is on an unsustainable path. Why is that so? Here are three key factors underpinning his analysis.
1. Infrastructure Costs That Burn Money
To train and run the latest-generation Large Language Models (LLMs), thousands of advanced GPUs, massive data centers, and enormous energy consumption are required. Big Tech is willing to “burn money” to secure this infrastructure so it won’t fall behind in the competition. The problem is that these operating costs are ballooning far faster than the real revenue growth generated by the AI products themselves.
2. Shrinking Margins, Delayed Profits
Unlike traditional software businesses (SaaS) with very high profit margins, AI is an industry that is “hungry” for computation. Every time a user enters a prompt, there is a real computing cost that must be paid by the service provider. With increasingly intense price competition to attract users, profit margins keep shrinking, while the break-even point (return on investment) continues to be pushed into an uncertain future.
3. The Real Threat from Open-Source Competition
This is the most compelling point in Ardoino’s view. While closed (proprietary) AI companies spend billions of dollars to monopolize technology, the open-source community is moving at extraordinary speed.
More efficient, flexible, and free open-source models are now able to match the capabilities of the paid models owned by technology giants.