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Today’s Cheap AI Services Won’t Last

We've seen this pattern:

  1. Initial hype and overinvestment

  2. A correction/consolidation phase as reality sets in

  3. Steady growth and value creation as the technology matures

We're currently riding high on the wave of AI hype. Venture capital is flowing freely, and AI startups are offering their services at artificially low prices, often below cost. This creates an illusion of boundless potential and ever-decreasing expenses. However, history suggests this phase is unsustainable.

The current landscape bears a striking resemblance to the early days of cloud computing. Fifteen years ago, it was commonplace for individuals and businesses to pay less than $10 a month for shared hosting or a VPS. This pricing model seemed set in stone, with costs expected to continue declining.

Fast forward to today, and we see a drastically different picture. The market is dominated by giants like AWS, Google Cloud, and Azure. Users now pay premium prices for CPU cores by the hour and exorbitant fees for hosted databases that are essentially glorified shared hosting. The promise of ever-falling costs didn't materialize as expected.

We may be headed for a similar awakening in the AI sector. As the initial hype subsides and the reality of building sustainable AI businesses sets in, we're likely to see a significant shift in the economic landscape:

  1. Consolidation: Many AI startups will struggle to achieve profitability, leading to a wave of mergers, acquisitions, and shutdowns. This could leave a handful of well-funded players dominating the market.

  2. Price increases: As VC funding dries up and companies face pressure to turn a profit, we'll likely see sharp increases in the cost of AI services. Businesses and individuals who have built their operations around cheap AI tools may face a rude awakening.

  3. Specialization: Surviving companies will need to differentiate themselves by focusing on specific industries or use cases, rather than trying to be all things to all users.

  4. Infrastructure evolution: The current reliance on expensive GPU clusters may give way to more specialized, efficient AI hardware. This could help mitigate some cost pressures.

Those who have become overly reliant on subsidized AI services may need to reevaluate their strategies.

Those who survive the hype cycle and emerge on the other side often become the dominant players of the next era. The AI landscape five years from now may look very different from today.

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