AI stocks bloodbath

Investment Analysis Clubs Macro Economic Trends and Risks
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Never invested in AI myself:

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It seems the AI speculators are waking up to the Achilles heel of AI - that the end-user purchases won’t show up to justify the immense investments for years to come, if ever.

Since AI speculative frenzy now represents 40% of the S&P500 index, investors who hold index funds will be hurt.

And leveraged speculators will start dumping the non-AI stocks to meet margin calls. This has happened in every bubble.
Wendy

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This time is never different.

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People have been saying AI is a bubble for months. The immediate factor is Meta’s decision to sell some data center capacity and IBMs report that customers delayed signing contracts causing drop in share value.

Investors decided to take profits. They say margin calls were heavy in SK Hynix in Korea.

Memory chip companies have been doing very well. Many have seen major declines. Some think support levels are forming.

Much depends on earnings. Strong earnings should stabilize things for a while. But people see limits to future growth. Until AI begins to deliver earnings. The key is productivity improving applications.

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Intelligence, by itself, is not valuable. Value is produced when intelligence is used to create value. The best current example is humanoid robots. What good would it do to have artificial intelligence without robots to use it? Apple is the best example, not for intelligence but for software. What sets the iPhone apart is Apple’s User Interface technology developed for Mac.

GoogleAI:

You are describing the concept of embodied AI—the idea that intelligence reaches its full potential only when paired with physical hardware that can interact with the world. Just as software requires a user interface, AI requires an “avatar” (like a humanoid robot) to execute tasks and generate real-world value. [1, 2, 3]

Here is how your insights align with current industry developments:

  • Humanoid Robots as the Ultimate UI: Companies like Figure, Agility Robotics, and Tesla are racing to create the “hardware chassis” that turns abstract AI models into productive labor. Value is finally generated when the AI can manipulate objects, navigate factories, or assist in homes. [1, 2]
  • Embodied AI Training: The transition from software to physical application is notoriously difficult. Leading companies are utilizing egocentric video data (first-person views of humans completing tasks) to train these robots, helping bridge the gap between human intelligence and machine action. [1, 2, 3, 4]
  • The Apple Parallel: You rightly point out that Apple’s success hinges on its mastery of User Experience rather than raw hardware or computational power. By combining intuitive macOS-derived touch interfaces with tailored software, Apple made smartphones accessible. In the same way, the next trillion-dollar opportunity in tech may belong to the companies that can package complex robotic AI into a consumer-friendly, accessible form. [1, 2, 3, 4]

The Captain