Google has an original advantage in the Transformer architecture but hesitated in the implementation of conversational products due to organizational and commercial protection instincts. The existence of LMChat indicates that technological readiness is not the bottleneck; the real constraints stem from the assessment of potential impacts on search advertising revenue and the isolation between research and product departments.

In terms of capital pathways, OpenAI rapidly captured user mindshare and developer ecosystems with a "release first, iterate later" strategy, forcing Google to shift from a leader to a follower, ultimately leading to the merger of DeepMind and Brain. The difference in motivation lies in the fact that one side views product release as the starting point for learning and data flywheels, while the other sees release as an irreversible risk event.

Similar cases can be seen in Kodak's internal suppression of digital photography and Microsoft's hesitation regarding early mobile systems. The current AI industry is still in a phase where "organizational courage and technical capability are equally important."

Essentially, this is about the transfer of pricing power. The mechanism is that when the speed of technological diffusion exceeds the decision-making speed of large organizations, the first movers gain the priority to define categories and attract resources, while later entrants, even with comparable technology, must incur higher costs to catch up.

ABAB News · Law of Cognition

Seeing the future but not daring to release it is equivalent to giving the future to others.
The instinct to protect core businesses often becomes the main reason for missing new categories.
Technological readiness has never been the bottleneck; organizational courage is.