Introduction to Hyperscalers: Scaling a Doghouse to Build a Cathedral

In his 1997 OOPSLA talk, The Computer Revolution Hasn’t Happened Yet , Alan Kay warned that scaling a doghouse does not create a cathedral. That is the risk in hyperscaler AI strategy today: more GPUs, more data centers, more tokens, and more power, without a clear architecture for value. Scale can increase capacity, but it cannot replace design. A cathedral is not a very large doghouse. It is a different system. As one example, Yann LeCun argues that simply scaling large language models is unlikely to produce AGI because LLMs lack robust understanding of the physical world. The question in 2028 is going to be: did MSFT/GOOG/ORCL/AMZN try to scale a doghouse?   submitted by   /u/valderium [link]   [comments]

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