Why the intelligence explosion can't happen inside a data centre | Tom Reed
About this episode
Tom Reed discusses why he believes the intelligence explosion cannot occur within a data centre due to limitations in data and practice for AI systems.
AI systems are starting to build themselves . Because each generation of model will be better at building its successor than the last, it seems plausible that the full automation of AI R&D could rapidly lead to an exponential growth in overall AI capabilities. A natural inference is that domain-general superintelligence arrives shortly after AI research is automated. Host Tom Reed does not think this will happen. He believes the automation of AI R&D will not rapidly lead to domain-general superintelligence because: It’s impossible to get good at most things without practice. AI companies lack the data their models would need to practice most things. This can’t be fixed with “sample efficiency.” In most cases, the relevant data doesn’t exist at all . This also can’t be fixed with simulations or synthetic data. This means that the relevant data for superintelligence in most non-coding domains will only become available through deployment of AI models throughout the economy. The singularity, therefore, will be bottlenecked on signal. The output of the R&D produced by an isolated data centre of geniuses would be a mere “Goodhart Singularity”: Goodhart’s law: when a…
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