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Thank you for this information. I did not know this. But my view (I may be wrong), is that AGI is too resource-intensive to be within the reach of normal comput

• naasking 4y ago
  > is that AGI is too resource-intensive to be within the reach of normal computing of the ordinary user for at least 2 decades. Hardware is still accelerating exponentially in density, albeit a bit slower. What you're not considering is that algorithmic improvements in machine learning are outpacing hardware improvements. For instance, NVidia recently revealed how to switch from 32-bit floats to 16-bit floats with no perceptible loss in effectiveness, and they're working on 8-bit floats next. That's a full doubling in number of parameters in your model in only a single step. Other improvements are refinements to language models themselves to reduce overfitting and boost effectiveness with fewer parameters. Arguably a machine learning model will achieve parity with human neuron density, in terms of number parameters, within the next decade. What that actually means is unclear.
• zamfi 4y ago
  You’re entitled to your own opinion, of course, but why do you hold this view? And why is “the reach of normal commuting of the ordinary user” a relevant bar — Google search (as an example) requires computation beyond the reach of normal computing of the ordinary user yet has still had a tremendous impact.