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I think this boils down to two things: 1) Algorithmic tech products replacing basic services are growing beyond even their creators' control 2) Analog computi

I think this boils down to two things: 1) Algorithmic tech products replacing basic services are growing beyond even their creators' control 2) Analog computing will replace these algorithmic products and fix all the problems I disagree. Not with the "growing beyond control" bit, I think that's clear, but to the analog computing bit. First, Dyson doesn't explain what he means by analog computing, other than a basic "operates on real numbers and continuous functions." He also doesn't give any clues about what hardware or software for these systems will look like, or specifically how they will outcompete what we have now (Google, FB, etc). Second, I think he's wrong. The only things that determine the broad direction of society are who has the power and money. This has been true as far back as you go, whether kings or merchant guilds or the citizenry, when enough of them decide to work together for a revolution. And there's one fact Dyson ignores: No matter how much or little control the owners of these algorithmic tech products have over the direction and consequences of their use, they still get the money. As long as Google, Facebook, Amazon, and the others are making the money, the unintended consequences of their algorithms dictating the shape of our lives will continue to be irrelevant.

k9s9 8y ago
He is not saying analog computation will "fix all problems". He is saying the computation that is happening that props up a Trump resembles an analog system where noise plays a role.
- visarga 8y ago
  That fits well with neural nets, where noise plays a crucial role, from the random order of selecting examples into batches, to randomly dropping out synapses, directly injecting noise, or even starting prediction from pure noise (GANs). In RL the epsilon-greedy technique prescribes random actions from time to time, in order to better explore the environment. Noise, when used properly, makes neural nets better and more resilient.
koonsolo 8y ago
> First, Dyson doesn't explain what he means by analog computing, other than a basic "operates on real numbers and continuous functions." I think he means that neural networks are not binary, but use analog communication between the neurons. We simulate that digitally, but maybe a system that uses analog by nature is better for artificial neural networks. No idea if this is actually the case, or if this is what he meant ;).

k9s9 8y ago

He is not saying analog computation will "fix all problems". He is saying the computation that is happening that props up a Trump resembles an analog system where noise plays a role.

visarga 8y ago
That fits well with neural nets, where noise plays a crucial role, from the random order of selecting examples into batches, to randomly dropping out synapses, directly injecting noise, or even starting prediction from pure noise (GANs). In RL the epsilon-greedy technique prescribes random actions from time to time, in order to better explore the environment. Noise, when used properly, makes neural nets better and more resilient.

koonsolo 8y ago

> First, Dyson doesn't explain what he means by analog computing, other than a basic "operates on real numbers and continuous functions." I think he means that neural networks are not binary, but use analog communication between the neurons. We simulate that digitally, but maybe a system that uses analog by nature is better for artificial neural networks. No idea if this is actually the case, or if this is what he meant ;).