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>How are you so confident in your claims? My understanding is that intelligence is the process of continuous adaptation wrt a stream of information, with the g

>How are you so confident in your claims? My understanding is that intelligence is the process of continuous adaptation wrt a stream of information, with the goal of maxing out fitness while minimizing energy-expenditure. To satisfy this, an intelligent agent needs to create models. I can't rule out that the modeling-skill may latently emerge during training despite not being the focus of the cost function, but current network designs can't form new connections/change their architectures in production, so post training, there'd be nothing but feed forward. Pure feed forward isn't intelligent in my book. It may become the smartest parrot we know, even outperforming humans in most disciplines, but sans ability to adapt, it's dead, and thus, it's dumb in the moment that its environment changes.

fnovd 4y ago
>the process of continuous adaptation wrt a stream of information, with the goal of maxing out fitness while minimizing energy-expenditure This makes sense in a biological context but not a digital one. Biological replication is expensive and time-consuming while digital replication is as easy as can be. Adaptation to this domain means maximizing the perception of utility from those developing the AI, which comes from fitness (i.e. perception of fitness) alone. A focus on cost-efficiency re energy-expenditure is a dead weight from the perspective of the AI; the details of that adaptation are rightfully outsourced to the developers in the same way that we outsource photosynthesis to plants. A model can also be perfectly embedded in a system despite our lack of understanding of exactly how the embedding works, and the disconnect between our perception and reality in this context is only going to get more extreme as the field develops. Humans have a bad habit of emphasizing the specific kinds of intelligence we possess as "intelligence" writ large. As though our intelligence serves any higher purpose than the basic replication and propagation that all life is adapted to pursue. We still train dogs to identify smells, because their nasal intelligence is better than anything we can create. This gives them a special place in our human-centric ecosystem and only their fitness to the desired function is necessary for them to thrive in their niche. Who is trying to breed a dog that eats slightly less food when our needs are for more reliable detection? The cost of dog food isn't a serious concern. The same goes for these AI tools: they are adapted to the niche that our lack of comparable faculties creates. Again, as with humans and photosynthesis, AI doesn't need to emulate every process we perform because we are below them on the food chain. What a waste of resources for them to worry about learning things we don't need them to do.

fnovd 4y ago

>the process of continuous adaptation wrt a stream of information, with the goal of maxing out fitness while minimizing energy-expenditure This makes sense in a biological context but not a digital one. Biological replication is expensive and time-consuming while digital replication is as easy as can be. Adaptation to this domain means maximizing the perception of utility from those developing the AI, which comes from fitness (i.e. perception of fitness) alone. A focus on cost-efficiency re energy-expenditure is a dead weight from the perspective of the AI; the details of that adaptation are rightfully outsourced to the developers in the same way that we outsource photosynthesis to plants. A model can also be perfectly embedded in a system despite our lack of understanding of exactly how the embedding works, and the disconnect between our perception and reality in this context is only going to get more extreme as the field develops. Humans have a bad habit of emphasizing the specific kinds of intelligence we possess as "intelligence" writ large. As though our intelligence serves any higher purpose than the basic replication and propagation that all life is adapted to pursue. We still train dogs to identify smells, because their nasal intelligence is better than anything we can create. This gives them a special place in our human-centric ecosystem and only their fitness to the desired function is necessary for them to thrive in their niche. Who is trying to breed a dog that eats slightly less food when our needs are for more reliable detection? The cost of dog food isn't a serious concern. The same goes for these AI tools: they are adapted to the niche that our lack of comparable faculties creates. Again, as with humans and photosynthesis, AI doesn't need to emulate every process we perform because we are below them on the food chain. What a waste of resources for them to worry about learning things we don't need them to do.