At the same time this additional x1,000,000 or so hardware overhang is developing (there is a good chance that a significant hardware overhang existed before the AI was turned on in the first place), the system is in the process of being interfaced and integrated by the development team with an array of other databases and abilities.
Some of these databases and abilities were available to the system from the start. The development team has to be extremely cautious about what they interface with which copies of the AI-these decisions are probably more important to the rate of takeoff than creating the system in the first place.
Language Acquisition
Because of the centrality of language to human cognition, the relationship between language acquisition and takeoff speed is worth analyzing as a separate question from takeoff speed for an abstract notion of general intelligence.
Human-level language acquisition capability seems to be a necessary condition to develop human-level AGI, but I do not believe it is a necessary condition to develop an intelligence either capable of manufacturing, or even of commerce, or hiring people and giving them a set of instructions. (For this reason, among, others, thinking about surpassing human-level does not seem to be the right question to ask if we are debating policy.)
Here are three scenarios for advanced AI language acquisition:
1) The system, like a child, is initially capable of language acquisition, but in a somewhat different way. (Note that for children, language acquisition and object recognition skills develop at about the same time. For this reason, I believe that these skills are intertwined, although they have not been that intertwined in the development of AI systems so far.)
2) The system begins with parts of a single language somewhat hardwired.
3) The system performs other functions than language acquisition, and any language capability has to be interfaced in a second phase of development.
If 1) comes about, and the system has language acquisition capability initially, then it will be able to acquire all human languages it is introduced to very quickly. However, the system may still have conceptual deficits it is unable to overcome on its own. In the movies the one they like is a deficit of emotion understanding, but there could be others, for instance, a system that acquired language may not be able to do design. I happen to think that emotion understanding may prove more tractable than in the movies. So much of human language is centered around feelings, therefore a significant level of emotion understanding (which differs from emotion recognition) is a requirement for some important portions of language acquisition. Some amount of emotion recognition and even emotion forecasting is required for successful interactions with people.
In case 2), if the system is required to translate from its first language, it will also be capable of communicating with people in these other languages within a very short time, because word and phrase lookup tables can be placed right in working memory. However, it may have lower comprehension and its phrasing might sound awkward.
In either case 1) or 2), roughly as soon as the system develops some facility at language, it will be capable of superhumanly communicating with millions of people at a time, and possibly with everyone. Why? Because computers have been capable of personalized communication with millions of people for many years already.
In case 3), the system was designed for other purposes but can be interfaced in a more hard-wired fashion with whatever less-than-complete forms of linguistic processing are available at the time. These less-than-complete abilities are already considerable today, and they will become even more considerable under any scenario other than disinclination to advance and government regulation.
A powerful sub-set of abilities from a list more like this:
Planning, design, transportation, chemistry, physics, engineering, commerce, sensing, object recognition, object manipulation and knowledge base utilization.
Might be sufficient to perform computer electronics manufacturing.
Little or no intelligence is required for a system to manufacture using living things.
At the same time this additional x1,000,000 or so hardware overhang is developing (there is a good chance that a significant hardware overhang existed before the AI was turned on in the first place), the system is in the process of being interfaced and integrated by the development team with an array of other databases and abilities.
Some of these databases and abilities were available to the system from the start. The development team has to be extremely cautious about what they interface with which copies of the AI-these decisions are probably more important to the rate of takeoff than creating the system in the first place.
Language Acquisition
Because of the centrality of language to human cognition, the relationship between language acquisition and takeoff speed is worth analyzing as a separate question from takeoff speed for an abstract notion of general intelligence.
Human-level language acquisition capability seems to be a necessary condition to develop human-level AGI, but I do not believe it is a necessary condition to develop an intelligence either capable of manufacturing, or even of commerce, or hiring people and giving them a set of instructions. (For this reason, among, others, thinking about surpassing human-level does not seem to be the right question to ask if we are debating policy.)
Here are three scenarios for advanced AI language acquisition:
1) The system, like a child, is initially capable of language acquisition, but in a somewhat different way. (Note that for children, language acquisition and object recognition skills develop at about the same time. For this reason, I believe that these skills are intertwined, although they have not been that intertwined in the development of AI systems so far.)
2) The system begins with parts of a single language somewhat hardwired.
3) The system performs other functions than language acquisition, and any language capability has to be interfaced in a second phase of development.
If 1) comes about, and the system has language acquisition capability initially, then it will be able to acquire all human languages it is introduced to very quickly. However, the system may still have conceptual deficits it is unable to overcome on its own. In the movies the one they like is a deficit of emotion understanding, but there could be others, for instance, a system that acquired language may not be able to do design. I happen to think that emotion understanding may prove more tractable than in the movies. So much of human language is centered around feelings, therefore a significant level of emotion understanding (which differs from emotion recognition) is a requirement for some important portions of language acquisition. Some amount of emotion recognition and even emotion forecasting is required for successful interactions with people.
In case 2), if the system is required to translate from its first language, it will also be capable of communicating with people in these other languages within a very short time, because word and phrase lookup tables can be placed right in working memory. However, it may have lower comprehension and its phrasing might sound awkward.
In either case 1) or 2), roughly as soon as the system develops some facility at language, it will be capable of superhumanly communicating with millions of people at a time, and possibly with everyone. Why? Because computers have been capable of personalized communication with millions of people for many years already.
In case 3), the system was designed for other purposes but can be interfaced in a more hard-wired fashion with whatever less-than-complete forms of linguistic processing are available at the time. These less-than-complete abilities are already considerable today, and they will become even more considerable under any scenario other than disinclination to advance and government regulation.
A powerful sub-set of abilities from a list more like this:
Planning, design, transportation, chemistry, physics, engineering, commerce, sensing, object recognition, object manipulation and knowledge base utilization.
Might be sufficient to perform computer electronics manufacturing.
Little or no intelligence is required for a system to manufacture using living things.