We even have lots of people encoding knowledge in it they are called programmers.

Integration is another problem, but the brain is not completely integrated. We need to develop programs that can understand the knowledge encoded in other programs, and programs to maintain the knowledge. Some way of constraining the system, while changing the internal programs, so that it has some purpose would probably also be useful.

I don’t see why you think ems would be so aggressive.

Who said anything about aggression? Like I said earlier: Warfare is different from winning.

You do not necessarily have to fight to prevail – all that is needed is for your competitiors to not have as many kids as you do. Of course, there might be fights – but they do not seem like a critical element.

Unfortunately, this task is much harder than it seems. Creating ontologies that actually have the flexibility, accuracy and coverage required is an open problem that has foxed the Cyc project for 25 years. There are entire communities of researchers working on problems of (a) creation of upper ontologies, (b) learning ontologies from text, (c) mapping between ontologies and (d) actually doing inference over ontologies. The biggest problem (as I see it) is that there is a bad mismatch between the world of formal logic which allows one to give meaning to terms, and the world of statistics and probability which allows you to approximate things. If you have no notion of approximation, you can’t leverage the powerful computers and large amounts of data we have on the internet, and you will be reduced to writing ontologies by hand. If you have no notion of meaning or semantics, you will end up creating a meaningless resource which can’t perform even the most basic inferences, or you will end up with a probability distribution over a narrowly defined set of outcomes that don’t even come close to providing the generality required to understand an “arbitrary” situation.

Basically, building an “ontology” which can represent “anything” is a very hard problem in itself.

If you have any ideas about how to make progress in this area, then do get in touch. I’ve spent a couple of months researching this, and I am becoming increasingly distressed by how hard it is to get anywhere.

Robin: I might do a post on this issue: “Advice for Wannabe Einsteins”

The idea that one/few people on his/their own can somehow develop an entirely new ‘localized’ complex thing that is largely independent of the wider community seems wildly improbable (no one is smart enough).

That’s why the universal parser/ontological approach is definitely a major alternative strategy, because it can draw on the insights of everyone in the wider IT community for sharing all the individual ideas in an integrated framework.

Roko, here’s the way to do it:

Instead of trying to develop all the ‘machinery’ for AGI from stratch, don’t work on the ‘machinery’ at all. Instead, develop a specialized language (a parser/ontology) enabling sharing and integration of all the various narrow IT domains – this way, you are in effect only designing the levers, whilst borrowing all the underlying machinery from everyone else.

What I love about this idea is that with an effective ontology (a ‘universal parser), all the world’s other IT researchers would in effect be working for me… with the right ontology I can simply plagiarize all their insights (how nice of academia to publish everything in open source journals for me!), and in effect, use their brains as ‘botnets’, which are linked via my effective ontology for sharing of cognitive content (I am simply pushing the levers, they’re supplying all the underlying machinery). LOL It’s the ultimate hack.

People with artificial hearts can think, so on for just about every organ. It is likely that it would be trivial to make very computationally efficient virtual organs that work as good or better. (probably just mimicking their final effects)

James, stupid idle rich humans are pretty safe now. No perfectly safe of course. I don’t consider the em world I describe to be a hell-hole, but don’t want to get distracted on that topic at the moment.

Tim, I don’t see why you think ems would be so aggressive.

Douglas, what is HG?

Ian, no whole body emulation seem unnecessary.

“we would probably have to emulate the whole body?”

The Whole Brain Emulation roadmap discusses this in its own section, p. 74

“Simulating a realistic human body is kinematically possible today, requiring computational power ranging between workstations and mainframes. For simpler organisms such as nematodes or insects correspondingly simpler models could (and have) been used. Since the need for early WBE is merely adequate body simulation, the body does not appear to pose a major bottleneck.”

The roadmap also notes that an environment may be required:

“Convincing environments might be necessary only if the long‐term mental well‐being of emulated humans (or other mammals) is at stake. While it is possible that a human could adapt to a merely adequate environment, it seems likely that it would experience such an environment as confining or lacking in sensory stimulation. Note that even in a convincing environment simulation not all details have to fit physical reality perfectly (Bostrom, 2003). Plausible simulation is more important than accurate simulation in this domain and may actually improve the perceived realism (Barzel, Hughes et al., 1996).”

For those who have not read the WBE roadmap in detail, I urge it strongly. It is technical and takes work. There you will see what the real issues are.

I find much of the discussion a bit frustrating as it doesn’t seem to address the force of the WBE roadmap at all. Since this is what Robin bases his thinking on, it seems crucial to me to engage with it.