You're speaking of functional completeness of boolean operators which I think is quite unrelated to theories of computation. For computation you need some notion of state, and while a circuit made of logic gates may possess some notion of state, a logic gate in itself does not. As for transistors being universal (whatever that means) if this is true then vacuum tubes, relays, pneumatic valves, etcetera are also universal.
I live in Germany at the moment and I do see this in many places. On the other hand there are also still shops where showing my card gets me a puzzling look as if I'm some kind of time traveller visiting from the future armed with my mysterious shiny plastic card.
Seconded. It's definitely worth spending some extra money on a reputable brand, rather than a generic low quality product with a meaningless name stamped on the box. For screwdrivers I stick with PB Swiss.
Perhaps basing our decisions on general purpose function approximators (whether forced or voluntarily) has not served us so well, ultimately. I think they play an important role in causing, or at least enabling, much of the trouble that we live in nowadays.
I'm nitpicking but my point is that a DAG doesn't let you run anything. It might represent something, though, such as a bunch of tasks and a "must be executed before" relation. It's sloppy, imprecise use of language.
There are more examples. Between the 60ies and early 90ies, Philips in the Netherlands sold their own line of proprietary computer systems such as the P800 series (PDP/11-like) and P4000 series (a Cobol programmed office computer). The Philips computer division was later sold to DEC. Information about much of this hardware is nearly nonexistent.
Perhaps what you’re thinking of is inductive logic programming, although I’m not sure that field has advanced to the point where your particular example can be solved.
Fuzzy logic deals with this in the exact same way as classical logic. Note that in classical logic, the truth value of "A and B" and "A or B" is also a function of the truth values of A and of B. When using fuzzy logic you have to make a choice as to which function you use. Typically these functions generalise the classical logic ones in the sense that they behave like the classical ones when using 0 and 1. These functions are defined by a so called T-norm.
Apart from the other answers, there is also one important technical difference. Fuzzy logic is truth functional but probability is not. That is, in fuzzy logic, if you know the fuzzy truth value of A and of B, you can calculate the fuzzy truth value of “A and B” “A or B” and so on. Not in probability. If you know, let’s say, A and B both have probably 0.9, you don’t know enough to calculate the probability of “A and B”, which lies somewhere between 0.8 and 0.9, or “ A or B”, which lies between 0.9 and 1.
Related to this: I wonder if the days of founders naming their companies after their own (family) names are ever coming back. There’s something wholesome about it and it inspires confidence. Who is more trustworthy: someone attaching their name to their business, or someone who hides behind WeeBlee or BlooBloo or whatever it is they came up with?
I agree with you. The point was not that this proves we reached human level intelligence. However we should keep in mind that the goalposts have been moved numerous times already. Once a problem that was initially considered an AI problem was solved, it was no longer called AI anymore. It is likely that any realistic goal we set ourselves and that will be solved at some point will suffer the same fate. Perhaps that’s characteristic for AI as a research discipline.
The history of Philips' computer divisions through the years is interesting and rather obscure. After building mainframes in the 60ies (P1000) they went on to develop minis such as the P800 and P4000 in the 70ies/80ies. As far as I know this was both developed and marketed mainly in Europe, the P800 for industrial control and P4000 as an office computer. This was very proprietary stuff (both hardware and software) and details are sadly hard to find online these days. Later, Philips abandoned their home-grown efforts and went on to produce PC clones, although I believe there was also something Unix-based (P9000?).
Thanks I’ll check that out. My own understanding is that pretty much any probabilistic graphical model can be constructed as a probabilistic program, combined with pretty much any mode of inference. How such programs compare to specialized algorithms in terms of efficiency is not clear to me. I’m asking because my understanding is based mostly on theory and I’d like to learn more about probabilistic programming in practice.
Surprisingly these can still be bought easily on Ebay, Aliexpress etc. Many seem to be Soviet "new old stock" models (or perhaps actual new items?). This might be explained by the fact that they've been used quite a lot in Soviet military equipment, even long after they were considered obsolete in the west.