11–20 of 102 posts
> and from the practice of software development and its commercial and industrial deployment. More specifically, the philosophy of computer science considers the ontology and epistemology of computational systems, focusing on problems associated with their specification, programming, implementation, verification and testing. Well, Stanford doesn't have a clue what Computer Science is and isn't and is apparently tryin…
> and from the practice of software development and its commercial and industrial deployment. More specifically, the philosophy of computer science considers the ontology and epistemology of computational systems, focusing on problems associated with their specification, programming, implementation, verification and testing. Well, Stanford doesn't have a clue what Computer Science is and isn't and is apparently tryin…
I think the easiest definition of Software is the stuff you can change without a soldering iron.
That reads like the successor to Prof. John McCarthy's "Epistemological Problems in Artificial Intelligence" class, which I once took, back in the days of logical inference and expert systems. AI people thought back then that if you thought about thought enough, you could figure out how to mechanize it. That turned out to be a dead end, and the "AI winter" (roughly 1985-2005) followed. That class was known informally…
AFAIK the AI winter was more related to the Minsky paper, and the hype and no delivery of the over-promisses made by the industry.
The way that I heard it, it was the fact that Lisp environments on Sun workstations were able to outperform Lisp machines at a much better price point. And just like that, a significant AI specific industry collapsed, and its other promises came into question.
That said, all three versions are consistent. The fact that researchers thought that they were closer than they were caused them to overpromise and underdeliver. Then when the visible bleeding edge of their efforts publicly lost to a far cheaper architecture, their failure became very visible.
Which we call cause versus effect almost doesn't matter. All of these things happened, and lead to an AI winter. And we continued to get incremental progress until the unexpected success of Google Translate. Whose success was not welcomed by people who had been trying to get rule-based AI systems to work.
> and from the practice of software development and its commercial and industrial deployment. More specifically, the philosophy of computer science considers the ontology and epistemology of computational systems, focusing on problems associated with their specification, programming, implementation, verification and testing. Well, Stanford doesn't have a clue what Computer Science is and isn't and is apparently tryin…
CS is to computers as geometry is to surveying.
Computer architecture, operating systems, etc. are about computers and they are topics in computer science.
> and from the practice of software development and its commercial and industrial deployment. More specifically, the philosophy of computer science considers the ontology and epistemology of computational systems, focusing on problems associated with their specification, programming, implementation, verification and testing. Well, Stanford doesn't have a clue what Computer Science is and isn't and is apparently tryin…
This is extreme. Computer architecture is undoubtably a field of study within CS.
Many parts of computer science are mathematical, but many parts are closer to physics or chemistry than mathematics. You can run experiments and form hypotheses in computer science.
Earlier quoted context omitted.
AFAIK the AI winter was more related to the Minsky paper, and the hype and no delivery of the over-promisses made by the industry.
First of all "this, then that" does not imply causality. The way that I heard it, it was the fact that Lisp environments on Sun workstations were able to outperform Lisp machines at a much better price point. And just like that, a significant AI specific industry collapsed, and its other promises came into question. That said, all three versions are consistent. The fact that researchers thought that they were closer…
https://www.vice.com/en/article/akex34/chatgpt-is-a-bullshit...
> and from the practice of software development and its commercial and industrial deployment. More specifically, the philosophy of computer science considers the ontology and epistemology of computational systems, focusing on problems associated with their specification, programming, implementation, verification and testing. Well, Stanford doesn't have a clue what Computer Science is and isn't and is apparently tryin…
Something that occurs to me is often when creating programs to run on a computer system we don't know exactly how they will perform in advance, because of the complexity of the hardware and software interrelations within the system. And so we run them and measure the results. That's definitely science.
Different professor (and no longer downloadable) Philosophy of Computer Science from buffalo.edu https://news.ycombinator.com/item?id=20912718 (and https://news.ycombinator.com/item?id=10388603 ) The author of the Buffalo tome is https://cse.buffalo.edu/~rapaport/ which links to a number of other resources too. > The table of contents alone (19 pages) is an extraordinarily good outline of what CS is, and what the maj…
Any ways to download that book which is no longer downloadable? Could you share some link or something helpful to find it?