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I was on a panel Assessments for Non-CS Major Computing Classes (see the ACM DL paper here ). Her talk was particularly relevant to me because she emphasized how she is studying business students, not computerscience students her research is about how non-CS students interact with computing and programming.
Think of it as the entangled limit of everything that is computationally possible: the result of following all possible computational rules in all possible ways. And it’s one that I think has extremely deep implications—both in science and beyond. The full ruliad is in effect a representation of all possible computations.
We can think of the ruliad as the entangled limit of all possible computations—or in effect a representation of all possible formal processes. Many of these consequences are incredibly complicated, and full of computational irreducibility. But now we can make a bridge to mathematics. So is something similar happening with mathematics?
See also: “Wolfram|Alpha as the Way to Bring Computational Knowledge Superpowers to ChatGPT” » It’s Just Adding One Word at a Time That ChatGPT can automatically generate something that reads even superficially like human-written text is remarkable, and unexpected. But how does it do it? And why does it work?
“For the line drawings, we traced the contours with custom-made computer vision algorithms,” says Dirk. “We We wanted to see whether there were enough consistent features in each category for the computer to be able to accurately categorise any one image.” If the computer had only guessed randomly, it would have had an accuracy of 17%.
In NaturalSciences, students often struggle to understand and apply science topics, and have difficulties imagining or realizing their importance and application in real life. As John Doerr, successful venture capitalist and early investor in Google, recently phrased it: “Sustainability is the next computerscience”.
But in a quirk of history that I now realize had tremendous significance, I had just spent a couple of years creating a big computer system that was ultimately a direct forerunner of our modern Wolfram Language. So for me it was obvious: if I couldn’t figure out things myself with math, I should use a computer. Computation theory.
Scientific simulations — an advanced type of computational model that not only represents a real-world phenomenon, but aims to predict how the phenomenon might change under different conditions or parameters. Software — a set of instructions, scripts or programmes that are used to operate computers and perform specific tasks.
So is that basically inevitablesay as a consequence of computational irreducibility ? But what about something more like a theory in naturalscience? And heres one page of it (out of about 30)presented in the form of a computable Wolfram Language dataset: Whats the basic idea of this proof? Its a subtle question.
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