In general, I love such novel concepts (rather than slight refinements of existing). They are like seeds - the vast majority of them won't sprout, but one in a thousand (or million) will change a field.
The same way as one erroneous paper on superluminal communication got refuted by the non-cloning theorem - which gave raise to quantum cryptography and quantum information in general. I recommend reading the backstory in "How the Hippies Saved Physics" (https://en.wikipedia.org/wiki/How_the_Hippies_Saved_Physics).
I don’t know how much of this paper I can understand but
I find it pretty interesting that, AFAICT, the dominant engineering paradigm of an era is also the dominant “this is what reality is” metaphor: cathedrals and architecture and the spheres; steam and clockwork and mechanical; now - computation and information!
Um, that's an overstatement. He was also "focused" on making refrigerators - he owned a patent on a novel system, but was foiled by the near-simultaneous discovery of better non-toxic refrigerant liquids.
Do you think it is from goodness of their heart that corporates support open source? E.g. Microsoft - VSCode and Typescript, Meta - PyTorch and React, Google - Chromium and Go.
Yet, we (developers, users, human civilization), benefit from that.
So yes, I cherish when Chinese companies release open source LLMs. Be it as it fits their business model (the same way as US companies) or from grants (the same way as a lot of EU-backed projects, e.g. Python, DuckDB, scikit-learn).
Yes. Sometimes people treat intelligence as a single line, or as nested sets, where a greater intelligence can solve all the problems a lesser one can, plus more.
While in some contexts these are useful approximations, they break down when you try to apply them to large differences not just between humans, but between species (for a humorous take, see https://wumo.com/wumo/2013/02/25), or between humans and machines.
Intelligence is about adaptability, and every kind of adaptability is a trade-off. If you want to formalize this, look at the "no free lunch" theorems.
My lecturer was once unable to solve a problem at the blackboard.
After trying for some time, he said he needed a short break to go back to his office to look at his notes. He brought the notes, and there he found a hint he had written for himself: "Use a trick"
I recommend using Qiskit to explore famous thought experiments (e.g. the famous Schrödinger's cat), vide "A Physics Lab Inside Your Head: Quantum Thought Experiments as an Educational Tool" by Maria Violaris https://arxiv.org/abs/2312.07840
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