I copied the code from the book and then did my own mods. I also ended up rewriting the engine with 6502 assembly macros. That made me realize, and appreciate, high level languages that had first order functions and very different approaches to computing and data structures, in contrast with BASIC arrays, gotos and gosubs. At the same time I was learning to program in Logo, which, without being aware of, introduced me to the world of Lispy languages and what computing really is. That tainted me a bit and left me a bit frustrated when I moved on to C and, much later in the 90s, to C++.
I learned to program with some of these books. Usborne also quickly published them in Spanish, and I was lucky that some editorial companies used to go to my school to sell their books. I grabbed the machine code and adventure programs. That was 1985 and I was 10 years old. Still looking at the drawings brings me good memories and goosebumps.
True. I have often encountered motion controllers where the implementer failed to realize that calculating derived variables like acceleration from position and velocity using a direct derivative formula will violate the Nyquist condition, and therefore yields underperforming controllers or totally noisy signal inputs to them. You either need to adjust your sample or control loop rates, or run an appropriate estimator. Depending on the problem it can be something sophisticated like an LQR/KF, or even in some cases a simple alpha-beta-gamma filter (poor version of a predictor-corrector process) can be adequate.
I mostly learned programming GUI applications, in Xwindow and in general, studying the code of xv. The GUI controls were written from scratch using X resources and the code quality was top notch. I remember printing the full source code back in the winter break of 1994 at my university printers since I was going on vacations with my family and I was going to be completely disconnected. I studied the code writing side notes every time I had a moment to relax. Good times. Many thanks, John.
It seems that common sense is very difficult to program. Perhaps because we don't really know how to properly define it or how an encoding of it would look like.
All of these models keep trying to convince me they can solve the Post Correspondence Problem.
People print guns and gun parts. More than you think. Now even more since metal printing is starting to become affordable. I print grip and grip attachments for my 9mms and my AR15, trigger guards, barrel clamps, etc. I also find it stupid since, as the article suggests, what kind of algorithm can you implement to do smart detection of something that could be potentially dangerous? Will it also detect negative space? I print inserts in elastic filament with my gun outlines instead of foam (or as foam templates) for my carrying cases. Will the "algorithm" prevent me to do that too? What about my plastic disc thrower toy gun, or my PKD Blaster prop? Both look like guns to me. What about a dumb AI algorithm that lacks common sense?
Printing barrels and FCUs -- the fire control unit, which is the only thing tracked and serialized in a gun at least in the US -- is more difficult but not impossible. Actually, building a functional FCU that can strike a bullet primer, or a barrel that can be used once is not difficult at all and if you look around you can find videos of people that have tested that with a mixture of 3d printing and rudimentary metal working skills. The major issues on designing those parts are reliability and safety. In the Philippines there is a full bootleg gunsmith industry dedicated to build illegal guns that match commercial ones in those aspects too.
Sadly, instead of having better laws we get fallacy rhetoric by people who probably have never touched, much less fired a gun in their lives.
Yet he did a lot of good leaving his money to academia and medical research.
I think the Egyptians had it right. Ultimately your heart will be weighted against the feather of Ma'at, and it is up to the goddess to decide. We mere mortals don't know the true intentions and circumstances of other people and their lives to judge, nor to throw the first stone.
Statements like these always brings me to memory the opening line of Hamming's Numerical Methods book: The purpose of computing is insight, not numbers. It is very easy to get carried away and forget that - in particular today when processing power grows exponentially. Even more when we know there are a myriad of problems that are uncomputable, literally, and human common sense and intuition (insight) are as relevant now as ever.
Correct, the famous d*F=J differential form formulation with one of the versions of the Hodge operator, which I have seen named in several ways. Also depending on your definition of the star operator and current density, you often see this as two equations with Hodge duals, like dF=0 plus d*F=*J. The tensor equivalent can be stated as a single equation or as a set, too.
To be fair and looking back at history, the discovery of Maxwell equations, relativity and quantum theory are so intertwined with the discovery, invention and application of new Mathematical ideas, in particular emanating from the work of Hamilton, Grassmann and then Lie, Levi-Civita, Cartan, etc. that is difficult to separate at what extent those concepts influenced over each other in their attempt to explain and describe reality. The ability to express Maxwell equations in a compact form with quaternions before vector calculus was even a thing provides some evidence. One can argue that the classical formulation for electromagnetism could be expressed that way because Hamilton was trying to find the proper framework that could capture his ideas about physics. Fast forward some 60 years and you also have a similar thing happening with Pauli matrices in quantum theory, and the work of Noether in modern physics.
Indeed you can use symmetry, but it feels more like a mathematical hack, and the fact that it agrees with reality could be a coincidence. You can state that, and there is a lot of evidence for, that nature follows some basic geometrical rules. Applying that through a Lie theory framework on a symplectic manifold to see how charges behave differentially will eventually get you to Maxwell equations because of how those Lie algebras operate. However for me the real revelation was just using the Lienard–Wiechert approach to calculate how charged particles should behave in a relativistic field, which is as simple as it gets, and then see that you can build the full electromagnetic theory on top of that, with the bonus that the formulation is already relativistic. The same resulting symmetry in a corresponding Lie group is consequence of that (nicely captured by Hodge's equation), and invariance or operator rules don't need to be forced.
What I always miss from this introductory abridged explanations, and what makes the connection between Lie groups and algebras ('infinitesimal' groups) really useful, is that the exponential process is a universal mechanism, and provides a natural way to find representations and operators (eg Lie commutator, the BCH formula) where the group elements can be transformed through algebraic manipulations and vice-versa. That discovery offers a unified treatment of concepts in number theory, differential geometry, operator theory, quantum theory and beyond.
Which for some of us, Spanish speakers, was on occasion amusing or lewd, depending on the context and culture. The Spanish equivalent is 'tronco' which is very similar and it is slang for a couple of things.
They also mainly continued to be loyal to the Spanish crown after Argentina and Chile went through their independence, and carried out the final pacification of the Mapuche territories in the 19th century. By then only a very small part of the population had not mingled with Europeans.
You would have thought they learned from their mistakes implementing VST2, but they doubled down going even further basing VST3 on the Windows Component Object Model. I guess it was a decision to avoid reinventing the wheel, but you can quickly realize it is a very bad model for real time audio plugins and audio host support. The API just exploded in complexity, and testing was a nightmare. In contrast you can tell the U-He developers have all the experience from the trenches.
Today I drove past a new Tesla Model Y, still with a temporary paper tag. As I was passing by I immediately noticed some pretty heavy water condensation inside one of the lateral tail braking lights. I just rolled my eyes.
Ahh... Brings me memories. Back in the 80s I did something similar after reading Dawkin's The Blind Watchmaker and his Biomorph evolution app. I wanted to recreate it but doing something more fun. So I hacked an Atari Logo space invaders game that used genetic programming on the invaders that survived most of the hits based on their shape (some pixels worked as shields) and motion. After 5 levels the game was almost impossible to beat.
To be fair, any multivariable regulator or filter (estimator) that has a quadratic component (LQR/LQE) will naturally yield a solution similar to backpropagation when an iterative algorithm is used to optimize its cost or error function through a differentiable tangent space.