The Trader Joe's at University and MLK is very recent, only since 2010 [1]. It used to be an auto-parts store before. Perhaps it used to be a grocery store back in 1955?
To put it in terms of what the audience here can relate to:
multiplication is an overloaded operation, or in more modern terms, it is doing multiple dispatch, depending on whether the input is a whole number or integer or rational or real or complex
The meme that the GPL is "less free" sounds very Orwellian.
What it really means is that I cannot freely use someone else's creation without restriction, and that I have to respect the wishes of the original author about how their work should be used.
That is because GPL was intended to be a hack on the copyright system (hence "copyleft"), but it always respected the idea of copyright - it does not call for the abolition of copyright.
This talk of GPL being "not free" smells of propaganda so that people (big corporations?) can reuse and repackage others' valuable work for free without any kind of compensation or acknowledgement. (TFA says the same thing)
Feel free not to use GPL'ed code if you find it too restrictive, but please don't contribute to spreading propaganda against it (and get off my lawn while you're at it)
[For the record, I work on proprietary software myself and haven't written any FOSS code, but I use GPL software daily - Linux, gcc, emacs etc]
"Resonance occurs when two sources of excitation fall completely in sync, and reinforce one another endlessly."
This is incorrect, even according to the wikipedia article it links to.
Resonance occurs when the excitation frequency matches a natural frequency of the system being excited, causing it to vibrate at larger amplitudes, even perhaps uncontrollably.
It seems that the author misunderstands mixing also - the graph that he presents for the mixed signal seems to be incorrect according to the other wikipedia article he links to.
Finding the closest point for an ellipsoid is more challenging in practice, because one needs to take a different parametrization near a pole, and sometimes conjugate gradient is necessary to get convergence.
You seem to be conflating "numerical computing" with machine learning. However, numerical computing typically involves solving PDEs via e.g. finite elements or finite differences, or solving large systems of linear equations associated with such methods.
The difference between the two is that when solving PDEs, accuracy is paramount, so even using single precision is a bit of a compromise, whereas in machine learning, the trend seems to be to use half-precision or lower, sacrificing accuracy for speed.
For classical numerical computing, e.g. solving PDEs or linear equations, Java may not be the best choice, e.g. see the following paper:
How Java's Floating Point Hurts Everyone Everywhere:
You can read Sokal's various commentaries on this topic. His point was that many philosophers tried to make grandiose statements about science and mathematics that did not make sense at all. The philosophers were making statements based on their imagination of what certain terms meant, and not on the actual meaning of those terms.
Please keep in mind that the book by Bruno Latour referenced here (Science in Action) and another of his articles was lampooned in the Sokal Affair because Latour was confused about relativity:
I don't disagree that badly-written scientific code exists (both in academia and in the industry), but I want to point out a couple of things for people who have only a software engineering background.
1. Keep in mind that most scientific code for numerical analysis, being based in mathematics, follows the convention for using algebraic symbols, e.g. even in physics, we write
F=m*a
instead of the wordy version, which we overcame a couple of centuries ago. So using shortened variable names [1] comes from that background, and using longer names as in Java-world seems like a regression.
2. Writing code like [2]
Ax_1 += Bx_1 + Cx_1 # Add Bx_1 to Cx_1
Ax_2 += Bx_2 + Cx_2 # Same thing, but for Ax_2
Ax_3 += Bx_3 + Cx_3 # "
Ay_1 += By_1 + Cy_1 # "
is known as loop unrolling [3,4] and is used for optimization.
I made my first offer to a full-time employee, who could add necessary medical expertise to the team. She chose us over an existing offer and gave notice to her current employer.
According to the Wikipedia entry [1] and other pages mentioned in another comment [2], the statue was found with a fragment of a left hand holding an apple, and a right hand with a draped sash. This was taken to understand that the statue represented the Judgement of Paris [3].
So apparently it is known what the hands held, which seems to make this speculation unnecessary.
Here's how you can apply this interpretation of matrix multiplication:
Think of the columns of the matrix A as basis vectors of a coordinate system represented in global coordinates, and the vector v as the components of a vector in that coordinate system. Then the product A * v transforms the vector v into the global coordinate system.
Carrying this forward, matrix multiplication A * B gives the combined representation of two coordinate transformations.
[1] https://www.sfgate.com/bayarea/place/article/Complex-houses-...