Ciro Santilli @cirosantilli 37

Remarkable 2 is really, really good. Relatively fast refresh + touchscreen is amazing.

No official public feedback forum unfortunately:

PDF table of contents could be better: twitter.com/cirosantilli/status/1459844683925008385

Of course, if academic journals require greater reproducibility for publication, then the cost per paper increases.

However, the total cost has to be smaller than the cost everyone who reads the paper spends to reproduce, no?

The truth is, part of the replication crisis is also due to research groups not wanting to share their precious secrets with others, so they can keep ahead of the publication curve, or maybe spin off a startup.

And when it comes to papers, things are even crazier: big companies manage to publish white papers in peer reviewed journals.

Ciro Santilli wants to help in this area with his videos of all key physics experiments project idea.

Cool initiative. Papers that do not share source code should be banned from peer reviewed academic journals.

Closed source on offline products used by millions of people is evil, when you could just have those for free with open source software! Thus Ciro's hatred for Microsoft Windows and MacOS (at least userland, maybe).

There's no point.

The question remains there, but people lose the ability to help the asker.

Reputation is meaningless regardless, since JavaScript gurus will always have 1000x more readers than low level junkies.

The deeper problem: the existence of multiple separate websites instead of just using the tags on a single website.

Examples:

CNN convolution kernels are not hardcoded. They are learnt and optimized via backpropagation. You just specify their size! Example in PyTorch you'd do just:as used for example at: activatedgeek/LeNet-5.

This can also be inferred from: stackoverflow.com/questions/55594969/how-to-visualise-filters-in-a-cnn-with-pytorch where we see that the kernels are not perfectly regular as you'd expected from something hand coded.

The CNOT gate is a controlled quantum gate that operates on two qubits, flipping the second (operand) qubit if the first (control) qubit is set.

This gate is the first example of a controlled quantum gate that you should study.

To understand why the gate is called a CNOT gate, you should think as follows.

First let's produce a generic quantum state vector where the control qubit is certain to be 0.

On the standard basis:we see that this means that only $|00⟩$ and $|01⟩$ should be possible. Therefore, the state must be of the form:where $x$ and $y$ are two complex numbers such that $|x|+|y|=1.0$

If we operate the CNOT gate on that state, we obtain:and so the input is unchanged as desired, because the control qubit is 0.

If however we take only states where the control qubit is for sure 1:

Therefore, in that case, what happened is that the probabilities of $|10⟩$ and $|11⟩$ were swapped from $x$ and $y$ to $y$ and $x$ respectively, which is exactly what the quantum NOT gate does.

So from this we understand more concretely what "the gate only operates if the first qubit is set to one" means.

Now go and study the Bell state and understand intuitively how this gate is used to produce it.

This is the most plausible way of obtaining a full connectome looking from 2020 forward. Then you'd observe the slices with an electron microscope + appropriate Staining. Superintelligence by Nick Bostrom (2014) really opened Ciro Santilli's eyes to this possibility.

Once this is done for a human, it will be one of the greatest milestone of humanities, coparable perhaps to the Human Genome Project. BUt of course, privacy issues are incrediby pressing in this case, even more than in the human genome project, as we would essentially be able to read the brain of the person after their death.

As of 2022, the Drosophila connectome had been almost fully extracted.

This is also a possible path towards post-mortem brain reading.

Finance is a cancer of society. But I have to admit it, it's kind of cool.

arstechnica.com/information-technology/2016/11/private-microwave-networks-financial-hft/ The secret world of microwave networks (2016) Fantastic article.

Finding a complete basis such that each vector solves a given differential equation is the basic method of solving partial differential equation through separation of variables.

The first example of this you must see is solving partial differential equations with the Fourier series.

Notable examples:

A: