Education of André-Marie Ampère Created 2024-06-26 Updated 2025-07-16
en.wikipedia.org/w/index.php?title=Andr%C3%A9-Marie_Amp%C3%A8re&oldid=1211946256:
Jean-Jacques Ampère, a successful merchant, was an admirer of the philosophy of Jean-Jacques Rousseau, whose theories of education (as outlined in his treatise Émile) were the basis of Ampère's education. Rousseau believed that young boys should avoid formal schooling and pursue instead a "direct education from nature." Ampère's father actualized this ideal by allowing his son to educate himself within the walls of his well-stocked library.
TODO find the source for this.
Electrical cable Created 2024-06-26 Updated 2025-07-16
One more more electrical wires surrounded by an insulator.
Oliver Heaviside Created 2024-06-26 Updated 2025-07-16
He participated in the development of the electrical telegraph, and he did some good modeling work that improved the foundations of the field, notably creating the telegrapher's equations.
He was one of those idealists who just want to do some cool work even if they have to starve for it, people had to get a state pension for him for his contributions. Nice guy. en.wikipedia.org/w/index.php?title=Oliver_Heaviside&oldid=1230097796#Later_years_and_views:
In 1896, FitzGerald and John Perry obtained a civil list pension of £120 per year for Heaviside, who was now living in Devon, and persuaded him to accept it, after he had rejected other charitable offers from the Royal Society.
He also never married: www.nndb.com/people/627/000204015/
Figure 1.
Oliver Heaviside c. 1900
. Source.
We intersect 2013 DNS Census virtual host cleanup with 2013 DNS census MX records and that leaves 460k hits. We did lose a third on the the MX records as of 260 hits since secureserver.net is only used in 1/3 of sites, but we also concentrate 9x, so it may be worth it.
Then we Wayback Machine CDX scanning. it takes about 5 days, but it is manageale.
We did a full Wayback Machine CDX scanning for JAR, SWF and cgi-bin in those, but only found a single new hit:
Tinker Tailor Soldier Spy (film) Updated 2025-07-16
This is not bad, but some divergences to the better BBC miniseries, which presumably sticks more closely to the novel:
  • in the film Jim Prideaux is captured in a cafe in Prague, in the series it's in the woods. It is therefore much more plausible that he would have been shot.
  • in the film Peter Guillam is played by Benedict Cumberbatch, who feels a bit young to be Ricki Tarr's boss. Not impossible, but still.
  • the series is much less chronological, and more flashback based, as new information becomes available. The film is more chronological, which makes it easier to understand, but less interesting at the same time.
  • in the film they shoot the Russian girl Irina in front of Jim, in the series the fact that she was shot is only known through other sources. The film has more eye candy, which weakens it.
  • Toby Esterhase is not threatened in an airfield, only in a safe ;house in London.
How large primes are found for RSA Updated 2025-07-16
Answers suggest hat you basically pick a random large odd number, and add 2 to it until your selected primality test passes.
The prime number theorem tells us that the probability that a number between 1 and is a prime number is .
Therefore, for an N-bit integer, we only have to run the test N times on average to find a prime.
Since say, A 512-bit integer is already humongous and sufficiently large, we would only need to search 512 times on average even for such sizes, and therefore the procedure scales well.
Human Compatible Updated 2025-07-16
The key takeaway is that setting an explicit value function to an AGI entity is a good way to destroy the world due to poor AI alignment. We are more likely to not destroy by creating an AI whose goals is to "do want humans what it to do", but in a way that it does not know before hand what it is that humans want, and it has to learn from them. This approach appears to be known as reward modeling.
Some other cool ideas:
  • a big thing that is missing for AGI in the 2010's is some kind of more hierarchical representation of the continuous input data of the world, e.g.:
  • game theory can be seen as part of artificial intelligence that deals with scenarios where multiple intelligent agents are involved
  • probability plays a crucial role in our everyday living, even though we don't think too much about it every explicitly. He gives a very good example of the cost/risk tradeoffs of planning to the airport to catch a plane. E.g.:
    • should you leave 2 days in advance to be sure you'll get there?
    • should you pay an armed escort to make sure you are not attacked in the way?
  • economy, and notably the study of the utility, is intrinsically linked to AI alignment
Brooks's law Updated 2025-07-16
Video 1.
The Misty Mountains Cold Scene from The Hobbit: An Unexpected Journey (2012)
Source.
I will take each and every one of these dwarves over an army from the Iron Hills. For when I called upon them they answered. Loayalty. Honour. And willing heart. I can ask no more than that.
Hyperparameter Updated 2025-07-16
A parameter that you choose which determines how the algorithm will perform.
In the case of machine learning in particular, it is not part of the training data set.
Hyperparameters can also be considered in domains outside of machine learning however, e.g. the step size in partial differential equation solver is entirely independent from the problem itself and could be considered a hyperparamter. One difference from machine learning however is that step size hyperparameters in numerical analysis are clearly better if smaller at a higher computational cost. In machine learning however, there is often an optimum somewhere, beyond which overfitting becomes excessive.
Total derivative Updated 2025-07-16
The total derivative of a function assigns for every point of the domain a linear map with same domain, which is the best linear approximation to the function value around this point, i.e. the tangent plane.
E.g. in 1D:
and in 2D:
A Updated 2025-07-16
Underlying field of a vector space Updated 2025-07-16
Every vector space is defined over a field.
E.g. in , the underlying field is , the real numbers. And in the underlying field is , the complex numbers.
Any field can be used, including finite field. But the underlying thing has to be a field, because the definitions of a vector need all field properties to hold to make sense.
Elements of the underlying field of a vector space are known as scalar.

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