Things actually have gotten more and more closed, e.g. of stuff getting paywalled with time:It appears that things got really bad starting in 2017, possibly when WebLearn was introduced. When things migrated to Canvas, they were closed by default, apparently with any mechanism to publish publicly.
Therefore, they managed to make things more closed than when teachers would just upload to good old ox.ac.uk/~name static websites!!
Ciro Santilli has also heard that some people in the Mathematical Institute of the University of Oxford opposed to moving away from their Moodle instance precisely because the new options did not support open publishing, so kudos to those people. But most teachers likely don't care and just do whatever is the best internally supported default.
Their "open" video material: podcasts.ox.ac.uk/ A somewhat small part is Creative Commons, but most proprietary. Despite the name "podcasts", they do contain video, it is just a relic.
podcasts.ox.ac.uk/open contains actual Creative Commons only it seems.
It does however appear that professors own their lecture notes, so there some hope maybe: governance.admin.ox.ac.uk/legislation/statute-xvi-property-contracts-and-trusts#collapse1383636
Video 1.
University of Oxford documentary by the British Council (1941)
Source.
Functional Updated 2025-07-16
A function that takes input function and outputs a real number.
Joule Updated 2025-07-16
Open boundary condition Updated 2025-07-16
In the context of wave-like equations, an open-boundary condition is one that "lets the wave go through without reflection".
This condition is very useful when we want to simulate infinite domains with a numerical method. Ciro Santilli wants to do this all the time when trying to come up with demos for his physics writings.
Here are some resources that cover such boundary conditions:
The first thing we had to do with the sample was to extract the DNA present in the water in a pure form for the PCR.
As you would expect, this consists of a purification procedure with several steps.
In each step we take a physical or chemical action on the sample, which splits it into two parts: the one with the DNA and the one without.
We then take the part with the DNA, and throw away the one without the DNA.
The first steps are coarser, and finer and finer splits are done as we move forward.
PuntSeq is a side project led by a few University of Cambridge PhDs that aims to determine which bacteria are present in the River Cam.
In July 2019, the PuntSeq team got together with the awesome Cambridge Biomakespace, an awesome biology makerspace open to all, to create a two day science outreach activity showing their procedures.
The data collected in this experiment, together with other collection sessions done by the organizers actually led to a publication on eLife: elifesciences.org/articles/61504 "Freshwater monitoring by nanopore sequencing" by Lara Urban et al. (2021), so it is awesome to see that were are actual being part of "real science".
Ciro knows nothing about biology, but since he is very curious about it, he jumped at this opportunity, and decided to document things as well as his limited knowledge would allow.
All participants chipped in some money to help cover the experiment's costs. Ciro suspects that this activity was done partially to help crowdfund the experiment, but it was a worthy investment!
The impressions you get from the experiment as a software engineer will be:
  • OMG, this is so labour intensive, why haven't they automated this
  • OMG, this is frightening, all the 8 hours of work I've just done are present in that tiny plastic tube
  • Amazing! Look at that apparatus! And the bio people are like: I've used this a million times, it's cheap and every lab has one, just work faster and don't break you piece of junk!
Drake (robotics software) Updated 2025-07-16
The Robotics team at TRI is working hard to close the gap between simulation and reality. For manipulation, one important piece is accurate simulation of rigid-body contact.
Bought: November 2023 during Black Friday sale for £1,323.00 to be Ciro Santilli's main personal laptop.
Six years after, and we are 2x on every key spec (except processor Hz ;-) at about 1/2 the price and 1/2 the weight (though smaller 14" screen for greater portability), so not bad! Customized to max out each hardware spec:
Specs:
Identifiers:
Upon arrival:
  • Weight: 1490 g
  • Charger weight: 323 g
  • Firmware according to sudo dmidecode -t bios:
    Vendor: LENOVO
    Version: R2FET33W (1.13 )
    Release Date: 09/08/2023
Buy research:
Log:
2024-01-17: firmware update:
Vendor: LENOVO
Version: R2FET36W (1.16 )
Release Date: 10/24/2023
Actually fixed performance mode: askubuntu.com/questions/604720/setting-to-high-performance/1343879#1343879
  • always upvote questions you care about, to increase the probability that they will get answered
  • never upvote other people's answers unless you might gain from it somehow, otherwise you are just giving other high reputation users more reputation relative to you
  • only mark something to close or as a duplicate if it will bring you some advantage, because closing things creates enemies, especially if the OP has a high profile
    One example advantage is if you have already answered the question (and the duplicate as well in case of duplicates), because this will prevent competitors from adding new better answers to overtake you.
  • protect questions you've answered whenever someone with less than 10 reputation answers it with a bad answer, to prevent other good contributors from coming along and beating you
  • when you find a duplicate pool answer every question with similar answers.
    Alter each answer slightly to avoid the idiotic duplicate answer detector.
    If one of the question closes, it is not too bad, as it continues netting you to upvotes, and prevents new answers from coming in.
  • follow on Twitter/RSS someone who comments on the top features of new software releases. E.g. for Git, follow GitHub on Twitter, C++ on Reddit. Then run back to any question which has a new answer.
  • always upvote the question when you answer it:
    • the more upvotes, more likely people are to click it.
    • the OP is more likely to see your answer and feel good and upvote you
  • if a niche question only has few answers and you come with a good one, upvote the existing ones by other high profile users.
    This may lead to them upvoting or liking you.
    Even if they don't, other people will still see your answer anyway, and this will lead to people to upvoting you more just to make your great answer surpass the current ones, especially if the accepted one has less upvotes than yours. Being second is often an asset.
  • always upvote comments that favor you:
    • "I like this answer!" on your answers
    • "also look at that question" when you have answered that question
  • don't invest a lot in edits. They don't give you rep, and they can get reverted and waste your time.
    Why are you trying to help other people's answers to get rep anyways? Just make a separate answer instead! :-)
  • if you answer a question by newbie without 15 reputation, find their other questions if any and upvote them, so that the OP can upvote your answer in addition to just accepting
  • If you haven't answered a question, link to related questions you've answered on question comments, so more people will come to your answers.
    If you have answered the question, only link to other questions at the bottom of your answer, so that people won't go away before they reach your answer, and so as to strengthen your answer.
  • if a question has 50 million answers and you answer it (often due to a new feature), make a comment on the question pointing to your answer
  • if you get a downvote, always leave a comment asking why. It is not because you care about their useless opinion, but because other readers might see the comment, feel sorry for you, and upvote.
  • ask any questions under a separate anonymous accounts. Because:
    • intelligent people are born knowing, and don't ever ask any questions, so that would hurt your reputation
    • downvoting questions does not take 1 reputation away from the downvoter, and so it greatly opens the door for your opponents to downvote you without any cost.
Three-level laser Updated 2025-07-16
The type of laser described at: Video "How Lasers Work by Scientized (2017)", notably youtu.be/_JOchLyNO_w?t=581. Mentioned at: youtu.be/_JOchLyNO_w?t=759 That point also mentions that 4-level lasers also exist and are more efficient. TODO dominance? Alternatives?
Video 1.
Three-level laser system by Dr. Nissar Ahmad (2021)
Source.
Ollama Updated 2025-07-16
Ollama is a highly automated open source wrapper that makes it very easy to run multiple Open weight LLM models either on CPU or GPU.
Its README alone is of great value, serving as a fantastic list of the most popular Open weight LLM models in existence.
Install with:
curl https://ollama.ai/install.sh | sh
The below was tested on Ollama 0.1.14 from December 2013.
Download llama2 7B and open a prompt:
ollama run llama2
On P14s it runs on CPU and generates a few tokens per second, which is quite usable for a quick interactive play.
As mentioned at github.com/jmorganca/ollama/blob/0174665d0e7dcdd8c60390ab2dd07155ef84eb3f/docs/faq.md the downloads to under /usr/share/ollama/.ollama/models/ and ncdu tells me:
--- /usr/share/ollama ----------------------------------
    3.6 GiB [###########################] /.ollama
    4.0 KiB [                           ]  .bashrc
    4.0 KiB [                           ]  .profile
    4.0 KiB [                           ]  .bash_logout
The file:
/usr/share/ollama/.ollama/models/manifests/hf.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF/Q2_K
gives a the exact model name and parameters.
We can also do it non-interactively with:
/bin/time ollama run llama2 'What is quantum field theory?'
which gave me:
0.13user 0.17system 2:06.32elapsed 0%CPU (0avgtext+0avgdata 17280maxresident)k
0inputs+0outputs (0major+2203minor)pagefaults 0swaps
but note that there is a random seed that affects each run by default. ollama-expect is an attempt to make the output deterministic.
Some other quick benchmarks from Amazon EC2 GPU on a g4nd.xlarge instance which had an Nvidia Tesla T4:
0.07user 0.05system 0:16.91elapsed 0%CPU (0avgtext+0avgdata 16896maxresident)k
0inputs+0outputs (0major+1960minor)pagefaults 0swaps
and on Nvidia A10G in an g5.xlarge instance:
0.03user 0.05system 0:09.59elapsed 0%CPU (0avgtext+0avgdata 17312maxresident)k
8inputs+0outputs (1major+1934minor)pagefaults 0swaps
So it's not too bad, a small article in 10s.
It tends to babble quite a lot by default, but eventually decides to stop.
C library Updated 2025-07-16
Clickbait Updated 2025-07-16

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