In a way, Agilent represents the most grassroots electronics parts of HP from before they became overly invested in laptops and fell.

They spun out the electronics part as Keysight in 2014, becoming life science only.

Bluetooth support: not enough RAM for it, though in principle its chip/transceiver could support it! microbit-micropython.readthedocs.io/en/v1.0.1/ble.html

Supported editors: microbit.org/code/

MicroPython web editor and compiler: python.microbit.org/v/2

Everything in this section is tested on the Micro Bit v1 from Micro Bit v1 unless otherwise noted.

Bibliography:

Microbit simulator using some Microsoft framework.

TODO the Python code from there does not seem to run on the microbit via uflash, because it is not MicroPython.

support.microbit.org/support/solutions/articles/19000111744-makecode-python-and-micropython explains.

forum.makecode.com/t/help-understanding-local-build-options/6130 asks how to compile locally and suggests it is possible. Seems to require Yotta, so presumably compiles?

Presumably this is because Microsoft ported their MakeCode thing to the MicroBit, and the Micro Bit foundation accepted them.

E.g. there toggling a LED:but the code that works locally is a completely differently named API set_pixel:Microsoft going all in on adopt extend extinguish from an early age!

When plugged into Ubuntu 22.04 via the USB Micro-B the Micro Bit mounts as:e.g.:for username ciro.

Loading the program is done by simply copying a .hex binary into the image e.g. with:The file name does not matter, only the .hex extension.

The back power light flashes while upload is happening.

Flashing takes about 10-15 seconds for the 1.8 MB scroll display hello world from microbit-micropython.readthedocs.io/en/v1.0.1/tutorials/hello.html:and the program starts executing immediately after flash ends.

You can restart the program by clicking the reset button near the USB. When you push down the program dies, and it restarts as soon as you release the button.

Both are harmonic oscillators.

In the LC circuit:

You can kickstart motion in either of those systems in two ways:

Instrumentation basically means adding loggers/print statements to certain points of interest of your hardware/software.

Instrumentation tends to slow execution down a bit, but way less than emulation.

The downside is that if the instrumentation does not provide you the data you need to debug, there's not much you can do, you will need to modify it, i.e. you don't get full visibility from instrumention.

This is unlike emulation that provides full observability.

Some of the earlier computers of the 20th centure were analog computers, not digital.

At some point analog died however, and "computer" basically by default started meaning just "digital computer".

As of the 2010's and forward, with the limit of Moore's law and the rise of machine learning, people have started looking again into analog computing as a possile way forward. A key insight is that huge floating point precision is not that crucial in many deep learning applications, e.g. many new digital designs have tried 16-bit floating point as opposed to the more traditional 32-bit minium. Some papers are even looking into 8-bit: dl.acm.org/doi/10.5555/3327757.3327866

As an example, the Lightmatter company was trying to implement silicon photonics-based matrix multiplication.

A general intuition behind this type of development is that the human brain, the holy grail of machine learning, is itself an analog computer.

They died so completely, Googling "ICL" now has higher hits such as Imperial College London.

"Free drift" can refer to different concepts depending on the context, but in a general sense, it often describes a state where something is allowed to move or operate without restraint or control.

Borrow from the Internet Archive for free: archive.org/details/supermenstory00murr

Initial chapters put good clarity on the formation of the military-industrial complex. Being backed by the military, especially just after World War II, was in itself enough credibility to start and foster a company.

It is funny to see how the first computers were very artisanal, made on a one-off basis.

Amazing how Control Data Corporation raised capital IPO style as a startup without a product. The dude was selling shares at dinner parties in his home.

Very interesting mention on page 70 of how Israel bought CDC's UNIVAC 1103 which Cray contributed greatly to design, and everyone knew that it was to make thermonuclear weapons, since that was what the big American labs like this mention should be added to: en.wikipedia.org/wiki/Nuclear_weapons_and_Israel but that's Extended Protected... the horrors of Wikipedia.

Another interesting insight is how "unintegrated" computers were back then. They were literally building computers out of individual vacuum tubes, then individual semiconducting transistors, a gate at a time. Then things got more and more integrated as time went. That is why the now outdated word "microprocessor" existed. When processors start to fit into a single integrated circuit, they were truly micro compared to the monstrosities that existed previously.

Also, because integration was so weak initially, it was important to more manually consider the length of wire signals had to travel, and try to put components closer together to reduce the critical path to be able to increase clock speeds. These constraints are also of course present in modern computer design, but they were just so much more visible in those days.

The book does unfortunately not give much detail in Crays personal life as mentioned on this book review: www.goodreads.com/review/show/1277733185?book_show_action=true. His childhood section is brief, and his wedding is described in one paragraph, and divorce in one sentence. Part of this is because he was very private about his family most likely note how Wikipedia had missed his first wedding, and likely misattribute children to the second wedding; en.wikipedia.org/wiki/Talk:Seymour_Cray section "Weddings and Children".

Crays work philosophy is is highlighted many times in the book, and it is something worthy to have in mind:

Cray's final downfall was when he opted to try to use a promising but hard to work with material gallium arsenide instead of silicon as his way to try and speed up computers, see also: gallium arsenide vs silicon. Also, he went against the extremely current of the late 80's early 90's pointing rather towards using massively parallel systems based on silicon off-the-shelf Intel processors, a current that had DARPA support, and which by far the path that won very dramatically as of 2020, see: Intel supercomputer market share.