There is a different take on Lisp in Python - fakelisp. It's literally Lisp in Python, not an interpreter, but a syntax sugar library that allows embedding Lisp snippets into valid Python.
from fakelisp import *
# And now you can start mixing Python and LISP
X = (BEGIN
(SET (F) (LAMBDA (X)
(IF (EQ (X) (1))
(1)
(MUL (X) (F (SUB (X) (1)))))))
(LIST (F (4)) (42)))
# Back to Python any time
print "x: ", str(X)
This is one of the most unexpected ecranisations ever. The book is great on its own, but I would never assumed it could become a film. The topic itself is a bit heavy, and I somehow assumed that most of the people pan Szablovski interviewed at one point or another are already dead. This is going to be a fascinating watch.
There should be a lesson for other communities but, unfortunately, there is none. StackOverflow used to be a fun and welcoming place in 2009. It became a toxic hellhole overtime
There are no obvious flows in the original design, and there were no endemic wrongdoings in the governance either. It just rotted slowly like any other community does. And nobody in the world knows how to keep communities from becoming toxic. There is simply no recipe. And that's why StackOverflow doesn't serve as a lesson either.
Students are lazy, in a good way, so they are more likely to run things on their own and play with interactive bits if the whole lecture is just one link.
The idea here is, one can pick the slides they want and arrange them into a sequence right in the URL. This way, there is no registration, no user data collection, no persistent state even. You just pick the slides, teach your material, and move on.
It's very raw, I still want to add a convenient sequence constructor, a "blank" slide so you could display your own content in it, and a similar quiz page. But I already used some of the slides for teaching, students seem to like them.
Hopefully, I'll have the rest done by the beginning of the spring semester.
The most interesting thing in this whole picture is not AGI, it's how the collective intelligence works. CEOs claim the AGI is near because that's how they manipulate the public. But the public knows that it's only a manipulation. So how come the manipulation is still possible?
Fun fact, there were no commercials in the USSR. No TV advertisements as a genre, so nobody knew how to make these. And one of the first Soviet commercials I saw was already during perestroyka, and it was about Lada. It was 15 minutes long, and it featured a line (sorry, may be misremembering it a bit) "if your brand new car doesn't start, no worries! Just take a 10mm wrench, and tighten the battery bolts. See how easy it is!"
The Fiat 124 was actually a pretty good car for its era. Russians improved its suspension, refitted the engine, and messed up the hydraulics. Still, pretty good car for the 60s. And then, they continued to produce the same car with miniscule modifications until 2010s.
That's the problem with authoritarian regimes. You can buy a plant by a fiat (pun intended), but you can't make a decent car by a decree.
There are plenty of activities that are essential for engineering but not a sort of engineering themselves. Like writing documentation, or communicating requirements to your colleagues. Making instructions and operational procedures. Management. Accounting. Marketing. What makes making software an engineering discipline and making coffee not? Where is the line and why we presume we should be behind that line?
Well, yes, but after the 75 years, don't you think that "too young" argument is getting old? Nuclear energy, medical imaging, and the space part of aerospace are all younger than "software development". These are all mature industries highly codified, and they also all also encompass software development among other things. Could it be that software development isn't an engineering discipline at all but a supporting activity?
Writing isn't an engineering discipline. And all industries rely heavily on writing. Could it be that writing software is just writing for computers and as such could only by codified within another engineering discipline and not by its own?
Most of the startups actually plan to survive for more than 2 months. And it makes total sense to think about scalability, reliability, and performance while it's still possible to change your whole stack every other week. Not forgetting about other things such as securing your cash flow, growing your talent pool, protecting your IP, etc. Finding a good balance between multiple focii is exactly the job for a founder. Of course, it's a hard job, that's why we don't see many successful startups to begin with.
Yes, reliability comes from the same ground the scalability does, and yes people are mostly chasing the latest trend. One does not contradict the other.
Some safety critical real time systems have strict time predictability requirements. This means that the whole loop should pass in exactly X microsecond, not more not less. For this, all the programming should be pretty much branchless.
For instance, all the sorting algorithm turn to, effectively, bubble sort since without branches, you always go with the worst case - and the sorting complexity is always the O(n^2). But it's okay, since the algorithm becomes predictable. You just swap a conditional swap:
Engineers believe in definitions. By definition, philosophy is not a scientific discipline, because as soon as a discipline becomes scientific it... stops being philosophy.
As Alexander Pyatigorsky famously wrote, "the value of philosophy is in that nobody needs it".
I'm not saying that philosophy is bad. Maybe making software just never meant to become an engineering discipline. I mean making clothes, laws, and music isn't. And it's fine.
There is a different take on Lisp in Python - fakelisp. It's literally Lisp in Python, not an interpreter, but a syntax sugar library that allows embedding Lisp snippets into valid Python.
https://codeberg.org/okaleniuk/fakelisp