>We would need all the intellect in the world to get the interface narrow enough to be usable,

It seems Dijkstra is describing potential calability of LLM model trained on published collective human knowledge enabled by the Internet

>and, in view of the history of mankind, it may not be overly pessimistic to guess that to do the job well enough would require again a few thousand years

Since the article was written in 1978 (about 50 years ago) and from the time the computing resources of CPU and RAM has increased exponentially until the LLM first appeared in 2020s, it seems the thousand of years prediction is merely several decades accelerated by the rapid advances of computer and communication systems technology spearheaded by companies like Nvidia.

LLM interfaces on everything these days equate to touch screen on cars. It is definitely a useful tool, but generally speaking, that's not how you'd talk to your computer.

I am surprised that cs.utexas.edu uses a TLS certificate chain who's root is eMudhra's "emSign Root TLS CA - G1".

There’s em dashes in that 1978 article.

           In order to make machines significantly easier to use, it has been
    proposed (to try) to design machines that we could instruct in our native
    tongues.  This would, admittedly, make the machines much more complicated,
    but, it was argued, by letting the machine carry a larger share of the
    burden, life would become easier for us.  It sounds sensible provided you
    blame the obligation to use a formal symbolism as the source of your dif-
    ficulties.

    transcribed by Tristram Brelstaff
    revised Fri, 19 Nov 2010

This article shows every now and then, and it's a must read. Indeed the natural language programming requires massive clusters of gpus just to make a half baked crud app

App stores are approving an order of magnitude increase of new apps because people are now able to create them using natural language. End users are deriving great value from them. So this is settled?

I find c++ very unnatural, since it's a giant collection of small rules in the end more complex than assembler. I can't remember the entire sintaxis, zoo of function decorators, undefined behavior, intrinsics which are just labels over asm instructions, Code golf sintaxis...

Dijkstra elegantly explains why AI systems are effective at mathematics and programming but much less effective when writing prose or other realms where what is good is nebulously defined:

> "The virtue of formal texts is that their manipulations, in order to be legitimate, need to satisfy only a few simple rules; they are, when you come to think of it, an amazingly effective tool for ruling out all sorts of nonsense that, when we use our native tongues, are almost impossible to avoid."

Fun fact: there are over 600 definitions of the word "run" and over 400 for "set". But yeah, English is really precise enough for programming.

How many times have we seen that there's been a spec for something and the programmers write something that is exactly like the spec said but was completely wrong?

Natural language as code has existed for thousands of years. Today we call it legalese.

It's excruciating to write, excruciating to read, and even legit geniuses with decades of hard won experience still leave room for essentially infinite interpretation. laws and contracts are all still swiss cheese and can be made to demand or prohibit whatever the party with the most money or other influence wants.