You might find Round-Trip Correctness: A New Metric for Generative AI-Based Process Modeling useful - https://news.ycombinator.com/item?id=49033317

Also see resources at https://news.ycombinator.com/item?id=49269323

You might find the paper Verification for legacy programs by Michael Ernst useful - https://homes.cs.washington.edu/~mernst/pubs/legacy-verifica...

Also see Round-Trip Correctness: A New Metric for Generative AI-Based Process Modeling - https://news.ycombinator.com/item?id=49033317

> Public posts on the internet are acceptable (to me).

Everybody needs to rethink this again.

Before LLMs the barrier to entry for building a character profile based on your various public posts was quite high. Remember "Psychographics" (https://en.wikipedia.org/wiki/Psychographics) and the infamous "Cambridge Analytica"?

Earlier it involved data mining, data cleaning, structuring data, building models, running algorithms and then evaluating the results for semantic information. Now it is straight to unfiltered semantic inference using a single sentence prompt (eg. point it to your HN profile and see what you get).

I actually did this on my HN profile and found it troubling. There were many unwarranted/hallucinated inferences due to the fact that it requires "commonsense reasoning" (https://en.wikipedia.org/wiki/Commonsense_reasoning), understanding human motivations and behaviour, context, assumptions, societal knowledge etc. which LLMs are bad at.

PS: You can cut-and-paste the above paras into a LLM prompt and ask it to elaborate for further details. The system itself will explain to you the problems/deficiencies which are quite scary.

So what might have been the incentive for OpenAI to do all this shenanigans?

It might have to do with the upcoming IPO and getting its models certified for AGI and getting out of lockin with Microsoft - https://deadneurons.substack.com/p/the-quiet-unwinding-of-mi...

When it comes to corporations/companies, always follow the money.

Tristan Buckmaster, the mathematician at the center of it (https://cims.nyu.edu/~tristanb/) put out a public statement that everybody should read (pdf) - https://cims.nyu.edu/~tristanb/statement.pdf

So what might have been the incentive for OpenAI to do all this shenanigans? It might have to do with getting its models certified for AGI and getting out of lockin with Microsoft - https://deadneurons.substack.com/p/the-quiet-unwinding-of-mi...

Interesting, didn't know of this. Some resources;

The ATS Programming Language - https://www.cs.bu.edu/~hwxi/atslangweb/

ATS3-Xanadu - https://github.com/githwxi/ATS-Xanadu

From https://en.wikipedia.org/wiki/ATS_(programming_language)

As of 2024, ATS/Xanadu (ATS3) is being developed actively in ATS2, with the hope of reducing the learning needed by two main improvements:

- Adding an extra layer to ATS2 to support ML-like algebraic type-checking

- Type-based metaprogramming using algebraic types only

With these improvements, Xi hopes for ATS to become much more accessible and easier to learn. The main goal of ATS3 is to transform ATS from a language mainly used for research, into one strong enough for large-scale industrial software development.

> I suspect that there is a body of C programmers out here that use C on a regular basis that aren’t posting who know that using C safely is 99% just using Valgrind and some specific GCC or llvm flags and you’re done.

Absolutely right! I sincerely hope they share their knowledge here and elsewhere.

> They don’t reply to these threads to share that knowledge because these threads devolve into cesspools

HN is often rage-inducing when it comes to comments on C/C++/Fortran/Cobol/etc. older languages and systems. There are many critical and industrial-strength systems developed by the previous generation of engineers/programmers which today's noobs/cargo-cultists cannot even hope to imagine much less understand.

As an example, people talk about all the great features provided by Erlang but forget that its BEAM VM where most of the "magic" resides is actually written in C! Imagine how much expertise lies buried in its implementation!

That is called Trusted Computing Base in security speech, having ensure Erlang runtime implementation is safe, is a much reduced effort than certifying a telecommunications distributed application 100% written in C as equally safe under the same attack vectors.

Security Standards/Frameworks like "TCB" (https://en.wikipedia.org/wiki/Trusted_computing_base), "Common Criteria" (https://en.wikipedia.org/wiki/Common_Criteria) etc. are not what i am talking about here. I am pointing to the fact that there is a large piece of industrial-strength C code (i.e. BEAM/ERTS) whose architecture/complexity/techniques are manifested as the "features" of another higher-level language (i.e. Erlang). People seem to appreciate the latter while not comprehending the former. The underlying C-based infrastructure is so good that there are now multiple different-paradigm languages targeting the BEAM.

Incidentally, the C implementation of BEAM/ERTS is not formally verified; only some parts of the upper-layer intermediate representation and bytecode have been verified (academic). Also an Erlang distributed cluster was designed to operate only within an already secure network (i.e. telephone network) and not on today's public Internet. So if you want to run Erlang securely you would need to know overall system security architectures and follow advice given by the "Erlang Ecosystem Foundation Security Working Group" - https://security.erlef.org/