Oh really? A 195% cost to revenue ratio isn't bad at all? I'm not a biz expert, but I spent a few minutes looking this up (e.g., what are usual cost-to-revenue ratios for new lines of business), and this sounds like BS to me.
585 karma · joined November 18, 2014
Find me at http://shonfeder.net/
Brogue looks like this: https://syltefar.com/screenshot/?id=624
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> It is with great joy that I have accepted the invitation to write you a personal letter. Even in your scientific writings your presence as a person is very strong, which is unusual for a mathematician. The traces of your personal life and your dramas extend beyond the limits of your own personal circumstances to concern us all ...
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> Perhaps the greatest catastrophe of anti-scientific computationalism can be seen in the recent theory of "The End of Theories". In a series of widely quoted articles, informaticians or managers of very large databases explain that: "Correlation supersedes causation, and science can advance even without coherent models, unified theories". In short, networked computers, bringing to light very extended correlations in huge databases, make it possible to predict and act, without the need to "understand": scientific intelligibility is an uncertain luxury that is subjective and outdated, and theories are fallible proposals. Data, especially in large quantities – tera-terabytes, Big Data – is objective, is a new form of the absolute, is individually exact, expressed in digits. Thus, they argue, the larger that databases become, the more that statistical regularities, brought to light by computers, can govern us without the need to understand the meaning of the correlations, to interpret them, and without the need for theories about them, for interpretations.
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> Fortunately, mathematics allows us to demonstrate the absurdity of these claims: Cristian Calude and I have written an article about this. Precisely the immensity of data involved has allowed us to apply the theorems of Ramsey and Van der Waerden. These make it possible to show that, given any "regularity", or any correlation between sets of numbers, you can find a number p large enough, such that every set with at least p elements contains a regularity (or a correlation between numbers) with the same structure. Now, since this applies to every sufficiently large set (with at least p elements), this also applies when it is generated … by a random process. Indeed, we observe, almost all sets of fairly large numbers are algorithmically random (one can give a mathematical definition of them, in terms of incompressibility), i.e., the percentage of non-random tends to 0 as p goes to infinity. So, if you observe regularities in increasingly large databases, it is increasingly likely that the inserted data are due to chance, in other words are perfectly without meaning and do not allow prediction nor action.
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First we develop the machines, then we contort the entire social and psychic order to serve their rhythms and facilitate their operation.
(Caveat that I don't claim to be a λProlog or expert.)
All examples showcase the typing discipline that is novel relative to Prolog, and towards day 10, use of the lambda binders, hereditary harrop formulas, and higher order niceness shows up.
Fun times are coming.
When me move from just making use of something to using something to make with, that is when we should have a deeper understanding I think.
Does that sound right?
> the important distinction here is that I wouldn't call myself an electrician if my relationship to the subject matter doesn't extend beyond the desire to flip a switch.
Yeah, that seems right to me!
> I do want to make things, and many times I dont want to know something, but I want to use it
This confesses the desire to make, to use, and to make use of, without ANY substantive understanding.
Of course this seems attractive for some reasons, but it is a wrong, degenerative way to be in the world. Thinking and being belong together. Knowing and using are two dimensions of the same activity.
The way of these tools is a making without understanding, a using without learning, a way of being that is thoughtless.
There's nothing preventing us from thoughtful, rigorous, enriching use of generative ML, except that the systems we live and work in don't want us to be thoughtful and enriched and rigorous. They want us pliant and reactive and automated and sloppy.
We don't have to bend to their wants tho.
It's true this a matter of taste, but also worth noting that the OCaml compiler devs have made it very clear they are open to well-motivated extensions of the stdlib, and it has been growing at a decent clip in the last few years.
> Large Language Models represent a fundamentally degenerative technology because they systemically devalue the very processes that underpin human progress: original thought, rigorous inquiry, and shared trust. On an individual level, they encourage cognitive offloading, substituting the difficult work of critical thinking and creative synthesis with effortless, probabilistic text generation. This fosters an atrophy of intellectual skills, making society more dependent on automated systems and less capable of genuinely emancipated thought. This intellectual dependency, in turn, threatens long-term technological advancement by trapping us in a recursive loop of recycling and rephrasing existing knowledge, rather than fostering the groundbreaking, first-principles discoveries that drive true progress. Ultimately, this technology is dangerous for society because it erodes the foundation of a shared reality by enabling the mass production of sophisticated misinformation, corroding social trust, and concentrating immense power over information into the hands of a few unaccountable entities.
What?
> I don't think OCaml is ready for production
seems to indicate your thinking is just not based on fact. This position is further belied by the stack of successful production applications you can see at https://ocaml.org/industrial-users/businesses.