vertere
Joined 9 years ago
Joined 9 years ago
Someone compared treatment of X 20 years ago to treatment of Y today -- seems pretty natural to bring up treatment of X more recently. You can't just say "the original comment didn't mention it so you can't mention it either".
I don't see how your accusations of bad faith are warranted.
If someone came up to you on the street and said "You are an elephant. Are you an elephant?" you wouldn't say "yes".
Also security is not one dimensional. A system's required level of confidentiality might be very different from its required level of availability. Being explicit about this might be better than trying to lump different requirements into a "production" label.
Strongly agree. I briefly developed a morbid fascination a few years ago, which then developed into a rather unpleasant sort of phobia/aversion.
Yes, but people have been attracted to Python largely because it's not like a lot of other languages. It is/was concise, simple, dynamic and fairly easy to learn. I think some of the new features, even if they don't make it a worse language, make it less "Pythonic", and so tend to undermine its comparative advantage. For experienced programmers the new features might not seem complicated, but python is used by a lot of people who are not in that category, including people for whom software development isn't their primary job.
Also much of math notation is effectively 2d. Programming langs use linear text. Latex syntax is sometimes used for a linear-text representation (even if it's not intended to be rendered), but it reduces readability.
And people still write equations by hand a lot, because the notation is more efficient than typing it out.
> ... SFT is a subset of RL.
> The first thing to note about traditional SFT is that the responses in the examples are typically human written. ... But it is also possible to build the dataset using responses from the model we’re about to train. ... This is called Rejection Sampling.
I can see why someone might say there's overlap between RL and SFT (or semi-supervised FT), but how is "traditional" SFT considered RL? What is not RL then? Are they saying all supervised learning is a subset of RL, or only if it's fine tuning?