hasley

Some questions that bother me:

Are people reviewing all the tests that have been created automatically?

What about existing tests? How do we make sure that AI does not fake them (by silent changes or by faking the test output)?

edit: corrected typo

When I was a child, my dad used to bring me to school by car. During the ride, I played "Star Trek" and we always had a technical issue like a phase variance in an induction coil. Usually it ended such that the warp core had to be ejected...

Sir Patrick Stewart inspired me since my childhood. Thank you captain!

I think there is a general problem:

When you let an LLM write a text for you (source code or some scientific stuff) and then you discuss about changes that you want, the LLM will put some comments in the text related to the conversation These comments will read weird when you do not know the conversation with the LLM. Like: You ask it to make a button read instead of blue and it will at "intentionally made button red here". - Or: The LLM will write that it did not use a certain approach for a derivation or notation just because you asked it to change such things.

You have to explicitly tell the LLM that bit shall only include what has been declared as finalized and that the text (especially prose) shall be self-contained.

Maybe it is hard for an LLM to distinguish the context of the conversation and the context of the text it shall write for you (I mean the abstract context, not the LLM context window).

> The answer was to add as many features to the language as possible.

This is an exaggeration.

For me, C+11/C++14 made the language much more approachable and readable.

It was only that from then on, the language was to be updated regularly.

This may not invalidate your point, but C++11 was a major step forward that, for me, made C++ feel much more convenient and modern than before. And C++14 is basically just adding/fixing stuff that should have been in C++11 in the first place.

I am not against some kind of "public review" and I really like arxiv.org. But I do not see it as a replacement for a peer review. It may start after a peer review when the paper is published, which IMHO should almost always be in an Open Access way.

For AI, the borders seem to have blurred a bit between academic scientists (e.g. at universities) and external scientists at companies or even private people). The problem with the latter is that it is much harder to enforce good scientific practice. Think only about the time it takes to write the state of the art of an ordinary conference paper.

I am also a bit drawn between giving everyone the chance to contribute to research and ensuring good scientific practice. Just writing down your latest ideas and successes is not the same as writing a scientific paper that shows the research in the context of past research and needs, for instance, to be much more mathematically rigorous.

I am sorry for that. Fortunately, this does not resemble my experience (electrical engineering/digital signal processing).

Usually I got quite critical comments (positive and/or negative). Yes, sometimes a reviewer does not write even a single sentence before giving an average score to complete the review process. But this has not been the regular case.

And as a reviewer for a conference paper of 4 to 6 pages, I usually assigned 1 to 3 hours to read it (journal papers: 1 to 2 days) and to give comments.

Yep, I was delighted that an MMSE estimator came up so early!

Here, you may give seminars. These are often about solving some tasks (e.g., "compute the Fourier transform of a triangle"). Sometimes it is just consultation where students can ask stuff about the lecture. You may als be asked to conduct lab experiments with students. Sometimes your only teaching consists of supervising student research projects, Bachelor's theses or Master's theses.

The lectures are usually given by the professor (head of the research group). Sometimes a PhD gives a lecture when the professor is away. But yes, it depends on your employment contract. If your contract involves a lot of teaching you might even give a whole lecture - though this is rarely the case for employees without PhD.

This is a very simplistic view of a PhD and basically a prejudice.

During conducting a PhD, you learn a lot about organizing yourself, about how to work together with others in a professional context, about teaching and guiding others, about presenting you and your results orally and in a written way, about using certain tools (whatever applies in your field) and so on.

Some people like to view it the way that a PhD makes you a expert in one field and rendering yourself useless for any other task. But this is in general far from reality. As a PhD (at least where I live in Germany and in the field of engineering) you are indeed expected to have a broad view such that you are able to know where you are located with your PhD topic and such that you are indeed not a narrow expert.

The idea is really nice. And I think projects like this could help elderly or mentally less gifted people.

Unfortunately, things break inside the programs. Usually the folder structure is still exposed as-is and the programs (except things like calculators or synthesizers) do not look like things from the physical world.

I have to do with some elderly people who do not have a mental model about file systems, program menus, tabs, and other things. They learn by heart where to click. And then they forget it when they do not use it on a regular basis. But they cannot regain this knowledge on their own since the UI has no inherent logic for them.

Your country started the war murdering thousands of Ukrainians. So, what do you expect?

One goal is probably to show average Russians that the war is not just something which happens somewhere else in the world - a side-note on the news, no need to bother about.

The question why people who do not agree with the government should also pay the price for a war started by their government/country is not specific to this war.