Revanche1367

I wasn’t talking about altogether different fields, perhaps you meant branches of the same field in your last part?

While this is somewhat true, people also overstate how narrow a Phd student’s general understanding of the field really become as they specialize. For pretty much any serious field, specialization is inescapable without spending decades minimally studying the field via many branches, but a Phd isn’t just preparing you to have a specialized understanding of a specific branch within the field, because very often contributing something mostly new and worthy to that branch requires a mix of depth and breadth, the proportions of which depend on the exact field, branch and specialized topic. Most Phd curriculums I’ve seen still require students to take several advanced courses outside of their main topic area and take exams in multiple areas within the field. Somebody working in only one area would need to have at least graduate level understanding of multiple branches to get through these. I have also seen Phd students who are not broadly interested or comfortable in certain core branches of their field so there are all types and different requirements for different programs.

"Endangering" is an exaggeration based on what actually occurred it seems. What the car did was technically in violation of traffic regulations but it was careful to not hit anybody or cause significant damage to people's property as it did so. This is essentially no different than a careful driver ignoring (intentionally or otherwise) a sign restricting them from entering an area, but still driving through the area successfully without doing any harm. Technically, traffic rules were broken, by mistake (an algorithmic one most likely) in this case, but there were no lasting effects.

People make mistakes like that all the time, and sometimes they still get ticketed for that kind of thing, and other times they get a simple warning or don't get any form of rebuke at all. How many of us have never accidentally gone into a one-way traffic lane from the opposite side and managed to still drive through and get back on track without killing or maiming anybody? It's unlikely anybody would get charged with a crime for this, nor should they over a simple mistaken rule violation that did no harm.

Replying to correct my phrasing in the edit, meant to say “so that humans can reduce the need to think about things _like_ survival and comfort,” but ended up saying the exact opposite. The end kind of suggests the earlier part was a mistake though so hopefully it wasn’t misunderstood.

(I change my phrasing multiple times as I’m writing and sometimes leave earlier changes in without realizing and mistakes like these happen, quite a lot in fact. I blame it on ADHD and anxiety, both of which I was professionally diagnosed with at the age of 33.)

Yeah, wouldn’t they rather be doing real impactful engineering work, like figuring out means to display even more ads on personal user devices, maximizing the number of hours kids spend doom-scrolling per day, or making robots that are deliberately designed to take jobs away from as many workers as possible?

But, imagine instead being an engineer of any kind today and you’re only getting paid to work on boring things like advanced automotive technology and building cars that can maneuver themselves in midair and might possibly fly in the future? Ridiculous.

(This message should not be taken as support for Musk or any of his views or business ventures.)

Your last sentence reminded me of a quote by Alfred North Whitehead which I read many years ago in one of my CS textbooks: “Civilization advances by extending the number of important operations which we can perform without thinking about them.” I think about the essential idea of this statement quite often but didn’t remember the exact phrasing. As I went to look that up, I was thinking to myself something like “bet he would’ve changed his mind if he knew about LLMs!” but in finding the quote with its wider context, it appears he would’ve been thrilled:

“It is a profoundly erroneous truism, repeated by all copy-books and by eminent people when they are making speeches, that we should cultivate the habit of thinking of what we are doing. The precise opposite is the case. Civilization advances by extending the number of important operations which we can perform without thinking about them. Operations of thought are like cavalry charges in a battle — they are strictly limited in number, they require fresh horses, and must only be made at decisive moments.”

Apparently, part of his philosophical thought was that the ultimate goal of mathematics is to reduce (maybe even eliminate) how much thinking we do. Not exactly what I thought he was going for all these years lol. I wouldn’t read much more into it but it’s not hard to see how the statement could be perceived as this renowned early 20th century mathematician, logician and philosopher implying that he would’ve have loved the idea of machines reducing the need for research and development in engineering and mathematics (even if only to allow researchers time to focus on more important things).

Edit: As I’m not familiar with the breadth of his works and know of them primarily through secondary sources, I can also see how what he said meaning that the purpose of mathematics is automation in a very general sense, so that humans can reduce the need to think about things other than survival and comfort, and being a mathematician, he likely saw mathematics, philosophy and knowledge in general as one of those “leisure” activities we should be thinking about instead.

This is one of the biggest benefits. I'm not a plugin user so I don't remember how they're different from skills. Not speaking about the tool in OP specifically but regarding skills in general: you can have essentially the entire task or some of its subtasks (which you'd ordinarily direct to the agent using the skill, the main benefits of which are clearer natural language directions) handled with assistive tools written in any language your environment supports. You can additionally supply the skill with its own config files, data files, etc., building essentially a small repo within particular skills and making these resources however closely tied to the skill as you prefer.

This is particularly useful when the agent would otherwise be doing a task that is programmable, or the agent is inconsistent or unable to do it in an efficient, performant or other preferred manner. The programmatic tool assistance means at least some parts of the task (possibly its entirety) could be handled in a well-tested and deterministic manner. How reliable the determinism, optimality, etc. are depends on how well you or the agent writes and verifies the code, tests, spec, etc. in the first place of course, but that only needs to be done correctly once.

The other great benefit is reduced token use, potentially a massive reduction. Imagine a task Claude takes 10 minutes to prepare to do because it's reading and analyzing files for the 3rd time in the last 4 minutes, then it's asking for permissions several times in between to do this and that even after you put it in auto mode, then it's "thinking" again for the thousandth time about how to approach the task even though you had it repeat the task a hundred times already...by the time it actually starts doing the task, the most recent models are likely to have churned through tens of thousands of tokens (and that's a conservative estimate for frontier models) in the first 10 minutes. But, with tool assistance, you can have Claude directly handle some parts of that same task which, for example, needs unpredictable analysis or decision-making each time, but also have it use a set of highly optimized programs to handle the bottleneck parts or the parts you want done "your way." You could potentially cut down those 10 minutes of prep time + whatever minutes to actually do the task down to seconds, with barely a couple of thousand tokens used up! Just an example of course, but I've benefited from this strategy repeatedly across various tasks, simple ones and very complex ones.

Another great thing is that the tools don't have to be tied to the skill at all, they can live anywhere in your codebase. You could even manually run the scripts like any other to handle certain tasks in their entirety or do the prep work before setting an agent loose on the remainder. There are many different approaches with different advantages. It's like actually using the agent as your...well, agent! But now you're supplying him with the latest gadgets like M/Q does for 007.

No, it was this one: https://news.ycombinator.com/item?id=47112892. Last posted on HN 8 months ago, that's when I saw it. I misremembered the Windows version, it was 3.11. But, the site looks to be significantly different now and has different Windows versions, XP being the default emulation.

Tried it today on some relatively complex mid-sized real world tasks with several thousand lines of code generated by Argon. My impression is not good. Maybe it's due to first-day high user counts, but it seems to be doing worse than 3.8 flash in some coding tasks. What I noticed was that it often forgot significant parts of detailed, well-structured and precise instructions (which is somewhat rare with newer Claude and ChatGPT models) and not just for small details. It also seems to spend too much time thinking even when the task was a quick and simple one.

Without going into details, for a small part of a larger task, I asked it to classify different content types of different files and formulate a structured mapping (e.g., in JSON) between content types and another set of files (deliberately left vague here but not to Argon) from my codebase. I even offered it a multi-part draft of a classification system to start with and told it that if it can find other classification systems from international standards, academia or industry more suitable to the task than my rough draft, we can discuss replacing my suggestion. There were other parts to the instructions too, written out like an article with bulleted lists, precise program-like wording, etc. Then, I sent the prompt and left for a while.

When I came back, it was nearly done with the implementation but the classification system it came up with was a mess. It even admitted to making up "bogus" classification standards when I pointed out some errors. It also kept leaving gaps multiple times when I referenced errors to fix in subsequent instructions (and not once apologized the entire time lol). So my first impression was subpar, not really comparable IMO with Opus >=5 or Sol >=6, and seemed to leave larger gaps than 3.8 flash typically does. The most irritating part to me was not only the fact that it was making up things, but that it ignored my instructions to discuss things with me before deciding to shift away from my draft; I don't recall any major LLM ignoring an instruction like that in at least a year.

Almost burned up my laptop within seconds of visiting the site. I thought at first it was something like that quite interesting windows 95 on the web demo (which may have been AI-generated too afaik), alas it was just some pretentious AI-generated art piece with little technical value (IMO). Still would have been a nice art piece even with the performance issues if it was (mostly) handwritten, but token-churned art just doesn't have the same feel, especially when it also tries to destroy your computer.

The rate of output from LLMs is very high compared to most developers' capacity to review every line, especially when they are often working on multiple tasks from multiple projects all on the same day. The directive to increase code churning is coming from the top since upper management believes everything tech CEOs advertise to them, and there is increasing anxiety across tech, mathematics, finance, arts, etc. about getting replaced so people want to at least appear to be much more productive with AI. The new norm is fast becoming "There will be mistakes, but maybe not most of the time. We'll deal with it when we get there, and since we're all on the same boat, let's spread out the blame or try to ignore it since you never know when it might happen to you."

To be fair, this was always the case as there was never any guarantee of bug-free code in general, but the difference today is mainly in volume.

This is my feeling too, going to sleep early feels like I’m missing out on so much. My entire family other than my late father has been this way since forever, we almost never go to bed till 2-3 am.

Some people do in fact do it for improving understanding and benefiting people. You’re rather showing your own worldview. I’ve met mathematicians who hold the view that the work they do is for the good of the world. Waking up everyday for that purpose is now a change of goal posts, pure mathematics as a field is what we were discussing, not the motivation mathematicians have in their daily lives to continue working in their field; I doubt anybody today can say they have the same motivation every day to go to work other than survival.

Except that wasn’t all I said. This is not a court case, I don’t have to go into details on why I have that opinion. Comments are just comments, you don’t have to say more than what impressions you had of the article. There was also no implication of moral or intellectual superiority, you’re projecting your own dim view of why someone might criticize an article. Just because I found the author’s claim unconvincing doesn’t mean I think I’m better than him. It takes a lot of arrogance to assume that’s why I said what I said, which is to say, you’re projecting your own arrogance onto me. Everyone in the world doesn’t share your (lack of) morals.

You had no reason to think that, pulling things out of thin air about me, which is called slander. In my case, the author’s article was linked and I read it, and expressed what I thought of it. I’m not obligated to say why because others here have already stated various reasons. And in fact, I have basically indicated my reason by saying the evidence was insubstantial. The author made a claim: that CL is the best language and then didn’t offer up evidence that was up to par with the claim. Using words you don’t understand doesn’t make you look smart.

This visage of mathematicians among the general public is fairly new I think; it may have existed in some intellectual circles but was not common among regular people. It’s fairly common to read about the lives of mathematicians well into the 19th or even early twentieth century where as children or young adults who excelled at mathematics, their parents or guardians attempted to dissuade them from pursuing mathematics as a career because of the difficulty in obtaining lucrative jobs in mathematics unlike fields like law, engineering, etc. This was the case not only in impoverished countries but in western Europe as well.

Side note: it’s often the case that mathematicians and scientists are perceived only in terms of their research work instead of their personal lives or just other aspects of their lives. How many people on sites like HN or Reddit, would still perceive, for example, Euler the same way if they learned that along with being a genius in mathematics, he was also a religious fundamentalist who was known for annoying his colleagues with his incessant preaching? My point is not to suggest that this takes away from his mathematical work, but it is an indication that the perception people have about at least some of these figures is not based on their reality.

While I’ve generally been on the side of mathematicians on this debate and will likely continue to be, saying something like mathematicians didn’t ask for this is off-putting. Nobody owns knowledge, experts of a field cannot in any general sense be said to own that field, and in this case, they don’t even speak for all mathematicians. It’s thoroughly “unmathematical” to declare no mathematicians asked for this when they haven’t inquired exhaustively. A statement like that just gives ammo to the people suggesting that they’re just trying to gatekeep their own field (which IMO may be true at some level for some mathematicians but is not the only reason to be against AI replacing human intellectual pursuits).

The specific proof may be in pure math but Navier-Stokes problems did originate in applied math. A lot of what we consider pure math has it’s origins in something applied. As one of my math professors implied, a lot of mathematicians liked to pretend they came up with theorems from scratch in their final published form, but in practice it was often from seeing examples, often practical ones in applied math, then making conjectures that eventually led to more generalized theorems.

A lot of people here are smart enough, they just don’t agree with the premise but maybe don’t know how to express that. Being purely for the sake of improving human understanding is more akin to philosophy than chess I’d say, and that is beneficial on its own if truly sought for that purpose.

I was expressing my opinion, not every statement is an argument, nor am I compelled to like whatever you do or whatever the author of the article wants to say; maybe work on not making so many assumptions.

Lisp and functional languages have a determined following. I rather like both too, but if a claim like this was made about any popular language, there would be a lot more detractors in the comments. I was hoping this would be an interesting article with actually good points so I could use them as incentive to finally get started on making some with Common Lisp, but it was very poorly written.

A very big claim backed with poor arguments and easily disputed evidence.

When mathematicians speak of pure mathematics having “intrinsic value” or being for the sake of improving human understanding, what they really mean is that no applied value (in engineering or science usually) is necessarily known at present, but it improves our understanding of mathematics as a system in itself. Why mathematics is this way is not an easy answer, you would have to first have an agreed upon definition of what mathematics actually is, and we don’t have this. Most people have an intuitive notion and “know it when they see it,” but mathematicians and philosophers of mathematics don’t have a clear answer, and different schools like the (neo-)platonists, formalists, constructivists, etc. have different contradictory approaches in even trying to get to a clear definition.

Which gets closer to my real point, mathematics is inherently philosophical and I’d argue it is a kind of analytic philosophy. A close reading of late 19th/early 20th-century history of mathematics, I believe, shows us how closely mathematics developed alongside analytic philosophy, such that at the foundational level at least, they seem to be the same branch of knowledge. It wasn’t too long ago that in some parts of the world mathematics was (rightfully in my opinion) considered a branch of philosophy and there was no clear separation between a philosopher and a mathematician. So, in my mind, mathematics is the way it is, or is beneficial to humans because, or is worth pursuing ourselves instead of handing most of it to machines because of the same reason as philosophy is all of these things: human beings are naturally curious and we satisfy our curiosity by trying to learn and understand things, it’s a natural drive and it’s among the things which help us grow as individuals and as a collective.

Personally, I consider the above a very practical value, so I’d argue that pure mathematics does have “applied” value at a more basic level than what engineering or science disciplines are usually concerned with.

Almost certainly a tech/venture-capitalist bubble like the SF bay area. They really seem to live in a different world from even the rest of California much less the wider US or the world.

Besides the bias question (which is possible and apparently likely for both sides), I realize this is a touchy subject for many but the tone of this article is rather more irritated than it really needs to be. They even mention that the authors of the Harvard paper said the study wasn't meant to show causality, but the very next section heading is "Ridiculous things you can 'prove' caused cancer mortality," which suggests that is what the authors of the original paper were trying to do. If you're going to accuse them of being deceptive, at least be open about it instead of using this sort of passive-aggressive approach.

Also, they say:

"Over the last several months, we have replicated the results of these papers. The authors supplied us with eight lines of code and answered a couple of questions about the covariates, which did not replicate the results. Most of our replication was done through first principles combined with trial and error. Once we were reasonably close to the results of the first national study on cancer mortality, we took the methodology and applied it to numerous other landmarks."

I'm no expert in experiment design, but unless I missed something, I have qualms about calling this method a true "replication."

The closest thing I’ve come across to this is Z (“Zed”) notation. It’s from the late 70s, quite influential and pretty easy to read with a bit of logic symbolism. The same designer (Jean-Raymond Abrial) and colleagues also made the B method which can also do program refinement. Several other “well-known” (relative to other formal methods) formal specification systems were influenced by Z, including possibly TLA+ as I’ve read somewhere (but cannot confirm). Z and B both have free tooling available online.

Yeah, the naming and proliferation of different tools and sites is confusing. Quickest way I know to get on any plan is via Google One at: https://one.google.com/.

Are you not implying that SWEs are the same as probabilistic guessing machines by analogizing the LLM-user with a human developer’s manager?

I've been trying to get into formal specification & verification too, but with Z notation (which is specifically for specification) instead, together with a couple of different theorem-provers. It's for a pet project to help me learn, so not something I would be using for serious work (not right away at least), but I find the Z notation quite readable and there is quite a bit of support and free tooling for it available online. Being quite new to formal methods, I think TLA+ would be overkill for learning.

https://en.wikipedia.org/wiki/Z_notation

Great, so they _finally_ decided to add a non-flash model and it's not available to regular subscribers for an indefinite period. What's the point of paying for the AI Ultra plan? Anthropic doing the same with Fable as far as I know, OpenAI at least allows Pro plan subscribers to use Astra. I subscribe to Gemini AI Ultra and ChatGPT Pro, and have enterprise access to Claude at work. To be fair, Gemini's flash models since at least 3.6 have been quite useful for non-complex work, but for any task where there is a bit of complexity involved, I've had to check and recheck the work multiple times myself or sometimes with another LLM to get it to follow plans accurately. It's disappointing to see yet another Gemini release ignore adding newer pro models.

Edit: seems I was wrong about Anthropic restricting Fable, I guess our enterprise plan doesn't include it. But, the block from Anthropic regarding Mythos for regular subscribers/enterprise-users is still true I think.