That's a bit too simplistic -- if there is a small group that really pushes things forward in a big way, then maybe not, but if this result builds upon decades of prior work, then Cook and Levin might be equally or even slightly more famous than the solver group after the dust settles.
But it is a moot point anyway. Cook and Levin are very well known already in TCS, and credit is not directly enumerable like money, so "more than a lot of credit" doesn't make too much sense.
For this problem in particular, asking the right kind of question was really important for the field and led to a lot of discoveries even before it will be answered.
> If the answer is "no one really", entropy will overwhelm your codebase sooner or later. Otherwise, you need to read the code
I think about this on the regular -- I know the answer is currently "you own the code, so you have to understand it", but to unlock the true productivity multiplier, in the future, the answer has to be "no one really".
I think about it using the concepts from my job (academia) -- to actually have PhD student-level intelligence means that you have to trust that it does a good enough job that you can focus on other stuff. Professors often bring the correct ideas or intuitions, but they have to trust the PhD student to write the code and/or fill in the gaps in the proofs -- they can advise them on the high-level issues during a consultation, but that's about it.
I am pretty bad at working in the current LLM workflow -- it is tough for me to focus on reading a TCS paper for review, keeping all the details and invariants in my head, but every 5-10 minutes go to my PC, completely switch contexts/projects, read the code and think about the LLM's comments, suggest the next step, and then go back to reading.
As a TCS assistant professor from Eastern Europe, I always am a little jealous of the biggest names in math having such an easy access to the expensive, long thinking models.
Paying for Pro from any of my current academic budgets is completely ouf of the field of reality here -- all budgets tend to have restricted uses and software payments fit into very few categories. Effectively, I'd have to ask for a brand new grant and hope the grant rules allow for large software payments and I won't encounter an anti-AI reviewer; such a thing would take one year at least.
As a nail to the coffin, I was "denied" all Claude Opus recently as part of Microsoft's clampdown on individual (and academic) use of Copilot.
(Chagpt 5.5 Plus does not seem sufficient for any deeper investigations into new research topics, I've tried.)
While this sounds generous (and in some ways it is), it does not address the general point that GP is making. That is, the systematic disadvantage which large parts of humanity have w.r.t. to access to the tools. You could say they can't drive a Lambhorgini either, but that also doesn't solve the problem.
An aside: It was a very nice gesture and completely unexpected by me, so even if it doesn't work out, it made my day. I personally believe that kind gestures have a lot of power.
Back on topic: There is a real danger of the gap between rich and poor universities significantly widening in all fields if the rich can afford Pro level models, or even hardware that can run their own comparable models, and this being fiscally inaccessible to the rest.
One can sweep this under the rug by blaming the educational funding but this just shoots down all discussion. Even if GDP of a country goes up by a lot -- such as Poland -- it takes time before any budget benefit trickles to the education budget, and with some governments it might never do.
I believe Microsoft et al do have the most power here to boost affordable access to AI for researchers on a large scale; the fact that they cut some too expensive models (Opus, 5.5) from their academic benefits package is a grim omen. I do realize they would like universities to pay them also, and ultimately the universities should do that -- but then we are back at the institutional level of the problem.
Its a problem of the individual institutions and countries. The budget required for AI tools currently is negligible compared to other university expenses. We don't need to call everything a systemic disadvantage when the disadvantaged (at the institution level) have agency here.
Can you tell me what is the budget necessary to supply AI tools capable of substantial research assistance to all academic staff at a university?
You seem to have a good estimate in your head; I definitely do not.
From personal experience, ChatGPT 5.5 (the Plus tier) is excellent for programming tasks and also for various teaching related tasks but I have not observed the research benefits that Tim Gowers has when I asked it questions in my area of expertise. So the costs are definitely higher than a few dozen $ a month per PhD/professor.
You might be right that universities should immediately spring into action and demand funding for research level AI resources and hardware. One thing you might be mistaken in is that public universities are unfortunately very inflexible institutions; one reason for this is that they have a large internal leadership structure AND they are funded by the state, so even if the entire university agrees on something, the funding is at the whim of the ministry of education and thus the current political leadership.
> Can you tell me what is the budget necessary to supply AI tools capable of substantial research assistance to all academic staff at a university?
I think the GP meant that *if the tools provide substantial benefit* to staff, their costs can be compared to salaries and other large expenses of the university. The $100/month subscription costs less than your office space.
Which is good, since public money is tax money, so it better be spent wisely and not just thrown at the latest hype without thinking properly about it. It's a feature that public spending moves slowly, we should all be thankful for it.
> The budget required for AI tools currently is negligible compared to other university expenses.
Is it? Do you have any idea what the salary of a mid-tier university researcher in an Eastern European country is? Or in Africa or south-east Asia? With sota LLM pricing you easily get into the same order of magnitude, so essentially labour cost would double for researchers at such universies. Not "negligible" at all.
I feel like this is one of the most advantaged times in history in terms of regular citizens having access to cutting edge tools.
Looking online it seems like the low end estimate might be $30k a year for such math researchers? And ChatGPT pro or whatever you want will run $100 a month, and should be coverable by grants. I’m quite sure matlab alone cost more in the past
> While this sounds generous (and in some ways it is), it does not address the general point that GP is making. That is, the systematic disadvantage which large parts of humanity have w.r.t. to access to the tools. You could say they can't drive a Lambhorgini either, but that also doesn't solve the problem.
This was also the case historically, when being at certain universities, with better professors, better scope of works available at the library, etc, would necessarily provide systematic advantage.
This is the reality of progress. It is always unevely distrubuted.
I do think the open source side of model development is a substantial counter to the pessimism here.
I mean, I don't think OpenAI should be wading into the policies and practices of foreign institutions and governments. Look at all the blowback we see from the collision of Anthropic or OpenAI and the US government.
At present, the tools are available for whomever wants to buy them. Not OpenAI's fault that parent comment's government and/or institutions policies haven't been updated to allow for their purchase and use.
I'd argue that the OpenAI dude/dudettes level of generosity is appropriate given the circumstances.
You know what, I'm ashamed that I didn't think of this. I'll sponsor three months. Email in my hn profile. I don't understand the math in the article, but I'd love to help you make progress in it.
I will leave the contact up for a bit longer if people want to get in touch and share their experience with the research gap of the models -- or anything, really -- but I do not think there is any need of further support. Like I said elsewhere, the offer of support made my day and the gesture is enough.
At my university, everyone had to pay their AI subscriptions out of their own pocket, until a communal AI service was introduced recently. It took 2 years to set up and only serves gpt-oss-120b, so everyone is still using other services. But at least some admin can scatter the word "AI" all over the university's website now and has an excuse to reject any requests for AI subscriptions because "we already have AI".
It’s a classic example of the best positioned people being in the best position to keep reaping all the rewards.
There’s the example of a poor person and a rich person buying boots. The poor person’s boots wear out and have to be replaced while the rich persons boots last for many years due to higher quality craftsmanship. Over years, the poor person’s boots wear will pay may for boots.
I know the example, but as a counter-argument: often more expensive boots are not more durable. It’s about spending time to learn to spot the quality.
Of course if you are really poor, then you have to take expensive shortcuts, but for most people that shouldn’t be the case. Learning to do more with less money isn’t as bad as many people think. It’s also good for the brain to be a bit more creative.
> Learning to do more with less money isn’t as bad as many people think.
We are wading into philosophy here, but I believe this analogy doesn't track in this case -- my suspicion from this blog post and others is that already today, the Pro level thinking models are a positive multiplier to your research output similar to how the models one level lower are a multiplier to one's programming output.
Maybe one can someday use the cheaper models similar to how you can use cheaper models than Opus/5.5 and still be nearly as productive as a programmer -- but I am trying and failing doing exactly that for research questions.
here I think it's less about "poverty" (non-US acedemic budgets are still high, though not in the same sphere), but it's about having red tape when it comes to software. My experience doing a PhD in Japan was: Everything you can touch was basically a free for all - including $500 keyboards and $10k Mac Pros, especially if you are a valued researcher. But software, oh man, how can we prove receipt of goods to accounting...
OpenRouter lets you pay by the token only (no subscription), has all the frontier models (including Opus 4.7, GPT-5.5) and most of the others, and if you use it sparingly it usually turns out to be quite cheap.
API pricing for Claude is about an order of magnitude more expensive than subscriptions (numbers: https://she-llac.com/claude-limits). But it may be worth it with DeepSeek V4 Pro, which is currently on discount.
Depends very much on usage! If you connect it to tools like Cursor, etc. then yes a subscription is probably cheaper -- although, you'd have to subscribe to each provider if you want to use them all.
But if you ask questions occasionally, (and don't resend, for example, your whole codebase with each request), then the API feels really cheap, even for the frontier models.
My problem with pay-by-the-token is that it discourages me using the thing ("oh the prompt will cost me $0.1"), so I pay a subscription which I'm pretty sure costs me about two-three times what I'd pay just for the api costs, but encourages me to use it more ("oh I have a subscription already, better make use of it").
I believe ChatGPT 5.5 Pro access is available for $100/month, is that an unrealistic level of expense for someone in your position and geography? Even if the university won't pay for it, it seems you'd like to use this tool for your own goals.
I'm not trying to shame here, just curious whether this is completely unattainable for most researchers in your area.
I fully understand your rant! I pay ~20€/month for the Pro account, as my university has a deal with Microsoft and only seems to recognize Copilot, so it’s very hard to use one own’s funding for paying something else.
Average European salary is around $4000/month, in eastern Europe is half of that. Median is probably lower than that. Makes me want to quit visiting places like reddit where everybody claims to be making 100k+/year
All salary discussions need a cost of living context. Yes in Europe you earn a bit less but the public services are much better than in the US and one emergency (r.g. healthcare) won't ruin you as it's mostly a public system.
I'll take a Euro salary and qualify life over a FIRE-typs salary and daily fear of falling into the abyss any day.
Given the topic and the fact llm providers charge global rates, the absolute take-home money is much more relevant. Even if you live like a king on $1000/mo, 5.5 pro is still $200.
Their loss if they don't move to regional pricing. AI will continue to remain an upper-management luxury then, and won't reach the mass adoption required to justify their outsized valuations.
Regional pricing makes sense for products that don’t have ongoing costs or where most of the input cost can be offset by local labor. You’re not buying server racks nor electricity at 1/3 of the price to serve poorer markets
That’s what most people spend on their phone and Internet connections per month in the US. That’s what the average American family spends on just five days of food.
People spend much more than that on just commuting to work if you can spend $200 a month to supercharge what you do at work and 1000x your productivity it’s a no-brainer.
From what money? Just pause the health insurance for a while? Stop paying the rent? No diapers for the kid?
Your entire story only makes sense if you have many hundreds of dollars/euros of entirely disposable income every month left, after all unavoidable expenses have been paid for. I understand that this holds for you and everyone you know but I’d like you to appreciate that for very many people it doesn’t.
37% of Americans would be unable to cover a 400 usd unexpected expense* without using one or more credit cards. 13% would flat out be unable to cover it. [1]
Are you honestly saying most families would be able to justify 200 usd a month for ChatGPT?
There is a significant gap between what academics are paid across European countries, and since most top universities here are public institutions, you are right -- Eastern European government employees tend to be on the poorer side.
There are several other philosophical arguments against what you propose but I do not wish to go down that route.
Bruh, $200/m for most people in the US is also a hard "no!". That's a lot of money. Plus Anthropic isn't doing good deals with orgs that spend less than 250k a month. It's ridiculous.
> Is the lock structuring here really deadlock safe? The model will tell you with complete confidence its code is perfect
Fully agree, in fact, this has literally happened to me a week ago -- ChatGPT was confidently incorrect about its simple lock structure for my multithreaded C++ program, and wrote paragraphs upon paragraphs about how it works, until I pressed it twice about a (real) possibility of some operations deadlocking, and then it folded.
> Every time a major announcement comes out saying so-and-so model is now a triple Ph.D programming triathlon winner, I try using it. Every time it’s the same - super fast code generation, until suddenly staggering hallucinations.
As an university assistant professor trying to keep up with AI while doing research/teaching as before, this also happens to me and I am dismayed by that. I am certain there are models out there that can solve IMO and generate research-grade papers, but the ones I can get easy access to as a customer routinely mess up stuff, including:
* Adding extra simplifications to a given combinatorial optimization problem, so that its dynamic programming approach works.
* Claiming some inequality is true but upon reflection it derived A >= B from A <= C and C <= B.
(This is all ChatGPT 5, thinking mode.)
You could fairly counterclaim that I need to get more funding (tough) or invest much more of my time and energy to get access to models closer to what Terrence Tao and other top people trying to apply AI in CS theory are currently using. But at least the models cheap enough for me to get access as a private person are not on par with what the same companies claim to achieve.
Hello, TCS assistant professor here: he is legitimately respected among his peers.
Of course, because I am a selfish person, I'd say I appreciate most his work on convex body chasing (see "Competitively chasing convex bodies" on the Wikipedia link), because it follows up on some of my work.
Objectively, you should check his conference submission record, it will be a huge number of A*/A CORE rank conferences, which means the best possible in TCS. Or the prizes section on Wikipedia.
I don't deny that his output is highly valued among AI researchers.
Provocative as my question may be, the point I wanted to make is that his most highly cited paper that I already mentioned is suspiciously very in line with the OpenAI narrative. I doubt if any of his GPT research is really independent. With great salary comes great responsibility.
> Realistically there's no reason government can't use open source software and open formats especially.
> Last time I had to fill out a government form in Canada (...)
Without any evidence, let me argue why maybe it shouldn't. In the past, a common opinion that I have heard is that open source is more secure because all the code is out in the open.
The recent xzutils backdoor attempt [1] kind of led me to believe it's not really true, it's only true if many good-actor eyeballs, which are willing to donate their time for public benefit, are on the code.
Almost all of the government's code that I interact with are web apps that are potential targets of foreign adversaries -- tax filing web apps, prescription + vaccination scheduling web apps, family benefit applications, and more. (This is not in Czechia, but close.)
Now, would I want to read that web app code? Not at all, I couldn't care less about it. However, foreign adversaries would love to immediately start analyzing it. Extracting the entire country's health data or tax data would be a goldmine.
And even though there probably are several people actively paid to maintain security of these systems, I feel that the foreign adversarial agents would be much more motivated (and better paid) than government employees/software developers.
You could make a opt-out for national-security purposes for the code, but I feel almost all the code a government works on would have such an impact when compromised.
(Disclaimer: I am a huge supporter of open source in general, contributed to the Linux ecosystem in the past and in my current job as an academic, almost everything I do is available out in the open in some way or another.)
Microsoft has literally been hacked multiple times by Russia in the last few years. Our government lost hundreds of thousands of CRA (tax agency) credentials to hackers and had to lock millions of accounts. Other agencies have also been breached.
Meanwhile the XZ backdoor was found in Sid, Arch and pre-releases of Fedora and openSuse. It never actually made it into any numbered release of Fedora, openSuse, Ubuntu, Debian, Red Hat or Suse distro. It's actually a pretty big win and the system worked as intended.
Open source and Linux are doing just fine security-wise.
Also, none of this has anything to do with using offline tools like a word processor to make documents.
>Meanwhile the XZ backdoor was found in Sid, Arch and pre-releases of Fedora and openSuse. It never actually made it into any numbered release of Fedora, openSuse, Ubuntu, Debian, Red Hat or Suse distro. It's actually a pretty big win and the system worked as intended.
I would maybe not go quite that far. That it got caught was mostly a confluence of lucky breaks and accidents. The second version of the exploit would likely have not been detected if not for the fact that the first version of the exploit had a couple of programming mistakes that attracted some attention to itself.
The entire thesis behind the open source security model is to have lots of eyes on the code/program, since more eyes = more likelihood of catching it. Even if you say it's accidental, let's say the odds of catching it are 0.00001. Repeat that enough times and you get 1.
It was caught before any distro released with it. The system worked.
If one of the Debian or Fedora developers had immediately caught on to what they were looking at when their attention was drawn to it by the failures, I would say the system worked. It's certainly true that open source saved the day here, but that's maybe different from saying "the system" worked. It easily could have gone unnoticed, or been noticed a few weeks later.
The xz backdoor was caught before anyone used it. This is typical of open source backdoors, but atypical of proprietary ones. History is full of proprietary software with backdoors which were discovered after years or decades of being actively used. Lotus notes, RSA corporation, Cisco routers, Juniper switches, Huawei everything.
We have more or less immutable history of every change leading to every release of open source software. Any backdoors you previously created under an identity could burn that identity forever. That history is not available for proprietary software. If someone adds a backdoor in proprietary software for two years and then removes it in later versions, it's totally likely it'll never be noticed.
Thinking that open source software is at greater risk of being backdoored is akin to thinking most trees in the world grow along the road, just because you drive everywhere and have never been inside a forest.
Every country already has a special government agency that deals with keeping stuff protected. In fact you tend to think the people who know most about this are in government, don't you?
And it's not like there haven't been vulnerabilities found in proprietary software, despite them paying people to keep things safe.
Crowdstrike is a recent example that comes to mind. I don't see how paying for CrowdStrike made it more secure or reliable.
I would also argue that you could take all the $$ paying for proprietary software and contribute it to people who are making the open source software, making the reliance on "free" eyeballs less of an issue.
> I've worked in academia - and yes, that has been in multiple countries in the EU - I've never had to utter a single word in something other than English in the workplace.
I have the same trajectory as you -- multiple countries in the EU, working in academia -- but different experiences for sure. Or at least a mixed bag.
Let me list them in order of how much English sufficed:
1. The Netherlands -- common knowledge is that their English is top notch and anecdotally it was the case as well, I also got by purely with English.
2. Germany -- their English is also good but I needed German in edge cases. One edge case was finding an apartment (not speaking German simply pushed you down the list of candidates, even with a full time job in academia). Another one were university rules and announcements; not every email was in English, but arguably easy to get by with modern translation tools.
3. Czechia & Poland -- English is good among the professors but the percentage of locals at the university level is so high that most internal meetings, announcements, local seminars take place in the local language. In my experience, non-faculty university staff (department secretaries, payroll, entrance security) usually strongly dislike speaking English or outright do not speak it at all.
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I've omitted some more cases where local languages are required. If you live in a country, you will eventually interact with the healthcare sector, where the language experience will likely mimic the experience at the workplace (for the countries above, it would be in the same order for the healthcare sector).
Another case is government bureaucracy. For most of the EU countries I've been to, the official language of the country is their local language and only their local language. This means that government employees are not required to speak any other language other than the official one to you, plus you might be required to fill in forms and communicate in the official language if you want to talk to them.
In my experience, the helpful/good ones may try to communicate with you in English but if you need something from them or if the bureaucrat had a bad day, you better start talking in the official language.
> Another case is government bureaucracy. For most of the EU countries I've been to, the official language of the country is their local language and only their local language. This means that government employees are not required to speak any other language other than the official one to you, plus you might be required to fill in forms and communicate in the official language if you want to talk to them.
This is true, and something I have indeed experienced. However, this is likely true for _any_ country where English is not the official language, not just those in the EU. Besides, understanding bureaucratic lingo is not just a matter of pure linguistics. Governmental concepts rarely translate 1:1 to another nation, even those with the same official language. If you migrate to another country, part and parcel of the experience is that you _must_ contend with bureaucratic principles, rules and institutes with which you are not familiar. There is no escaping that.
That said, at least here in the Netherlands, there is certainly a movement to provide more and more governmental information in English as well. I'm not going to dox myself, but for example my muni's English website looks nigh-identical to the Dutch one.
The problem is social life and informal discussions. I France or Germany you cannot have a normal life without a fairly good knowledge of the language.
It reminds me of the fact that the "Fake Mr Beast giveaway" ads that even raised some attention here on Hacker News [1] a while ago are still around. In fact, I have seen one yesterday. Those must have been flagged as impersonation and scam thousands of times by many people, including me personally, and Youtube finds them perfectly fine.
After that episode, where I tried myself to get rid of them, I am much more convinced that Youtube is fine with all but the worst scammers, and don't buy any of the "they're just low on manpower" arguments anymore.
Last year for weeks I was seeing these fake Mario games on YouTube ads. And it wasn’t a Mario feel-like. They called it “Super Mario” and had whole asset rips in the graphics.
Nintendo lawyers were surely all over that. I’m shocked it took so long to get them removed.
> Hi! I'm a PhD student studying computer science at Rice University.
This means that we are on the same career path (I am currently an assistant professor in theoretical CS in Europe). I wish you of course best of luck!
Here is the harshest truth about teaching I learned during my PhD:
If you are focusing on teaching too much, you are setting yourself up for failure.
This sounds cruel, and in fact I am much like you, I love teaching and I love self-improvement and it is quite easy for me to invest time into my teaching prep, presentation, and more and see measurable results in class quality and usually also student feedback.
However, at least in my neck of the woods (i.e. Europe), almost all gates and gatekeepers for you as a PhD student, and later postdoc, are checking your research. At some places they really do expect you to have K publications in the top 3 CS conferences or you will not be considered at all -- and it seems these thresholds are only getting higher. Here I mean for example invitation-only workshops, postdoc positions with top advisors, and later also permanent positions.
On the other hand, if you are a talented scientist, they usually only care that your teaching skills are at the bare minimum -- have you taught something? Yes? Great.
Now orator/presentation skills are critical and presenting a coherent lecture plan might be useful for a final presentation at an interview for a permanent position. But even there, it is more about you knowing what you want to teach and how it complements the department than about your past achievements (i.e., how much you have put in a course previously).
My PhD advisor usually said that he likes to dig into teaching when research is not going well. I agree with that -- teaching really is fulfilling to me and I love to improve my class and see people happy with it, and research is all about global ranking (which is tough on anyone's psyche) and generating progress which is the fun part but sometimes takes a long time. However, at your stage of your career, the research really can't go slow.
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PS: If the author reads this, since it is a self-post, your class sounds really nice and it is actually one I would have loved to attend. My research is in online algorithms -- a field which you can rephrase as seeing some theoretical problems as two player games between a solver and an adversary -- and among other things I would like to consider utilizing all the techniques of chess solvers (which cannot evaluate the game fully, but "almost") and transfer it to other areas of online algorithms.
Just as a counterpoint: this very much depends. I probably spent at least a year (probably more) of my PhD (in Europe) just teaching a class I built up from the ground up myself. I barely got any research done the first year I gave that class, and every subsequent year it still took a large chunk of my time. It's part of the reason I spent a total of 7 years doing a PhD (which is long, considering I already had an MSc), during 5 of which I taught my class, and grew it from 10 students in the first year to 200 in my last. But I don't consider that time wasted. I had a blast and found that teaching helped me understand the fundamentals of my fields at an extremely deep level that I'd never reached otherwise. It didn't improve my research output, but I feel that the soft skills and understanding of fundamentals was a real advantage. My future career also didn't suffer, I'm now working as researcher at a FAANG AI lab.
> I had a blast and found that teaching helped me understand the fundamentals of my fields at an extremely deep level that I'd never reached otherwise
You spent 5 years teaching a class that, judging from your words, you probably prepared and improved very thoroughly. That is a lot of hours of work. Are you sure if you devoted all those hours to reading textbooks, papers, doing experiments, etc. on your field, you wouldn't have achieved an even deeper understanding?
Maybe yes, but if so, I honestly think you're in a minority. As an academic myself, I like teaching and I do learn things from it, but it's far from the most efficient way to learn a scientific field. If I had a pure research position I'm pretty sure that my research productivity would be better.
> If you are focusing on teaching too much, you are setting yourself up for failure.
This is good advice. And this is true even once you become a professor. All time spent on teaching will go against your career progression. Even if you're tenured and don't care about promotion, you'll feel like an imposter in your department if you're not somewhat competitive research wise.
Generally speaking, there's no recognition in teaching in general, and at university level it's often not even considered as a job by itself.
Maybe it's different in Asia, but that was my experience in the western countries where I worked.
> However, at least in my neck of the woods (i.e. Europe), almost all gates and gatekeepers for you as a PhD student, and later postdoc, are checking your research.
While I'm also in Europe, my bet is that this is universal and won't change in the foreseeable future.
The reason is that teaching is practically impossible to evaluate. How do you quantitatively measure which professors provide high-quality teaching? By grades? No, easiest course wins. By employability? No, it depends a lot on the field, a philosophy professor can be amazing but that won't create jobs in philosophy. Student polls? Correlation with actual quality is really weak, and I say this as someone who has good polls - there is a strong influence of difficulty as well as the subject itself (a CS student will almost always prefer programming to physics, and it's not the physics professor's fault), apart from gender bias.
In my country they try to give an equal weight to teaching equally with respect to research in applications for positiosn and tenure, but since there is no realistic metric, the bulk of the score ends up being about "years teaching" or "number of hours taught" which is the only objective number that they can come up with. So it becomes basically a seniority factor and since your seniority is what it is and preparing high-quality lectures won't give you more hours or years, the outcome is still that focusing too much on teaching is bad for your career.
There are different types of universities. While R1 institutions are more focused on research than teaching, there are smaller liberal arts universities which revolve around the undergraduate student experience. These universities still have research expectations as part of tenure and promotion, but faculty aren’t required to crank out research publications. Teaching is hugely important at these schools, both during the hiring process and when evaluating candidates for tenure and promotion.
I have been fortunate enough to work at such a university for the past 20 years. We have a deep endowment, small class sizes, and extensive support for our faculty research projects. Undergraduates at our school are often engaged in research projects as well.
For me, this is like an academic utopia: a blend of teaching and research with a primary focus on teaching. There are many other universities like mine.
Yes, I'm fully aware of the fact that teaching isn't really a priority in academia - for that reason, I probably won't be reviving my class in the near future. I really do like teaching, but it doesn't get me much closer to any of my current goals.
> Isn't the problem de facto solved by matchmaking? The player that aims better will quickly win more and be elevated to the level of opponents on par with them.
Matchmaking decreases the odds you meet a cheater for low rank players, and significantly increases it for higher rank players -- and since there's fewer of them due to the Bell curve, they are going to feel the cheaters that much more.
If you just rely on rank and not on anti-cheat efforts, you'd be just destroying one of the loyal cores of the playerbase, one which is also quite vocal online.
From my personal experience of thousands of hours in competitive FPS shooters on PC, there is no point in ranking where playing against a cheater becomes fair or fun.
modern matchmaking includes streamers that pay for accounts that have purposefully lost repeatedly so they've tanked their rank so they can stream themselves pubstomping noobs.
Back in the day an obvious cheater would get booted from the server, nowadays, they literally record themselves doing it and nothing happens because it brings in an incoming to the company.
But it is a moot point anyway. Cook and Levin are very well known already in TCS, and credit is not directly enumerable like money, so "more than a lot of credit" doesn't make too much sense.
For this problem in particular, asking the right kind of question was really important for the field and led to a lot of discoveries even before it will be answered.
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