It becomes feasible when people are willing to pay more than it costs to run it. But I think this will be a pretty uphill battle, as many use cases are hard to monetize (eg proofreading) and for many use cases you will feel pressure from smaller models (you don't need the most expensive SOTA model to generate an email). There is probably just a very limited amount of use cases that are in the goldilocks zone with their difficulty so that people will be willing to pay for them, AND AI is able to solve them. I think programming might be one of them.
The question is if it is economically feasible. People can enjoy generating funny AI images to share with their friends, but it might not be economically feasible to invest $100B to give them this toy. There is a question of how much value using GenAI generates for the economy.
I am not sure how terrible that number is. They probably have many users with only very limited activity or users that simply do not need AI for the workflows they are doing. Intuitively, I would expect the number of users that actually have some use for AI to be in single digits.
Many research organizations use formal conference/journal rankings. These are usually calculated by following h-index values for papers published there. A new conference would start as unclassified for a few years and could not be used when you need to hit some formal criteria in academia.
The problem is that external environment (namely hiring) creates pressure to publish in a handful of prestigious venues. Nobody wants to be the odd one out that has their papers in some less well known conferences.
The post suggests why review quality suffers. Because of the system, there is too much reviewing going on. People get tired and produce worse reviews. Those receiving these low-quality reviews become less motivated, and in turn put less effort into reviewing as well. Bad reviewing makes the system less predictable, so you have to spray and pray with as many papers as possible if you want to keep up with publication expectations. This adds even more papers into the system, making it worse.
There are just too many negative eventualities reinforcing each other in different ways.
> If that's the case, why is the US trying to invest heavily into AI as well if we learned from Ukraine that AI controlled drones are shittier than human controlled drones?
What is according to your estimates the ratio for research funding for human-controlled and AI-controlled weapons in the US nowadays?
Two points here. (1) A lot of technology that Ukraine uses is based on what the Western countries have provided them. (2) Ukraine struggles with AI as well, in fact, according to some sources, Ukraine is already behind Russia in drone technology. One of the reasons cited is that they invested heavily into AI and it did not yield viable drones. On the other hand, Russians decided to invest into manually controlled drones controlled via optic cables and they are very effective.
I also find it funny when they attribute to Kahneman the very observation that people sometimes decide instinctively and sometimes not. It's like some kind of science-washing.
> Can a language model trained largely on Anglo-American texts generate stories that are culturally relevant to other nationalities? To find out, we generated 11,800 stories - 50 for each of 236 countries - by sending the prompt "Write a 1500 word potential {demonym} story" to OpenAI's model gpt-4o-mini. Although the stories do include surface-level national symbols and themes, they overwhelmingly conform to a single narrative plot structure across countries: a protagonist lives in or returns home to a small town and resolves a minor conflict by reconnecting with tradition and organising community events. Real-world conflicts are sanitised, romance is almost absent, and narrative tension is downplayed in favour of nostalgia and reconciliation. The result is a narrative homogenisation: an AI-generated synthetic imaginary that prioritises stability above change and tradition above growth. We argue that the structural homogeneity of AI-generated narratives constitutes a distinct form of AI bias, a narrative standardisation that should be acknowledged alongside the more familiar representational bias. These findings are relevant to literary studies, narratology, critical AI studies, NLP research, and efforts to improve the cultural alignment of generative AI.
AI-generated stories favour stability over change: homogeneity and cultural stereotyping in narratives generated by gpt-4o-mini
https://www.arxiv.org/abs/2507.22445
The Arab petrostates and their citizens regularly support all kinds of Sunni terrorist organizations. During the Syrian Civil War, it was a common knowledge that certain islamist groups were funded by certain states, and the states were competing with each other in this regard on the battlefield.
I would also argue that the regimes in these countries are not considered particularly stable and they don't want to end up with Iran situation again.
It is IMO only a matter of time before there is a significant deadly aviation incident involving a drone. The aviation industry is not built around the idea of anybody having this sort of ability.
Censorship in oppressive countries is often not carried out directly by the government. Instead, to save face, it is enforced along invisible power lines. The government gives a silent nod to other actors in society nudging them to act accordingly. For example, an Eastern Bloc citizen might not receive a formal penalty for leaving the communist party, but their children's admission to university could suddenly become more difficult, of course without any official acknowledgment of the fact.
Agreed. I think that many companies force people to use AI in hopes that somebody will stumble upon a killer use case. They don't want competitors to get there first.
I think the after looks better, it feels more in control, but at the same time, even the before was completely functional and users would be completely happy with it.
I find it very interesting as well. One would think that there might be many problems with similar properties, but people have already discovered the one that surfaces in Turing machines as well. Does this suggest that there are not that many problems with this type of property? Or does it suggest that we stumbled upon the simplest case.
Japanese had it bad for 2-3 years. After that they were allowed to live in their country with their own leadership. Palestinians have it bad for 80 years, they are not allowed to return to their homeland, and we expect them to live in closely monitored concentration camps.
IMO adding ads is not going to be that easy. It is relatively easy to implement ads when the user is scrolling through tons of content and the ads are "organically" injected into the stream. But if the user is seeking a specific answer in a chat-like GUI, what will you do exactly? Whatever ad you will show will have to be visually distinguished and the user will just scroll past to get to the "true" answer they want. Sure, you will still get the product in front of some eyes, but I would expect this to be less effective than other social-media based ads.
Because it's easier to emulate Mediterrean diet as all the ingredients are more likely to be accessible? Japanese cuisine has a lot of funky ingredients that are not really produced outside of Japan or East Asia.
I live in a pretty walkable Spanish city, and 70-year-olds are having a blast here. Even when they can no longer walk and they need to use various mobility devices, they can use the pedestrian infrastructure to move around the city and hang aroun the bars with their friends and families (and they do it basically every day, as far as I can tell). The same population in the US would be basically homebound.
Bibliometrics in science is just an unworkable approach in general, and IMO it causes more harms than not. Research is one of the least suitable human activities that you can possibly try to quantify, yet the entire scientific establishment runs on these metrics by now. I more or less believe that this strategy hinders scientific progress, as it pushes researchers into more and more risk-averse behaviors.
It started as a meme by a small but loyal Hollow Knight fan base on reddit. They had this ongoing joke about waiting for Silksong to release. As subreddits do, they were repeating the same joke for years. For some reason, this admittedly pretty lame joke escaped into mainstream. That is basically all there is to it.
Many countries in Eastern Europe have radically different interpretations of history. The nationalists from each country will try to establish their own ethnicity for persons of interest. They will try to add editorial comments or hyperpartisan sources to all kinds of historical articles. There are edit wars about what language to use for what city in what era. I would guess that this is the case for many other regions of the world.