I think that part of the problem is that value of entertainment has dropped.

Value has dropped, because everyone can nowadays make entertainment and some even use AI to make it. All these people compete against each others in the same markets, even if the products are different type (music, game, video, book, ...). Even if you are an amateur, you can get lucky and create something worth watching, for example just by getting hit by a lightning.

I don't think that piracy is their problem. I think it is all the free stuff you can find from the Internet.

I would not say that AI does scut work well. I have a case that is trivial to do, you could even hire a first grader to do it, but, AI does it with 90% accuracy, when 100% accuracy would be needed.

Instead what AI does really well is work where accuracy does not matter. AI is good solution when 90% accuracy is good enough for you, but if you don't want any mistakes in your data, you should not use AI to make it. Good example of such work is writing proof on concept code. Something that you use to test your idea and then throw away.

One solution is to have different price for electricity and transfer of that electricity. Then you can set the price of transfer based on top demand. This way those who demand most from the grid, will pay most to the grid. And those who require most electricity, will pay most to the produces of electricity.

I have tried AI several times. Different AI models, different versions. When I started testing them, hallucinations was a major problem. It was basically waste of time to ask anything, because answers were so often incorrect. Asking it to write code was also waste of time, because code was so buggy.

But I noticed a big leap from Gemini 2 to Gemini 2.5. It is still unable to answer "difficult" questions, but it is remarkably good as a search engine. It is also good for reading hundreds of pages of pdf and answering simple questions from it. Another thing it is good at is writing simple scripts like "retrieve data from this json file and put it into this database. The quality is not something I would use as a professional, but for hobby projects it works really well (not perfect, but I still get results faster than by doing it manually). Currently, instead of wasting my time, it actually saves sometimes few hours of work or searching.

I have tried to use AI to do actual thinking also, but currently it still fails miserably, it other words, it can not produce similar results in thinking as I can. I would not trust anything that comes as a result of thinking process from AI. I think this is why people think AI is useless.

Upvote the video posted by by dinfinity. It answers pretty much all the questions and even compares it with lithium batteries and air batteries.

> At what point does the unusual become usual? When does abnormal become normal? I guess that depends on context, which is why research like this is very useful.

I disagree. This research does not answer those questions nor is it even related to that. This research is about comparing two different visual presentations, which are both revealed instantly. Two answer your questions or to be related to the frog myth, you would need to reveal data one bit of a time during some period of time. And then compare that into revealing all data at once.

What is boiling frog effect? Considering that there is no proof that such effect exists.
https://en.wikipedia.org/wiki/...

If you ask the question "how long are human blood vessels"

Almost every website will tell you the incorrect answer 100 000 km. From the top results, only wikipedia and quora will give you the correct answer (9000-19000km).

AI will tell you that answer is 100 000 km according to Cleveland clinic. So it provides you a source, but the source is also incorrect. So how do you know?

100X is possible if the problem is so hard that the control group can not solve it at all. For example is developer A has tried solve a problem for a month and failed and gave up. And developer B solves it in 2 weeks. Is developer B a 2X developer or [infinity]X developer?

For problems that others can solve, I think 10X is pretty normal in some cases, but also pretty hard to maintain all the time. But he speed difference depends heavily on the lower end, not the higher end. Just like 100m running, there is a huge speed difference between a toddler and best of the world or even if you take an average person against the champion. But the difference between 1. and 200. is not so big.

You are overthinking. If you as an individual are offered a very large bonus, you will be very tempted to change a company you don't need to have a mess to do so. Google is the only company that constantly makes progress with the AI. The guys listed here are some which I have never heard of, so I assume they are not really the top staff.

Besides, Google has nothing to worry about as long as Demis Hassabis is in the team.

Are you trying to prove that humans can't think?

> But it fails on simplest tasks when doing something new.

https://www.coachloya.com/wp-c...

> And it constantly makes totally obvious errors in calculations.

https://www.quora.com/Why-does...
https://www.youtube.com/watch?...

I find it odd that people are so obsessed with words without defining them. It doesn't matter can AI think or not, unless you define what "thinking" means. Once you have a solid definition for the word, you can test if AI can think or not. Also if we define what swimming means, we can answer the submarine riddle.

If you make more than $23,380 a year, you belong to the top 50%. If you make more than $122,100 you are in the top 10%. Just in case you are wondering if you are rich or not.

But the reason why people misunderstand the rich and poor is because they think it is money that makes people rich. Money is just a tool which has no value in itself. What makes people rich are the goods they own and the goods they can produce. The rich can own automated factories and trade goods with other rich people and live happily without the poor and without money. So there is no need for any evil master plan. The rich will sell goods as long as there are buyers. If there are no buyers, they just produce for themselves. So even if all the rich are humble, good willing and good citizens, your dystopia will happen, if nothing is done to change it.

Only solution that I know of, is government owned factories and farms that produce goods for the masses.

LLMs can do a lot. The problem is that people try to use them into things that they can't do, instead of using them into things they can do. For example I recently had a 200 page document from which I wanted quickly to get some info, so I just gave link to the document and asked AI and got my answer.

Open AI's problem is that they are fixated on making LLM some kind of AGI that can solve any problem and they simply don't have the required skills for that.

Google Deepmind on the other hand developes AI like it should. They don't focus on LLM, it is just a side project for them. Instead they take a real world problem, like "creating medicine" and then develop AI specifically to fix that problem. I really wish that other AI companies would do the same also, because there are so many problems where tailored AI would help and many of those problems are easily solved with minimal skills, so any technical person could do it.

If California joins the larger grid, it would most likely lower the electricity price in California and also in the rest of the USA. It would also most likely lower CO2 emissions. It would also most likely lower the probability of peak prices and blackouts. IMHO only losers would be fossil energy providers.