Google search won’t exist in the medium term. Why use a list of static links you have to look through manually if you can just ask AI what the answer is? Ai tools like chatgpt are what Google wanted search to be in the first place.
Because you cannot trust the answers AI gives. It presents hallucinated answers with the same confidence as true answers (e.g. see https://news.ycombinator.com/item?id=45322413 )
Aren't blogspam/link farms the equivalent in traditional search? It's not like Google gives 100% accurate links today.
Yes. Google Search on its own generates about $200b/y, so capturing Google Search's market would be worth $1t based on 5x multiplier. GPT is more valuable than search because GPT has more control over the content than Search has.
Personal hot take: China is forbidding its companies from buying Nvidia chips and instead wants to have its industries use China-made chips.
I think a big part of the reason for this is that they want to take over Taiwan and they know that any takeover could likely destroy TSMC and instead of this being a bad thing for them it could actually give them a competitive advantage vs everyone else.
The fact that the US has destroyed relationships with so many allies implies it may not stop a Taiwan invasion when it happens.
It isn’t a question asked by people generally suspicious of productivity claims. It’s only asked by LLM skeptics, about LLMs.
That doesn’t seem to me like a good reason to dismiss the question, and especially not that strongly/aggressively. We’re supposed to assume good intentions on this site. I can think of any number of reasons one might feel more productive but in the end not be going much faster. It would be nice to know more about the subject of the question’s experience and what they’re going off of.
You’re right; I’m rereading and it’s rude. Thanks.
It is the kind of question that takes into account that people thinking that they are more productive does not imply that they actually are. This happens in a wide range of contexts, from AI to drugs.
It isn’t a question asked by people generally suspicious of productivity claims. It’s only asked by LLM skeptics, about LLMs.
Maybe you are not aware of such kinds of topics, but yes it is asked often. It is asked for stimulants, for microdosing psychedelics, for behavioural interventions or workplace policies/processses. Whenever there are any kind of productivity claims, it is asked, and it should be asked.
Just you switching away from Google is already justifying 1T infrastructure spend. Just think about how much more effective advertisements are going to be when LLMs start to tell you what to buy based on which advertiser gave the most money to the company.
> Just think about how much more effective advertisements are going to be when LLMs start to tell you what to buy based on which advertiser gave the most money to the company. Optimistic view: maybe product quality becomes an actually good metric again as the LLM will care about giving good products. Yea, I know, I said it's an optimistic view.
Has a tech company ever taken 10s or 100s of billions of dollars from investors and not tried to a optimize revenue at the expense of users? Maybe it's happened but I literally can't think of a single one.
Given that the people and companies funding the current AI hype so heavily overlap with the same people who created the current crop of unpleasant money printing machines I have zero faith this time will be different.
It is the kind of question that takes into account that people thinking that they are more productive does not imply that they actually are. This happens in a wide range of contexts, from AI to drugs.
It's not that hard to review how much you actually got done and check whether it matches how much it felt like you were getting done.
To do that properly, one needs some kind of control, which is hard to do with one person. It should be doable with proper effort, but far from trivial, because it is not enough to measure what you actually did in one condition, you have to compare it with sth. And then there can be a lot of noise for n=1: when you use LLMs, maybe you happen to have to solve harder tasks. So you need at least to do it over quite a lot of time, or make sure the difficulty of tasks is similar. If you have a group of people, you can put them into groups instead and thus not care as much for these parameters, because you can assume that when you average this "noise" will cancel out.