- it causes mass unemployment and social unrest
- leads to a further concentration of wealth and increase in wealth inequality
- it means I have to work more, produce more, all for the same wage or less
- it's implementation leads to large societal harms such as increased isolation/loneliness
- it ends up being overhyped causes a large economic crisis
I'd guess it might be more of a structured/agentic approach - maybe having learnt how to map "search" strings to relevant data retrieval queries, then combining/summarizing the returned results.
- it works when the info is either relatively well known or quite new
- no-AI mode now becomes dumber, the old trick to "grep" the internet with +/-/"" is gone
At least some of the Google search operators seem to still work, although Google themselves aren't very forthcoming about documenting these.
It's probably the most popular AI on earth by daily queries, and likewise probably an ~8B level model, it means a whole bunch of people equate Google AI to AI overviews.
I do probably 40% of my searches with AI Mode now. It can't possibly be profitable (and maybe that's why it's not more discoverable), but the results are awesome.
Edit: I also tried to show my aging parents how to use it, and it was inexplicably not available on their devices. They use old (10ish year) ios devices, which is apparently incompatible even though it's a web interface.
It also seems to excel at things ChatGPT 5 Thinking isn't good at. Simple things like "Here's a screenshot of text, please transcribe it" - ChatGPT 5 Thinking will spend 2 minutes and still get the results wrong, while Gemini Pro will spend 20-30 seconds and transcribe everything perfectly.
Obviously that's just 1 use case, but as someone who previously used ChatGPT exclusively, I'm increasingly impressed by Gemini the more I use it. Mainly due to the much faster thinking times that seem to provide equal or better results than GTP 5 Thinking.
OpenAI searches are even better, but GPT5 is extremely slow with thinking. Without thinking it's roughly equivalent.
I'm sure this method _did_ come under discussion in the lawsuit & settlement, but as you pointed out the settlement itself was only about pirated works.
I've gotten it to identify:
- the comic from a random page of an obscure Russian comic
- obscure French comedy from a random clip
It was extra impressive because even reverse search from lens didn't immediately identity them
- When I know so little about a subject that the concepts are all vague and I'm intellectually grasping in the dark. LLMs are good at taking my imprecise wording and orienting me towards the paths/gradients others have taken.
VS
- I know this subject well enough and instead of fumbling around I want to be able to run grep over a massive amount of open text data.
While the former mode is useful, the act of training without asking has led to the repopularization of walled gardens. Early Google felt like being able to grep every library book in existence and a 3 paragraph summary in response to very poorly worded questions is a terrible trade.
I know Simon is smart and he included his search terms with their warts to be open so I don't want to elicit shame over this. But cmon, just type out bought ("Anthropic but lots of physical books..."). Complete anecdote but I have noticed my LLM reliant friends have become way worse at texting and it feels like it's worth taking 5 seconds to try to structure your thoughts, simply for the practice
Google answers more concisely, faster and confidently, but not convinced quality of output is better. e.g. Google pulled in info from AWS and Oracle cloud when I asked a GCP specific question. Perplexity sourced only from GCP docs
Which is an interesting outcome since I'd expect google to excel in the search aspect
Sharlin•2h ago