Avid Amoeba is right that Google ruined their own search before LLMs entered the public consciousness (this does not mean LLMs didn’t exist before this, but that they were not widely available for the general public to use or became part of the zeitgeist).
If you don’t agree please listen to the Better Offline podcast episode “The Man That Destroyed Google Search”. The episode goes through the rollbacks/changes Google made to their search Algorithm well before AI was commonplace.
Yeah. Also I’m guessing their AI additions to search made their profit margins worse since they take a lot more computation to produce. Although they probably cache a lot of them for common searches.
Even though that surely results in them being able to access more money and makes shareholders richer, that’s not a factor in profit margins. Profit margins are just about revenue vs cost. In this case - how much the make from each search vs how much it costs to produce that search.
Many people around me are using LLMs in many parts of their work al the time. Neutral networks are used in many useful situations. I feel exactly like you, but I’m afraid we’re going to have to cope with it.
The US National Weather Service releases updated 84-hour forecasts every 6 hours. Even with supercomputers at their disposal, due to the computational complexity of simulating physics, that is their best possible effort.
Google, meanwhile, is “developing a machine learning model that it says can accurately predict weather in seconds – not hours – and outperforms 90% of the targets used by the world’s best weather prediction systems.” Using a single desktop computer, they can generate a highly accurate 10-day forecast in under a minute.
Yes. Search generally pulls data from databases. It doesn’t compute weather forecasts. The addition of AI results is net addition computation. In the worst case scenario where the generation of the AI results happens on-the-fly, that’s a lot more computation. I’m sure they pre-compute a lot of them so they’re not in the worst case scenario. However in the best case scenario they still have to do this new additional heavy (check LLM compute usage) computation once per result. So the profit margin for search is very likely lower than it used to be when isolating for this variable. If they’re somehow increasing their revenue from these results, that’s another variable that might offset it. I’ve no idea. What I’m certain about is the cost is higher after AI results were introduced because more energy is used.
They specifically made search less accurate so that users would search multiple times to boost the number of ads that get displayed to juice their numbers for quarterly earnings. You can blame Prabhakar Raghavan.
They ruined it without AI before AI was commonplace. They ruined it with higher profit margins. 🥹
Avid Amoeba is right that Google ruined their own search before LLMs entered the public consciousness (this does not mean LLMs didn’t exist before this, but that they were not widely available for the general public to use or became part of the zeitgeist).
If you don’t agree please listen to the Better Offline podcast episode “The Man That Destroyed Google Search”. The episode goes through the rollbacks/changes Google made to their search Algorithm well before AI was commonplace.
Yeah. Also I’m guessing their AI additions to search made their profit margins worse since they take a lot more computation to produce. Although they probably cache a lot of them for common searches.
Probably made the margins better because investors apparently still love hearing the word “AI” attached to shit
Even though that surely results in them being able to access more money and makes shareholders richer, that’s not a factor in profit margins. Profit margins are just about revenue vs cost. In this case - how much the make from each search vs how much it costs to produce that search.
I hope AI is the new metaverse. I’ll have a good chuckle when it all implodes.
Many people around me are using LLMs in many parts of their work al the time. Neutral networks are used in many useful situations. I feel exactly like you, but I’m afraid we’re going to have to cope with it.
The US National Weather Service releases updated 84-hour forecasts every 6 hours. Even with supercomputers at their disposal, due to the computational complexity of simulating physics, that is their best possible effort.
Google, meanwhile, is “developing a machine learning model that it says can accurately predict weather in seconds – not hours – and outperforms 90% of the targets used by the world’s best weather prediction systems.” Using a single desktop computer, they can generate a highly accurate 10-day forecast in under a minute.
More information:
https://www.weforum.org/stories/2023/12/ai-weather-forecasting-climate-crisis/
Given this information, and given the enshittification of Google search, would you still make the same guess about their profit margins?
Yes. Search generally pulls data from databases. It doesn’t compute weather forecasts. The addition of AI results is net addition computation. In the worst case scenario where the generation of the AI results happens on-the-fly, that’s a lot more computation. I’m sure they pre-compute a lot of them so they’re not in the worst case scenario. However in the best case scenario they still have to do this new additional heavy (check LLM compute usage) computation once per result. So the profit margin for search is very likely lower than it used to be when isolating for this variable. If they’re somehow increasing their revenue from these results, that’s another variable that might offset it. I’ve no idea. What I’m certain about is the cost is higher after AI results were introduced because more energy is used.
They specifically made search less accurate so that users would search multiple times to boost the number of ads that get displayed to juice their numbers for quarterly earnings. You can blame Prabhakar Raghavan.
They ruined it by setting themselves as untouchable and wanting bigger profit margins than “richer than God” money.