Google under Sundar Pichai is a terrible company that only succeeds based on its size and monopoly. Let’s be honest, they’re saying that search results will become secondary as they push their service. How do you, as a CEO and board, sign off on an idea that kills most of your (ad) revenue pursuing something that you haven’t even figured out how to monetize? Make it make sense.
I read this a few weeks ago about it.
Google is basically ran like Boeing. Their goal is to maximum the stock price regardless of long-term consequences.
Billions of queries becoming way more energy intensive for a feature almost nobody asked for, now the default. What the fuck are we even doing
Are we taking bets on how long it will be before Google Search ends up on killedbygoogle,com?
The sooner, the better. It’s so painful when I use Google these days. Why is it that smaller people can do seemingly obvious features like custom user-controlled site rankings, but the big players are completely incapable of that?
Why is it that smaller people can do seemingly obvious features like custom user-controlled site rankings, but the big players are completely incapable of that?
Because that would give control to the user. And we all know they hate us having that because they can’t shove their shit down our throats then
How long before Google ends up on killedbygoogle.com?
I thought it was just an ad aggregator.
Awesome. Truly spectacular.
Generative AI is so energy intensive ($$$), that Google is requiring users subscribe to Gemini.
Google is entirely dependent on advertising sales. Ad revenue subsidizes literally everything else, from Android development to whichever 8-12 products and services they launch and subsequently cancel each year.
Now, Google wants to remove web results and just use generative AI instead of search as it’s default user interface.
So, like I said: Awesome.
While I agree in principle, one thing I’d like to clarify is that TRAINING is super energy intensive, once the network is trained, it’s more or less static. Actually using the network isn’t dramatically more energy than any other indexed database lookup.
It’s static, yes, but the static price is orders of magnitude higher. It still involves loading the whole model into VRAM and performing matrix multiplication on trillions of numbers
To be fair, I wouldn’t include “loading the whole model into VRAM” as part of the cost, given they can just keep it in there between different requests, and it might be down to hundreds of billions or dozens of billions instead of trillions… but even after all improvements it should still be orders of magnitude more expensive than normal search, which just makes their decision even crazier
Indexing and lookups on datasets as big as companies like Google and Amazon are running also take trillions of operations to complete, especially when you take into account the constant reindexing that needs to be done. In some cases, encoding data into a neural network is actually cheaper than storing the data itself. You can see this in practice with gaussian splatting point cloud capture, where they are training networks to guide points in the cloud at runtime, rather than storing the position of trillions of points over time.
Training will never stop, tho.
New models will keep coming out, datasets and parameters are going to change.
I firmly believe it will slow down significantly. My prediction for the future is that there will be a much bigger focus on a few “base” models that will be tweaked slightly for different roles, rather than “from the ground up” retraining like we see now. The industry is already starting to move in that direction.
