191–200 of 512 posts
Was this written by an LLM? It's pretty bad copy. Maybe they laid off their copywriting team...? > "Now millions of developers are building with Gemini. And it’s helping us reimagine all of our products — including all 7 of them with 2 billion users — and to create new ones" and > "We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading…
Sorry, what's wrong with these phrases?
No mention of Perplexity yet in the comments but it's obvious to me that they're targeting Perplexity Pro directly with their new Deep Research feature ( https://blog.google/products/gemini/google-gemini-deep-resea... ). I still wonder why Perplexity is worth $7 billion when the 800-pound gorilla is pounding on their door (albeit slowly).
Just tried the deep search. It's a much much slower experience than perplexity at the moment - taking sweet many minutes to return result. Maybe it's more extensive but I use perplexity for quick information summary a lot and this is a very different UX. Haven't used it enough to evaluate the quality, however.
Perplexity is a much less versatile product than it has to be in the chase of speed: you can only chew through so many tokens, do so much CoT, etc. in a given amount of time.
They optimized for virality (it's just as fast as Google but gives me more info!) but I suspect it kills the stickiness for a huge number of users since you end up with some "embarrassing misses": stuff that should have been a slam dunk, goes off the rails due to not enough search, or the wrong context being surfaced from the page, etc. and the user just doesn't see value in it anymore.
Think of Google as of a tanker ship. It takes a while to change course, but it has great momentum. Sundar just needs to make sure the course is right.
That's almost word for word what people said about Windows Phone when I was at Microsoft.
Earlier quoted context omitted.
You're still focused about inference :) inference basically does not matter, it is a commodity
That makes no sense. Inference cost dwarf training cost if you have a succesfull product pretty quickly. Afaik there is no commodity hardware that can run state of the art models like chatgpt-o1.
Stack enough GPUs and any of them can run o1. Building a chip to infer LLMs is much easier than building a training chip.
Just because one cost dwarfs another does not mean that this is where the most marginal value from developing a better chip will be, especially if other people are just doing it for you. Google gets a good model, inference providers will be begging to be able to run it on their platform, or to just sell google their chips - and as I said, inference chips are much easier.
Flash combines speed and cost and is extremely good to build apps on.
People really take that whole benchmarking thing more seriously than necessary.
Earlier quoted context omitted.
Sorry, what's wrong with these phrases?
> all of our products — including all 7 of them All the products including all the products?
"...all of our products — including all 7 of them with 2 billion users..."
It tells people that 7 of their products have 2b users.
"With your supervision". Thus avoiding Google being held responsible. That's like Teslas Fake Self Driving, where the user must have their hands on the wheel at all times.
Big companies can be slow to pivot, and Google has been famously bad at getting people aligned and driving in one direction. But, once they do get moving in the right direction the can achieve things that smaller companies can't. Google has an insane amount of talent in this space, and seems to be getting the right results from that now. Remains to be seen how well they will be able to productize and market, but hard…
> Remains to be seen how well they will be able to productize and market The challenge is trust. Google is one of the leaders in AI and are home to incredibly talented developers. But they also have an incredibly bad track record of supporting their products. It's hard to justify committing developers and money to a product when there's a good chance you'll just have to pivot again once they get bored. Say what you w…
Eh... I don't know about that. Their tech graveyard isn't as populous as Google's, but it's hardly empty. A few that come to mind: ATL, MFC, Silverlight, UWP.
Earlier quoted context omitted.
> Remains to be seen how well they will be able to productize and market The challenge is trust. Google is one of the leaders in AI and are home to incredibly talented developers. But they also have an incredibly bad track record of supporting their products. It's hard to justify committing developers and money to a product when there's a good chance you'll just have to pivot again once they get bored. Say what you w…
> they also have an incredibly bad track record of supporting their products Incredibly bad track record of supporting products that don't grow . I'm not saying this to defend Google, I'm still (perhaps unreasonably) angry because of Reader, it's just that there is a pattern and AI isn't likely to fit that for a long while.
My main issue with Google is that internal politic affects users all the time. See the debacle of anything built on top of Android and being treated as a second citizen.
You can’t trust a company which can’t shield users from its internal politics. It means nothing is aligned correctly for users to be taken seriously.