Yeah - The thing though is, you could build the same thing better in a day's work by using OpenAI's API, or Gemini's for that matter.
I wonder if there isn't a deeper, more worrying (for Google) reason behind that - that AI is killing their margin.
Google has always been about delivering top notch services, and winning by being able to do that cheaper than the competition.
It's "in their DNA" - everyone knows that using links to a website as a quality signal was a really good idea in the early days of Google, but what's a little less well known is that the true stroke of genius was the algorithmic efficiency of PageRank.
Similarly for GMail. Remember when it launched, 1 GB of free storage was just completely out of every competitor's league?
It may just be that this recipe of being smarter than everyone on algorithms and on datacenter operations might just not work anymore in the age of modern machine learning.
The problem with current crop of LLM models is that it makes for a great demo. I am also confident that you can build a working prototype for GMail, Outlook or any other surface. But I am equally confident it will be a massively different ballgame to role it out to a billion users. You'll run into a lot of edge cases and have to take care of a lot of adversarial scenarios as well.
Pretty sure that's the same issue Apple is running into as well, and why they have had to postpone rollouts.
I wonder if there isn't a deeper, more worrying (for Google) reason behind that - that AI is killing their margin.
Google has always been about delivering top notch services, and winning by being able to do that cheaper than the competition.
It's "in their DNA" - everyone knows that using links to a website as a quality signal was a really good idea in the early days of Google, but what's a little less well known is that the true stroke of genius was the algorithmic efficiency of PageRank.
Similarly for GMail. Remember when it launched, 1 GB of free storage was just completely out of every competitor's league?
It may just be that this recipe of being smarter than everyone on algorithms and on datacenter operations might just not work anymore in the age of modern machine learning.