The 10 blue links aren’t gone, but AI is pushing them down the page.
The AI snapshots borrow colors from the content they discover and change depending on what you search.Google feels pretty good about the state of its search results. We’re long past the “10 blue links” era of 25 years ago when you Googled by typing in a box and getting links in return. Now you can search by asking questions aloud or snapping a picture of the world, and you might get back everything from images to podcasts toMany searches are already well-served by these results.
“The bottleneck turns out to be what I call ‘the orchestration of structure,’” says Prabhakar Raghavan, the SVP at Google who oversees Search. Much of that data existson the internet or even within Google — museums post hours on Google Maps, people leave reviews about wait times at restaurants — but putting it all together into something like a coherent answer is really hard.
That’s the idea, but Raghavan and Reid are both quick to point out that SGE still can’t do these completely creative acts very well. Right now, it’s going to be much more handy for synthesizing all the search data behind questions like “what speaker should I buy to take into the pool.” It’ll do well with “what were the best movies of 2022,” too, because it has some objective Rotten Tomatoes-style data to pull from along with the internet’s many rankings and blog posts on the subject.
The reason for this goes beyond just that strange itchy feeling you get talking to a chatbot for too long. And it doesn’t seem like Google is just trying to avoid super horny AI responses, either. It’s more a recognition of the moment we’re in: large language models are suddenly everywhere, they’re far more useful than most people would have guessed, and yet they have a worrying tendency to be confidently wrong about just about everything.
Google projects a lot of confidence in its ability to be factually strong, but recent history seems to suggest otherwise. Not only is Bard less wacky and fun than ChatGPT or Bing, but it’s also— it makes basic mistakes in math, information retrieval, and more. The PaLM2 model should improve some of that, but Google certainly hasn’t solved the “AI lies” problem by a long shot.
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