Long before Google became the default place people go to search the web, its cofounder Larry Page was already thinking about how search should work. Some of the things he talked about back then sound very similar to what Google’s AI system, Gemini, does today.
In the late 1990s, search engines were not very smart. You typed in a word, and they showed pages that used that word. The results were often messy. You had to click through many links just to find one useful page.
Page saw this as a problem.
He believed computers should understand what people are asking, not just match words on a page. If someone searched for a topic, the system should know which pages mattered and why they mattered.
When Google started in 1998, it was small and easy to ignore. Yahoo and AltaVista were much bigger names at the time. Most people did not think Google would take over search.
Page and his team focused on one key idea. Rank pages based on trust. This led to PageRank, which looked at how websites linked to each other. Pages that were linked more often, especially by good sites, ranked higher.
This made Google’s search results feel cleaner and more useful.
Still, Page did not think search should stop there.
He talked about a future where search engines could understand ideas, connect facts, and explain things in simple language. Instead of sending users to ten different websites, computers should help answer questions directly.
At the time, this sounded unrealistic.
Computers were slower. AI research was limited. The internet itself was still growing. But Page kept thinking long term.
Years later, those ideas started to take shape.
Gemini is designed to respond to full questions, not just keywords. People can ask things the way they would ask another person. Gemini tries to give clear answers, short explanations, or summaries instead of a list of links.
This marks a clear change from old-style search.
What stands out is how early Page talked about this direction. He shared these ideas before Google became dominant, before smartphones existed, and before modern AI systems were possible.
He was not following trends. He was imagining what search could become.
Over time, Google invested heavily in data systems, research teams, and machine learning. These choices did not show quick results. They took years to matter. Gemini is one outcome of that long process.
The tools look new, but the thinking behind them is not.
The goal has stayed the same. Make information easier to understand. Help people get answers faster. Reduce the effort it takes to learn something online.
Larry Page described that future long before Google ruled search.
Now, parts of that future are finally showing up.
Also Read: Sam Altman Talks About OpenAI’s Uncertain Path to Going Public
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