
Rare Books: Amazon Uses Them To Train Its Artificial Intelligence
We thought rare books ended up in dusty libraries. Amazon, it seems, has other plans for their future.
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Tuesday, September 15, 2026
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We thought rare books ended up in dusty libraries. Amazon, it seems, has other plans for their future.

From an online bookstore to a text shredder? Amazon is literally tearing up history to feed data to its AI models. A thought-provoking paradox, isn't it?

How many technical books have you bought, swearing you'd study them cover to cover? Someone decided to let an AI learn it for you, so you can flaunt your 'knowledge' effortlessly.

Tired of asking OpenAI for permission every time you want to use AI? Someone just built a desktop app that runs locally, free, with a model packing a million-token context window (basically, it remembers everything like it just read 100 books). And no, you don't need the cloud.
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An unexpected overtake is shaking up the chip world. A Chinese manufacturer has surpassed a Japanese giant in flash memory, shifting balances.

Betting on interest rates is a high-wire act. JPMorgan suggests the Fed might hold steady in July, disappointing those hoping for more hikes.
A startup is betting that video games teach algorithms what textbooks can't: instinct. Millions of hours of gameplay to train robots that understand the world like humans do.
While everyone's debating where AI will find the chips and power to scale, Meta just quietly made a power move in India. A freshly announced deal with Reliance marks the opening of its first AI data center on the subcontinent—and it's not just another warehouse. This is the kind of strategic real estate grab that rewrites the global AI race.

In 2026, you often hear about LLMs, but what exactly are they? An LLM, or Large Language Model, is an extremely advanced artificial intelligence program designed to understand, generate, and manipulate human language. Imagine it as a digital brain that has read an immense amount of text – books, articles, web pages – learning to recognize patterns, styles, and meanings. Thanks to this "learning," it can answer questions, write texts, translate languages, and even create stories, making interaction with technology more natural and intuitive for all of us.