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Nvidia Is Copying the Earth

Eric Schmidt of Google once said it would take 300 years to crawl and index all the digital information in the world. Thirty years later, Google has collected, structured, and ranked the planet’s data, establishing itself as the central hub of global information.
This process has been one of humanity’s long attempts to digitally capture the sum of its knowledge.

Around the same time, Facebook began copying humanity itself. It targeted not only personal attributes and relationships but even private exchanges, mapping them into a social graph that visualized how people are connected.
If Google drew the “map of knowledge,” Facebook drew the “map of human relationships.”

AI has bloomed on top of these vast copies. What AI seeks is not mere volume of data, but the ability to analyze accumulated information and transform it into insight. Value lies in that process of interpretation. For this reason, possessing more data no longer guarantees advantage—what matters now is the ability to understand and utilize it.

So, what becomes the next battleground?
After the maps of knowledge and human connection, what is the next domain to be replicated? One emerging answer lies in Nvidia’s current approach.

Nvidia is attempting to copy the Earth itself. Whether we call it a Digital Twin or a Mirror World, the company is trying to reconstruct the planet’s structure and dynamics within its own ecosystem.
It aims to simulate the movements of the physical world and overlay them with digital laws. This marks a departure from the information-based replication of earlier internet companies, moving instead toward the duplication of reality itself.

What lies ahead is a complete digital copy of Earth—and a new industrial ecosystem built upon it. In Nvidia’s envisioned world, cities, climates, and economies all become entities that can be simulated. Within that digital Earth, AI learns, reasons, and reconstructs. Humanity has moved from understanding the planet to recreating it.

Yet if we wish to honor diversity and generate more possibilities in parallel, what we will need are not one, but countless “worlds.” Rather than imitating a single correct reality, AI could generate multiple “world lines” that diverge under different conditions. We can imagine a future where AI compares these world lines and derives the most optimal outcome. Such a vision would require an immense foundation of computational power.

This is no longer a contest of information processing alone but a struggle over resources themselves. The question becomes how efficiently we can transform energy into computation.The industries that produce semiconductors and the infrastructures that generate and distribute energy will form the next field of competition.
Nvidia’s challenge is not about data but about the “replication of worlds”—a new scale of technological struggle, an attempt to rewrite civilization with the Earth itself as the stage.

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Why Didn’t Google Build ChatGPT?

When OpenAI released ChatGPT, I believe the company that was most shocked was Google.

They had DeepMind. They had Demis Hassabis. By all accounts, Google had some of the best researchers in the world. So why couldn’t they build ChatGPT—or even release it?

Google also had more data than anyone else.
So why did that not help? Perhaps it was because they had too much big data—so much of it optimized for search and advertising that it became a liability in the new paradigm of language generation. Data that had once been a strategic asset was now too noisy, too structurally biased to be ideal for training modern AI.

Having a large amount of data is no longer the condition for innovation. Instead, what matters now is a small amount of critical data, and a team with a clear objective for the model’s output. That’s what makes today’s AI work.

That’s exactly what OpenAI demonstrated. In its early days, they didn’t have access to massive GPU clusters. Their partnership with Microsoft only came later, after GPT-3. They launched something that moved the world—with minimal resources, and a lot of design and training ingenuity. It wasn’t about quantity of data, but quality. Not about how much compute you had, but how you structured your model. That was the disruptive innovation.

And what did Big Tech do in response? They began buying up GPUs. To preempt competition. They secured more computing power than they could even use, just to prevent others from accessing it.

It was a logical move to block future disruptions before they could even begin. In language generation AI especially, platforms like Twitter and Facebook—where raw, unfiltered human expression is abundant—hold the most valuable data. These are spaces full of emotion, contradiction, and cultural nuance. Unlike LinkedIn, which reflects structured, formalized communication, these platforms capture what it means to be human.

That’s why the data war began. Twitter’s privatization wasn’t just a media shakeup. Although never explicitly stated, Twitter’s non-public data has reportedly been used in xAI’s LLM training. The acquisition likely aimed to keep that “emotional big data” away from competitors. Cutting off the API and changing domains was a visible consequence of that decision.

And just as Silicon Valley was closing in—hoarding data and GPUs—DeepSeek emerged from an entirely unexpected place.

A player from China, operating under constraints, choosing architectures that didn’t rely on cutting-edge chips, yet still managing to compete in performance. That was disruptive innovation in its purest form.

What Google had, OpenAI didn’t. What OpenAI had, Google didn’t. That difference now seems to signal the future shape of our digital world.

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Google Self-Driving Car Project – A First Drive


Here it is. The future is closer than we think.

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Pinterest Raises A $200 Million

They’re trying to become a next Twitter/Facebook.

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What is the biggest website in Japan?

This interactive map can show us how famous sites are big. And you can compare sites.

If you look for .jp sites and zoom it up, you can see Japan version of the map. Here is the biggest one.

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Disabled Google Instant Search

Decided to disable Google Instant Search option which removes my keywords when I search in Japanese. That’s useful but not for Japanese search. Especially for Safari users like me.

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How can I handle multiple social platforms? Here is my workflow


We have too many places to update our status or pictures recently. The latest web innovations made us easy to connect to the world but at a time, it gave us too many options.
We’re in a complicated situation again. But I believe we stepped forward, and got a lot more opportunities with the huge innovations.
So I tried to make 3 steps to make things clear. My goal is to find out how I can use multiple social platforms efficiently without extra effort. I hope this post helps you to find your own way to connect to the new social world.

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The Most Impressive Ad Ever By Google


Today Google announced some updates about Google+. And now they make it public for all users using Google service. And Google put the impressive ad on Google.com. Did you already noticed? I suppose no one can ignore it.

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How NFC devices change ads around us?


Here is an obvious thing. Foursquare and its clones including Japan made clones have to be happy with the Facebook’s decision about their location service.

Anyway, they must have ideal strategies to beat their enemies. There’re a lot of clones here in Japan now. A big difference between Foursquare and Japan made clones is mobile clients. Most of Japan made clones support typical Japanese mobile phones unlike iOS/Android devices. It means they’re based on Japanese mobile phone culture. This difference is making some innovative movement right now. They get some ideas from typical Japanese mobile phones.

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First Step Of Google Buzz

Kevin posted what he thought on his blog.
Changes/Feature Requests For Google Buzz – Kevin Rose

The big news here isn’t really the functionality of Pownce Buzz, but that Google is boldly integrating this directly into their Gmail product

And he listed up his requests. Google Buzz is definitely in a beta stage but they’ve launched to get opinions and I know they will learn from it. Try the current version and give your opinions through the web.

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