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Japan’s Own AI Revolution: Building ChatGPT with a Sushi Twist!

Hey there, tech-savvy friends! It’s your pal, DataSagar, and boy, do I have some hot and steaming tech news for you! Japan, the land of sushi, sumo, and, let’s not forget, super cool tech gadgets, is venturing into the wild world of AI chatbots. They’re crafting their own version of ChatGPT, that chatty AI sensation from the folks over at OpenAI. It’s like they’re cooking up their special recipe for tech takoyaki!

Picture this: the Japanese government, along with tech bigwigs like NEC, Fujitsu, and SoftBank, are tossing in hundreds of millions of dollars to whip up AI systems that speak fluent Japanese. Yep, you heard it right, they want their AI to talk like a local, not some lost-in-translation robot.

So, why all the fuss, you ask? Well, it turns out, current AI models, like ChatGPT, are like wizards in English but stumble over their kimono when it comes to Japanese. You see, Japanese isn’t just a different language; it’s a whole different beast. While English has a cozy 26-letter alphabet, Japanese is flexing its muscles with two sets of 48 basic characters and over 2,000 Chinese characters (they call ’em kanji). It’s like the AI equivalent of juggling sushi knives!

Imagine this: when ChatGPT tries to converse in Japanese, it sometimes throws out super rare characters that most folks have never laid eyes on. It’s like trying to read a secret ninja code. Trust me, it’s not easy!

But it's not just about language; it's also about cultural finesse. Think of it this way: if ChatGPT were Japanese, it might pen a job application email that's about as polite as a sumo wrestler in a tea ceremony. It would scream "English translation alert!" They want their AI to blend in seamlessly, like a ninja in the night.

To see just how well these AI chatbots blend in, some crafty researchers invented a ranking system called Rakuda. They basically asked ChatGPT to tackle tricky questions about Japanese culture and evaluated how smoothly it handled them. Surprise, surprise! ChatGPT, aka GPT-4, aced the test, claiming the top spot. Go, GPT-4, go!

But don’t count out the Japanese just yet. They’ve got their secret weapon: the Fugaku supercomputer. This beast is one of the fastest in the world, and they’re using it to train a Japanese LLM (that’s Large Language Model, not some new sushi roll). This homegrown Japanese LLM, slated for release next year, will be open source, which means everyone can get a taste of its coding magic. They’re aiming for a whopping 30 billion parameters – that’s tech speak for its size and complexity.

But wait, there’s more! Japan’s Ministry of Education, Culture, Sports, Science, and Technology is splurging big bucks to create an AI for science stuff. It’s like having a lab assistant that can generate scientific hypotheses by reading research papers. They’re starting with 100 billion parameters – that’s over half the size of GPT-3! It’s a colossal effort that could speed up scientific discoveries, but it’ll cost them a cool ¥30 billion (about US$204 million) and won’t hit the scene until 2031. Science takes time, folks!

And you know what’s really cooking in Japan’s tech kitchen? Companies like NEC and SoftBank are already putting their Japanese LLMs to work. NEC’s generative AI is slicing and dicing report writing and software code, while SoftBank is pouring ¥20 billion into creating its very own LLM. They’re gearing up to serve universities, research institutions, and more. It’s like a tech sushi train, but instead of sushi, you get AI smarts!

In the end, Japan’s quest to create a top-notch, culturally savvy AI chatbot isn’t just about tech. It’s about bridging language gaps, making scientific strides, and maybe even sharing a bit of Japanese culture with the world. So, stay tuned, tech aficionados, because a Japanese ChatGPT could be the next big thing, and who knows, it might even teach you how to order sushi like a pro!

Catch you on the tech flip side, and remember, keep it quirky and keep it techy! 🍣🤖

The author of this blog post is a technology fellow, an IT entrepreneur, and Educator in Kathmandu Nepal. With his keen interest in Data Science and Business Intelligence, he writes on random topics occasionally in the DataSagar blog.
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