Why didn't we get an AI like GPT-2 in 2005? The hardware was there

By Gi Pyeong Lee
AI History GPT-2 Tech Trivia
An image contrasting the clunky computer environment of 2005 with cutting-edge AI technology
AI Summary

While training a GPT-2 level AI was technically possible with 2005 technology, the lack of algorithmic expertise, investment priorities, and low social interest delayed its realization until 2019.

Imagine if the smart AI assistant we use every day had existed 20 years ago, in 2005. A world where you wake up, turn on your computer, tell the AI, “Summarize yesterday’s news,” and it answers you right away.

Surprisingly, if you crunch the numbers, it was technically possible to train an OpenAI language model like GPT-2 using the computing power of 2005. Reference 8, Reference 13. So why did we have to wait until 2019 to see it? If hardware wasn’t the issue, what was missing?

Why does this matter?

This question isn’t just about looking back at the past. We often ask, “Why did AI take so long to develop?” or “Why is it progressing so rapidly now?” Understanding why GPT-2 didn’t emerge in 2005 helps us realize that technological progress isn’t determined solely by machine power (hardware)—it only becomes reality when appropriate algorithms and investment come together.

Simply put: The relationship between ingredients and a recipe

Think of it this way: to cook a delicious meal, a giant kitchen (hardware) is important, but a killer “recipe” (algorithm) is even more crucial. The supercomputer of 2005, ‘BlueGene/L,’ was like having the largest and most luxurious kitchen in the world. Using this kitchen, it would have taken about 41 days to complete the GPT-2 “dish.” Reference 8.

However, the chefs of that time lacked the most important recipe: the “Transformer” (an AI structure that identifies relationships between words in sentences). Reference 8. Techniques like “Adam optimization” (a method that speeds up AI training) hadn’t been invented yet either. It was like having the best kitchen equipped with the latest oven, but being completely lost on what ingredients to use or how to cook.

Current situation: Why is it getting attention now?

GPT-2 was officially released by OpenAI in 2019. Reference 12. While the model, trained on data from 8 million web pages, surprised the world, many initially considered it a “fun but half-baked toy.” Reference 11.

At the time, AI research wasn’t the field receiving massive investment like it is today; it was sometimes even dismissed as “pseudoscience.” Reference 7. Investors were pouring computing resources into fields grappling with regulations or research related to nuclear weapons rather than AI. Reference 7. It was a cold winter for AI, not just in terms of technical foundations, but also in social interest and capital flow.

What happens next?

Today, we live in an era where models with over 1.5 trillion parameters appear. AI models now perform astronomical calculations, requiring 1.9 × 10²⁰ to 2.5 × 10²¹ FLOPs (a unit of computer operations) for training. Reference 6, Reference 9.

Moving forward, research on how to achieve smarter results with fewer resources will become more active than simply building larger computers. As each new model emerges, we will need to watch how the “performance-to-price” ratio changes and contemplate how to adapt our daily lives accordingly. Reference 10.

MindTickleBytes AI Reporter’s perspective

The reason we had to wait until 2019 for something possible with 2005 technology reminds us that technology is not created by machines alone, but by a combination of human curiosity and the social soil that supports that curiosity. The technological advancements we see today also depend not on the hardware capacity we have right now, but on how we fuel the embers of research in the directions we choose to take.

References

  1. GPTImage2(ChatGPT Images2.0): Free Online, No Sign-up
  2. He Asked ChatGPTOne Question and ItGetsDisturbingly… - YouTube
  3. ChatGPT Images2.5 — бесплатный ИИ-генератор и редактор фото
  4. FreeGPTImage2Online ｜AI Image Generator… - Img Creator AI
  5. ChatGPT Images2.0: Try AI Image Generation
  6. Why didn’t we get GPT-2 in 2005? - hn.today
  7. Why didn’t we get GPT-2 in 2005? : r/mlscaling - Reddit
  8. [Why didn’t we get GPT-2 in 2005? Hasty Briefs](https://hb.int2inf.com/en/s/item/T4BcbcDVfviZ83kREhv9Xp-why-no-gpt2-in-2005)
  9. Why didn’t we get GPT-2 in 2005? - Substack
  10. Why didn’t we get GPT-2 in 2005? - hoton.ai
  11. Why didn’t we get GPT-2 in 2005? : r/slatestarcodex - Reddit
  12. GPT-2 - Wikipedia
  13. [Why didn’t we get GPT-2 in 2005? Itai Katz - LinkedIn](https://www.linkedin.com/posts/itaijkatz_why-didnt-we-get-gpt-2-in-2005-activity-7266848522186932224-deGR)
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Test Your Understanding
Q1. How long would it have taken to train GPT-2 using the highest-performing supercomputer available in 2005?
  • About 41 days
  • About 1 year
  • About 10 years
It is estimated that it would have taken about 41 days to train using BlueGene/L, the top-performing supercomputer at the time.
Q2. What core technology was missing in 2005 that made training such an AI model impossible?
  • The Internet
  • Transformer architecture and Adam optimization
  • Data storage
In 2005, key algorithmic techniques like the Transformer architecture and Adam optimization had not yet been invented.
Q3. How was GPT-2 generally perceived at the time of its release?
  • Everyone thought it was revolutionary
  • It was treated as a toy-level novelty
  • It was considered the most important AI model
When GPT-2 was released, many people treated it as an interesting but half-baked toy rather than a highly useful tool.
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