Why OpenAI, Anthropic & DeepSeek Won't Reach AGI

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🚀 The AI Boom – But Something's Missing

AI is everywhere—writing essays, generating art, even making your to-do list feel less intimidating. We’ve got chatbots that can hold conversations, image generators that can paint like Van Gogh, and prediction models that guess your next online purchase before you even think about it. Impressive, right?
But there’s a catch: AI doesn’t understand time. And without time, AI will never be truly intelligent.

⏳ The Time Problem – AI’s Biggest Blind Spot

Most AI models, from your friendly neighborhood chatbot to the massive brainpower behind search engines, live in a world of static snapshots. Even LLMs (like the ones generating eerily human-like responses) predict text one word at a time, but they don’t actually grasp the passage of time. They don’t remember when something happened in a meaningful way or how events build upon each other.

Imagine an AI that reads “The king was alive in 1800” and “The king died in 1820” but still tells you the king is alive in 2024. That’s because, to AI, time is just another data point—it doesn't experience the flow of past, present, and future like we do. Without a sense of time, AI is just a really smart parrot, mimicking patterns without understanding the story.

⏭ Why Time is the Key to AGI

AI cannot reach AGI without temporal grounding—unambiguous object reference demands a specified time.

Sounds fancy, but here’s what it means: If AI wants to truly think, reason, and be useful in real-world decision-making, it needs to know when things happened. Let’s say you ask AI, “Where is the president?” Without context, it might give you an outdated answer. Shouldn’t it know whether you mean 2024, 2010, or 1776?

Humans do this effortlessly. If someone tells you, “I saw a puppy yesterday,” you don’t assume they’re seeing that exact puppy right now. AI, on the other hand, struggles with this unless explicitly trained on specific time references. This is a fundamental gap between today’s AI and real intelligence.

🛠 How Do We Fix This?

If we ever want AI to be more than a glorified search engine, it needs to: ✅ Track time – When was the data created? When was an event relevant? ✅ Model change – The world isn’t static. AI should update its understanding as things evolve. ✅ Understand causality – Events influence each other. AI should know why something happened, not just that it did. ✅ Build a dynamic memory – Humans remember key events and adjust their thinking accordingly.
AI needs to do the same.

🌍 The AI Giants Are Missing the Point

OpenAI, Anthropic, DeepSeek, and the rest of the AI giants are racing ahead, stacking more GPUs, scaling up their models, and fine-tuning algorithms—but they’re missing something fundamental. They’re training on bigger datasets, but they’re not making AI smarter. Nor aware it of time.

Without a deep understanding of time, all these AI systems will remain glorified autocomplete machines—stuck in an eternal present, unable to truly grasp change, causality, or history.

The world isn’t static, and intelligence isn’t just about crunching more data. Until AI can process and reason about time like humans do, it will never be anything more than a high-speed prediction engine.

If the AI industry wants to build AGI, it’s time to stop chasing marginal improvements in chatbots and start addressing the elephant in the room: AI must evolve beyond statistics and start truly understanding the fabric of reality—time itself.