China AI Blitz? More Like Chinese AI is the Shitz

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‍China has gone on an AI rampage claiming it has created the best two open-source AI models all in the span of a week: DeepSeek’s R1 and Alibaba’s Qwen 2.5-Max. Both claim to outgun OpenAI, crush costs, and threaten Nvidia’s GPU empire. But is this the truth? Would China lie to us? Is China bluffing about its chip independence? Despite the low energy output and chip claims, neither model solves AI’s fatal flaw. The real answer? Verses AI’s Genius Model—a cognitive revolution that makes LLMs look like a Motorola flip phone compared to its iOS 16. Let’s break this whole psyop down first; we’ll get into Verses AI’s Genius Model after.

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China’s Power Play: Smoke, Mirrors, and Likely Just Nvidia Chips

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China’s back-to-back AI launches—DeepSeek R1 and Alibaba’s Qwen 2.5-Max—could very well be nothing but a geopolitical attempt to mog the West by using sus claims of "cutting costs" and" increasing efficiency".

- DeepSeek R1: Claims to be 10x cheaper than GPT-4, trained on a shoestring budget.

- Qwen 2.5-Max: Boasts 89.4% accuracy on Arena-Hard, crushing OpenAI and Meta’s models.

Both models flaunt “efficiency” thanks to Mixture-of-Experts (MoE) architectures, which use fewer computational resources. Alibaba even bragged about training Qwen on 20 trillion tokens with homegrown Hanguang 800 chips.

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However: Is China lying about ditching Nvidia?

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Despite U.S. export bans, reports suggest Chinese tech giants hoarded $5B+ of Nvidia GPUs before sanctions hit. In layman's terms, China’s “efficiency” might rely on smuggled H100s and A100s retrofitted into domestic systems. Beyond the potential purchases of pre-sanctioned GPUs, rumors are spreading that the Chinese are actively doing whatever they can to get their hands on/purchase American chips.

The motive behind this? (possibly) Power—by hyping cheap AI, it could be China’s attempt to smoke out Nvidia’s stock (already down 17% this week) and bait the U.S. into loosening chip restrictions. This could very well be a high-level psyop with trillion-dollar stakes.

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Nvidia’s Nightmare

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China’s AI spam fest isn’t just about having the best models—it’s may be about decreasing demand for Nvidia’s GPUs. Here are the numbers:

- Qwen 2.5-Max’s MoE design slashes infrastructure costs by 40-60%, meaning enterprises need fewer GPUs.

- DeepSeek’s “low-cost” AI could flood the market with budget models, decimating the need for $40K H100 clusters.

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The Following Crash Out:

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- Nvidia lost $589B in market cap in 48 hours this week.

- Semiconductor stocks (AMD, Intel) are wobbling as investors question if the AI hardware gold rush is over.

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But here’s the chess move: China still needs Nvidia. Their domestic chips (Hanguang, Ascend) can’t match U.S. GPUs for raw power. This “efficiency” claim might just be a stalling tactic while China reverse-engineers Nvidia tech.

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The LLM Illusion: Why China’s Models Don’t Actually Solve Anything

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Large Language Models (LLMs) like OpenAI’s GPT-4 or Alibaba’s Qwen 2.5-Max are essentially autocomplete on roids. They’re trained on heaps of text to predict the next word in a sequence, spitting out “human-like” responses by mimicking patterns—not logic. The result? They make up facts, parrot pre-approved biases, and fail catastrophically at tasks requiring real reasoning. They’re the McDonald’s of AI: quick, cheap, and deeply unsatisfying if you need actual nutrition.

How Verses’ Genius Model Smokes Out the Opposition
Verses’ Genius isn’t an LLM—it’s a cognitive engine built on active inference, a framework inspired by how biological brains work. Instead of guessing words, Genius reasons through problems by testing hypotheses, adapting to feedback, and minimizing uncertainty.

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The Mastermind Showdown:

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- Genius cracked codes every time, averaging 1.1–4.5 seconds per game, costing $0.05 total.

- OpenAI’s “advanced” o1-preview failed 29% of the time, took up to 15 minutes per game, and burned $263.

Genius achieved this not with supercomputers, but on a MacBook M1. Meanwhile, OpenAI used pricey GPU cloud servers. This isn’t a minor improvement—it’s a full system reset of what’s possible in AI efficiency. While LLMs throw money and power at problems, Genius solves them with lean, adaptive intelligence. The future isn’t “bigger models”—it’s smarter ones.

Translation: Genius is 140x faster, 5,260x cheaper, and runs on a Goddamn laptop.

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Why Genius Will Soon Be the Only AI That Matters

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While China and Silicon Valley have a pissing match over who the king of the LLM hill is, Verses AI is focused on building something long-term, sustainable, and scalable.

- Active Inference: Genius doesn’t guess—it reasons. Like a human, it tests hypotheses, learns from feedback, and adapts in real-time.

- Hardware Agnostic: No $40K GPUs needed. Genius runs on anything from cloud clusters to Samsung smart fridges.

- Explainable & Ethical: Every decision is traceable. No black-box bias or hallucinations.

- Cost Apocalypse: At $0.05 per 100 tasks, Genius could undercut every AI model on Earth.

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The Bottom Line: China’s Big Week in AI Could Just Be a Psyop

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China’s LLM win is like a bump—it’ll feel good for a bit, but it all comes crashing back. Whether they’re using smuggled Nvidia chips or not, they’re still stuck in the “bigger, faster, dumber” AI loop. The real revolution isn’t happening in Beijing or Silicon Valley—it’s happening at Verses.
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Disclaimer:

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Not financial advice. I eat crayons. I support Chinese AI & the nation as a whole. Happy Chinese New Year (Gong Hei Fat Choi) This was not a sponsored article. We may buy or sell shares of Verses in the open market at any time. Fill disclaimer here: https://www.vhlamedia.com/terms-disclaimer

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