How Grok Outpaced r1 and o1 in Real-Time Reasoning

Plus: Quantum Breakthrough, Google Shake-Up, and the AI Song Everyone’s Talking About

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Speed is key in intelligence—see how Grok left r1 and o1 behind in real-time reasoning.

This issue also explores THE quantum computing milestone, Google’s possible shake-up, and the must-listen AI song. The quality is getting insane.

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DeepSeek’s R1-Lite—China’s answer to OpenAI’s o1

First OpenAI’s o1, now DeepSeek’s R1—the AI reasoning race is heating up.

Chinese AI firm DeepSeek just launched R1-Lite-Preview, a reasoning model that rivals OpenAI’s o1 and offers a transparent, real-time chain-of-thought (CoT) process.

Unlike o1’s condensed summaries, R1-Lite-Preview lets you peek into its full reasoning as it happens.

It shares even its feelings 😄 

I tested it with a tough math riddle:

“Three positive integers form a geometric sequence. Their sum is 91, and their product is 1,365. What are the numbers?”

R1-Lite-Preview took over two minutes, sharing an extensive (and sometimes amusing) internal dialogue. It even admitted, “This is frustrating.” 

In the end, it couldn’t solve the problem.

OpenAI’s own reasoning model also couldn’t. And Google’s Gemini? Forget it.

Surprisingly, Elon Musk’s Grok 2 nailed it quickly, giving the correct answer: 7, 21, and 63. The comparison video:

Why it matters

DeepSeek’s advancement shows how rapidly AI reasoning is evolving globally. With an estimated 50,000 H100 chips, they’re matching Western AI labs in compute power.

By open-sourcing R1, DeepSeek accelerates innovation across the AI industry, challenging closed US AI labs.

As reasoning models become widespread, the competition isn’t just about intelligence—it’s about speed.

Inference latency is the new battleground.

In a world where powerful reasoning models are accessible to all, the edge goes to those who can think and act faster!

The AI arms race is shifting from who thinks best to who thinks best, but fastest.

AlphaQubit: DeepMind’s Quantum Error Correction Breakthrough

Google DeepMind’s AlphaQubit is revolutionizing quantum computing by improving error correction accuracy using AI.

Qubits, the building blocks of quantum computers, are highly sensitive to noise, requiring error correction to ensure reliability.

AlphaQubit employs GPTs (it’s basically a language model) to predict and correct errors better than traditional methods. Tested on Google’s Sycamore processor, it achieved:

  • 6% fewer errors than tensor networks.

  • 30% fewer errors than correlated matching.

While AlphaQubit excels, challenges include real-time speed improvements and scalability to millions of qubits.

Why it matters: This innovation brings quantum computing closer to real-world impact, enabling, e.g., drug discovery and material science breakthroughs.

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DOJ Eyes Google’s Search Dominance—What’s Next for Chrome?

The U.S. Department of Justice (DOJ) is intensifying its antitrust scrutiny of Google’s search monopoly.

While there’s no official mandate yet, industry chatter suggests that Google might be pressured to separate its Chrome browser to level the playing field.

Speculation is rife about who could acquire Chrome if it becomes available.

OpenAI’s name has surfaced, though no concrete evidence of their interest exists. Tech giants like Microsoft, Amazon, Apple, and Meta could also be interested.

A new owner for Chrome would accelerate AI integration. Exciting times ahead.

ChatGPT “Creative Writing“ Mode + Suno AI = Absolute Banger

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That’s a wrap! I hope you enjoyed it.

Martin

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