New AI Splits Into Multiple Minds to Boost Its Intelligence (Parallel Thinking)

Tencent just unveiled Parallel R1, an AI system that doesn’t just think faster or bigger — it literally splits into multiple reasoning paths before deciding on the best answer. Inspired by how humans explore different options in their heads, Parallel R1 uses reinforcement learning to master “parallel thinking,” and the results are shocking. Accuracy on elite math benchmarks jumped by over 40%, and researchers say the AI even learned to double check itself without being told. This could be the first step toward machines reasoning in ways that feel disturbingly human.

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🦾 What You’ll See:
• Tencent Parallel R1 explained and how it learned parallel thinking
https://arxiv.org/pdf/2509.07980
• Why reinforcement learning made this system reason like humans
• Benchmark jumps including a 43% leap on AIME 25
• How parallel thinking evolved during training and changed the AI’s style
• Why splitting into multiple minds could reshape AI research
• The unsettling implications of machines adopting human-like reasoning

⚡ Why It Matters:
AI is no longer just scaling in size — it’s scaling in how it thinks. Parallel R1 proves models can be trained to reason smarter, not just bigger, and it raises unsettling questions about what happens when machines start using strategies that feel all too human.

#ai #aitools #tencent