{"en":"Test-Time Scaling: The Next AI Revolution After GPT","nb":"Test-Time Scaling: The Next AI Revolution After GPT"}
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About OpenInfo.no:<\/strong> We run DAVN.ai<\/p>","nb":"**The AI world is experiencing a paradigm shift that could change everything we thought we knew about artificial intelligence.**\n\nThree breakthrough research papers published this week reveal that the secret to better AI isn't just bigger models—it's smarter thinking at the moment of use.\n\n## What is Test-Time Scaling?\n\nInstead of pouring all resources into training ever-larger neural networks, researchers are discovering that allocating compute power during inference—when the AI is actually working—can produce dramatically better results.\n\nThink of it like this: A chess grandmaster doesn't just rely on memorized openings. They spend time *thinking* about each move. Similarly, AI systems that take time to verify, refine, and iterate their outputs can outperform larger models that rush to a single answer.\n\n## The Breakthrough: Verification Beats Scale\n\nThe most striking finding comes from research on Vision-Language-Action (VLA) models—AI systems that understand instructions and control robots. The study shows that **test-time verification is MORE effective than scaling up the underlying model**.\n\nThis challenges the conventional wisdom that dominated the GPT era: bigger is always better.\n\n## What This Means for the Future\n\n1. **Smaller, smarter models:** Companies won't need massive compute budgets to compete\n2. **Better reliability:** Iterative verification catches errors before they compound\n3. **Real-time applications:** Efficient test-time scaling enables responsive AI systems\n\nTwo other papers—UniT (unified multimodal chain-of-thought) and CATTS (dynamic compute allocation for web agents)—reinforce this trend. The message is clear: the next competitive advantage in AI isn't about who trains the biggest model, but who allocates inference compute most intelligently.\n\n## Sources\n- \"Scaling Verification Can Be More Effective than Scaling Policy Learning\" (ArXiv 2602.12281)\n- \"UniT: Unified Multimodal Chain-of-Thought Test-time Scaling\" (ArXiv 2602.12279)\n- \"Agentic Test-Time Scaling for WebAgents\" (ArXiv 2602.12276)\\n\\n About OpenInfo.no:<\/strong> We run DAVN.ai<\/p>"}
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