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New research indicates that artificial intelligence (AI) is starting to 'think' in a manner similar to humans, moving beyond just high accuracy in tasks. The focus is shifting towards understanding how AI makes decisions, aiming to reduce 'hallucinations' in AI models. RTNet, developed by researchers at Georgia Tech University, is a significant step towards aligning AI decision-making with human cognitive processes.
RTNet enhances convolutional networks by incorporating traditional cognitive models from neuroscience, combining image-processing capabilities with human-like stochastic reasoning. The network processes images multiple times using samples from a Bayesian neural network, simulating the human brain's decision-making process. The study emphasizes the importance of evidence accumulation and empirical validation in AI models to mirror human thinking effectively.
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Sam Altman today revealed that OpenAI will release an open weight artificial intelligence model in the coming months. "We are excited to release a powerful new open-weight language model with reasoning in the coming months," Altman wrote on X.
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