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AI models master capabilities long before exhibiting them, research shows
The post AI models master capabilities long before exhibiting them, research shows appeared on BitcoinEthereumNews.com. Artificial intelligence (AI) models possess some capabilities long before they exhibit them during training, new research has shown. According to the research carried out by Havard and the University of Michigan, the models do not showcase these abilities until they need to in one way or another. The research is one of the many that has been carried out to understand how AI models build their capabilities before showcasing them. The study analyzed how AI models learn basic concepts like size and color, revealing they master the skills earlier than most tests suggest. The study also provided insight into the complexity of measuring an AI’s capabilities. “A model might appear incompetent when given standard prompts while actually possessing sophisticated abilities that only emerge under specific conditions,” the paper reads. Research shows AI models internalize concepts Havard and the University of Michigan are not the first to try to understand AI model capabilities, with researchers at Anthropic unveiling a paper titled ‘dictionary learning’. The paper discussed mapping out connections in their Claude language to specific concepts it understands. Although most of these researches took different angles, it is primarily to understand the AI models. Anthropic revealed it found features that could be tied to different interpretable concepts. “We found millions of features which appear to correspond to interpretable concepts ranging from concrete objects like people, countries, and famous buildings to abstract ideas like emotions, writing styles, and reasoning steps,” the research revealed. During its research, the researchers carried out several experiments using the diffusion model, one of the most popular architectures for AI. During the experiment, they realized the models had distinct ways to manipulate basic concepts. The patterns were consistent as the AI models showed new capabilities in different phases and a sharp transition point signaling when a new ability…
The post AI models master capabilities long before exhibiting them, research shows appeared on BitcoinEthereumNews.com.
Artificial intelligence (AI) models possess some capabilities long before they exhibit them during training, new research has shown. According to the research carried out by Havard and the University of Michigan, the models do not showcase these abilities until they need to in one way or another. The research is one of the many that has been carried out to understand how AI models build their capabilities before showcasing them. The study analyzed how AI models learn basic concepts like size and color, revealing they master the skills earlier than most tests suggest. The study also provided insight into the complexity of measuring an AI’s capabilities. “A model might appear incompetent when given standard prompts while actually possessing sophisticated abilities that only emerge under specific conditions,” the paper reads. Research shows AI models internalize concepts Havard and the University of Michigan are not the first to try to understand AI model capabilities, with researchers at Anthropic unveiling a paper titled ‘dictionary learning’. The paper discussed mapping out connections in their Claude language to specific concepts it understands. Although most of these researches took different angles, it is primarily to understand the AI models. Anthropic revealed it found features that could be tied to different interpretable concepts. “We found millions of features which appear to correspond to interpretable concepts ranging from concrete objects like people, countries, and famous buildings to abstract ideas like emotions, writing styles, and reasoning steps,” the research revealed. During its research, the researchers carried out several experiments using the diffusion model, one of the most popular architectures for AI. During the experiment, they realized the models had distinct ways to manipulate basic concepts. The patterns were consistent as the AI models showed new capabilities in different phases and a sharp transition point signaling when a new ability…
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