Artificial intelligence (AI) is shaking things up across all kinds of industries, sparking some serious innovation and making waves in ways we never thought possible. One of the main reasons AI is so powerful is its ability to learn from data—a process called training. Traditionally, AI models have been designed to gradually build on what they already know. But now, new research is showing that “selective forgetting” (yes, like how we humans forget things) could actually make AI even better at what it does. Quanta Magazine brought this topic to our attention in their article, “How Selective Forgetting Can Help AI Learn Better.“
So, what’s selective forgetting in AI? It’s when AI adjusts how much it “remembers” past experiences while it’s learning new stuff. By mimicking how our brains handle memory, AI models can continuously learn, stay flexible and avoid something called catastrophic forgetting (which is when an AI basically forgets everything it knew after learning something new). As this research moves forward, selective forgetting could take AI to the next level—making it smarter, faster and more adaptable.
At Access Innovations, we blend our know-how in information science, scholarly publishing and AI to help you get the most out of these cutting-edge AI tools. With a mix of techniques, we work to enhance your data and train AI models that give you the best possible results.
Melody K. Smith
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