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Researchers hypothesize that a powerful type of AI model known as a transformer could be implemented in the brain through networks of neuron and astrocyte cells. The work could offer insights into how the brain works and help scientists understand why transformers are so effective at machine-learning tasks.
A deep dive into Transformer a neural network architecture that was introduced in the famous paper “attention is all you need” in 2017, its applications, impacts, challenges and future directions
Apple Slays the AI Game: Unwrapping the Cornucopia of AI Marvels at WWDC 2023, Technology & Science News, Times Now
MIT researchers have explained how large language models like GPT-3 are able to learn new tasks without updating their parameters, despite not being trained to perform those tasks. They found that these large language models write smaller linear models inside their hidden layers, which the large models can train to complete a new task using simple learning algorithms.
South Korea: A newly developed "transformer"-based DL (deep learning) model may help cardiologists accurately diagnose plaque erosion in patients with acute coronary syndromes (ACS), according to a...