Google’s new neural-net LLM architecture separates memory components to control exploding costs of capacity and compute
Titans architecture complements attention layers with neural memory modules that select bits of information worth saving in the long term.
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Rat vision: A lesson in visual object recognition for AI
Rats perceive the world with a complexity that modern artificial neural networks struggle to match. This is the finding of a ...
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Liquid AI’s LFMs Outshine GPTs: All You Need to Know
Explore if MIT’s spinoff Liquid AI can deliver on its promise to build a new type of AI in 2025. Learn more about its ...
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Beyond Transformers: New AI Architectures Could Revolutionize Large Language Models
Two new neural network designs promise to make AI models more adaptable and efficient, potentially changing how artificial ...
What is a Neural Network?
Neural networks have revolutionized the fields of artificial intelligence (AI) and machine learning by providing a flexible, ...
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MicroCloud Hologram Inc. Develops Quantum Algorithm Technology for Deep Convolutional Neural Network Exchange Submissions
MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, have developed a quantum algorithm technology for deep convolutional neural network (CNN) exchange ...
Nvidia’s DLSS 4 is so much more than just ‘fake frames’
Here's what you need to know about DLSS 4 and Multi Frame Generation, a key addition to Nvidia's GeForce RTX 50-series.
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MicroCloud Hologram Inc. Develops Quantum Algorithm Technology for Deep Convolutional Neural Network Exchange Submissions
the architecture of the QCNN significantly improves computational efficiency in both forward and backward propagation, providing strong support for the training process of deep neural networks.