Nature

Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability

Deep neural networks (DNNs) possess the capability to represent more complex nonlinear problems than shallow neural networks, and their distributed data learning method is more effective 1,2,3. The ...

In 1986, three scientists improved backpropagation, making neural networks learn effectively from data

A groundbreaking 1986 technique called backpropagation revolutionized artificial intelligence, enabling computers to learn ...
Outlookindia

How Will Decentralized AI Networks Integrate With MCP Compute Layers In Web3?

Artificial intelligence is evolving at an unprecedented rate, but its capabilities are still dominated by a few large organizations that control the central systems of AI. However, Web3 is also ...
Nature

Real-time 4K computer-generated hologram based on encoding conventional neural network with learned layered phase

Learning-based computer-generated hologram (CGH) demonstrates great potential for real-time high-quality holographic displays. However, real-time 4K CGH generation for 3D scenes remains a challenge ...
Nasdaq

How Blockchain Layers Work: Interview with Ankr’s Stanley Wu

Blockchain can be best described as a decentralized type of database that is used to maintain a growing list of records called blocks. Each block contains a list of transactions, a timestamp, and a ...