Understand the merits of large language models vs. small language models, and why knowledge graphs are the missing piece in ...

Embrace city science as a vital partner in architecture, merging creativity with data to build resilient and equitable urban ...

Recently, researchers introduced a new representation learning framework that integrates causal inference with graph neural networks—CauSkelNet, which can be used to model the causal relationships and ...

Recently, Jiangxing Intelligent collaborated with Professor Zhu Yifei's team from Shanghai Jiao Tong University to achieve significant progress in the field of compound large language model systems.

The compounds that emerge aren't just theoretical curiosities. They're synthesised and tested, and one targeting fibrosis ...

Oracle's current P/E ratio of 75x is 143% above its five-year average, signaling overvaluation. Click here to find out why ...

For the last few years, chain-of-thought prompting has become the central method for reasoning in large language models. By encouraging models to “think aloud,” researchers found that step-by-step ...

Abstract: Decision-making of autonomous driving is challenging due to high-density traffic and complex road environment. Based on vehicle to vehicle (V2V) communication, collaborative decision-making ...

Link technologies in today’s data center networks impose a fundamental trade-off between reach, power, and reliability. Copper links are power-efficient and reliable but have very limited reach (2 m).