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Seminal Research in the Evolution of Artificial Intelligence

ImageNet Classification with Deep Convolutional Neural Networks (Krizhevsky et al., 2012)

Playing Atari with Deep Reinforcement Learning (Mnih et al., 2013)

Deep Residual Learning for Image Recognition (He et al., 2015)

Mastering the Game of Go with Deep Neural Networks and Tree Search (Silver et al., 2016)

Attention Is All You Need (Vaswani et al., 2017)

DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter (Sanh et al., 2019)

A Path Towards Autonomous Machine Intelligence (Yan LeCunn 2022)

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning (Daya Guo et., al 2025)

DeepSeek-V2: A Strong, Economical and Efficient Mixture-of-Experts Language Model (Daya Guo et., al 2025)

General Topics in Artificial Intelligence

Ant Group’s use of China-made GPUs, not Nvidia, cuts AI model training costs by 20%

Sam Altman On AGI and Superintelligence in 2025

MIT's Technology Review: What’s next for AI in 2025?