OpenAI officially introduced DALL-E, a 12-billion-parameter version of the GPT-3 Transformer trained to synthesize realistic digital images directly from written text prompts. Crucially, they released CLIP (Contrastive Language-Image Pre-training), a neural network that learned visual… Read More »The Launch of DALL-E 1 and CLIP
OpenAI officially released GPT-3, a massive autoregressive language model trained with an unprecedented 175 billion parameters. By scaling the Transformer architecture to hyper-scale data corpora, GPT-3 displayed startling few-shot learning capabilities, writing code, composing poetry,… Read More »The Launch of GPT-3 and the Era of LLM Scale
Alec Radford and the OpenAI team trained GPT-2, a 1.5-billion-parameter Transformer language model scaled on WebText (a dataset of 45 gigabytes of high-quality internet text scraping). In a historic corporate move, OpenAI initially refused to… Read More »The Launch of GPT-2 and the Staged Release Debate
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova of Google introduced BERT. By pioneering masked language modeling to train deep bidirectional Transformer layers on the entire English Wikipedia and BooksCorpus, BERT shattered eleven natural… Read More »The Deployment of BERT (Bidirectional Encoder Representations from Transformers)
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin of Google Brain published the seminal paper Attention Is All You Need. By completely eliminating recurrent and… Read More »The Invention of the Transformer Architecture (Attention Is All You Need)
DeepMind’s AlphaGo supercomputer faced 18-time world Go champion Lee Sedol in Seoul, South Korea, achieving a historic 4-1 victory in a five-game match watched by 280 million people. Operating across a distributed cloud network of… Read More »The AlphaGo Victory Over Lee Sedol
Google open-sourced TensorFlow, its highly proprietary, production-grade deep learning framework. Engineered with native support for multi-GPU acceleration and distributed cloud orchestration, this framework rapidly became the dominant software operating system for deep learning globally, unifying… Read More »The Launch of TensorFlow Open-Source Framework
Ian Goodfellow and his research colleagues at the Université de Montréal published a seminal paper introducing the GAN architecture. By pitting two neural networks against each other in a zero-sum game—a Generator attempting to synthesize… Read More »The Invention of Generative Adversarial Networks (GANs)
Tomas Mikolov and his team at Google published a landmark paper introducing the Word2Vec architecture. By training shallow two-layer neural networks (Continuous Bag-of-Words and Skip-gram) on massive text corpora, they proved that human words could… Read More »The Invention of Word2Vec (Word Embeddings)
Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton deployed AlexNet, a deep convolutional neural network (CNN), in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). By utilizing two NVIDIA GeForce GTX 580 GPUs to train an… Read More »The AlexNet ImageNet Triumph