Gemini 1.0 Ultra launches in Gemini Advanced
Google makes Gemini 1.0 Ultra available through Gemini Advanced, moving the largest Gemini 1.0 model from announcement to a consumer product.
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Google releases the Gemini 1.0 family
Google introduces the natively multimodal Gemini 1.0 family—Ultra, Pro and Nano—with Pro and Nano entering products immediately and developer APIs following a week later.
Google launches PaLM 2 across more than 25 products and features
PaLM 2 emphasized multilingual, reasoning, and coding capabilities and launched across Bard, Workspace, Google Cloud, and other products.
Google opens limited testing for MusicLM
Google opened an AI Test Kitchen waitlist for MusicLM, allowing selected users to generate music from text descriptions and provide feedback.
Google releases open Flan-T5 checkpoints
Google instruction-tuned the T5 family on 1,836 tasks and released five checkpoints ranging from 80 million to 11 billion parameters.
Google Research announces Imagen
Google Research announces Imagen, a text-to-image diffusion model focused on photorealism and language understanding; its code and public demo were not released at launch.
DeepMind introduces the Flamingo visual language model
DeepMind introduced Flamingo, an 80-billion-parameter visual language model that used a few examples to handle image, video, and text tasks.
Google publishes the 540B-parameter PaLM
Google presents a 540B-parameter dense language model trained with Pathways; the initial release is a research disclosure, without public weights or a general-purpose API.
Google DeepMind releases Chinchilla
Google DeepMind releases a model and scaling-law result arguing that parameter count and training data should grow in proportion.
DeepMind introduces the competitive programming system AlphaCode
DeepMind introduced the code-generation system AlphaCode, which performed at about the median level of participants in Codeforces competitions.
Google publishes the LaMDA research paper
The paper documents LaMDA as a dialogue-focused model family with up to 137B parameters and examines response quality, safety and factual grounding.
DeepMind introduces the 280-billion-parameter Gopher language model
DeepMind introduced Gopher, a 280-billion-parameter language model, and published research on its capabilities, limitations, and risks without releasing public weights or an API.
Google first introduces LaMDA
Google introduces LaMDA for open-domain dialogue at I/O 2021; the model remains an internal research system without public weights or a general-purpose API.
Google publishes Switch Transformer, scaling a sparse model to 1.6T parameters
Switch Transformer routed each token to a single expert, scaling total sparse parameters to about 1.6 trillion without activating the full model for every token.
GShard paper demonstrates a sparse-expert translation model with more than 600B parameters
Google researchers introduce GShard automatic sharding and use it to train a multilingual translation MoE with more than 600B total parameters on 2,048 TPU v3 accelerators.
Google Research introduces the open-domain conversational model Meena
Google Research introduced the 2.6-billion-parameter open-domain conversational model Meena but did not release an external demo or model weights.
Google publishes T5 and releases models, code, and C4
T5 cast a wide range of natural-language-processing tasks into a text-to-text format and released a model family ranging from 60 million to 11 billion parameters.
XLNet paper and XLNet-Large weights are released
Researchers from Google Brain and Carnegie Mellon University introduce XLNet and release the XLNet-Large checkpoint with TensorFlow code.
Google publishes BERT and releases pretrained models
BERT unified many language-understanding tasks around a bidirectional Transformer encoder, followed by a release of code and pretrained checkpoints.
Google researchers publish the Transformer paper
The paper introduced an encoder–decoder architecture built entirely on attention, replacing recurrent computation with parallelizable self-attention.