Blog

Research

Active offline policy selection

To make RL more applicable to real-world applications like robotics, we propose using an intelligent evaluation procedure to select the policy for deployment, called active offline policy...

Research

Tackling multiple tasks with a single visual language model

We introduce Flamingo, a single visual language model (VLM) that sets a new state of the art in few-shot learning on a wide range of open-ended multimodal tasks.

Research

DeepMind’s latest research at ICLR 2022

Beyond supporting the event as sponsors and regular workshop organisers, our research teams are presenting 29 papers, including 10 collaborations this year. Here’s a brief glimpse into our...

Research

An empirical analysis of compute-optimal large language model training

We ask the question: “What is the optimal model size and number of training tokens for a given compute budget?” To answer this question, we train models of various sizes and with various numbers...

Research

GopherCite: Teaching language models to support answers with verified quotes

Language models like Gopher can “hallucinate” facts that appear plausible but are actually fake. Those who are familiar with this problem know to do their own fact-checking, rather than trusting...

Research

Predicting the past with Ithaca

The birth of human writing marked the dawn of History and is crucial to our understanding of past civilisations and the world we live in today. For example, more than 2,500 years ago, the Greeks...

Research

Learning Robust Real-Time Cultural Transmission without Human Data

In this work, we use deep reinforcement learning to generate artificial agents capable of test-time cultural transmission. Once trained, our agents can infer and recall navigational knowledge...

Research

Probing Image-Language Transformers for Verb Understanding

Multimodal Image-Language transformers have achieved impressive results on a variety of tasks that rely on fine-tuning (e.g., visual question answering and image retrieval). We are interested in...

Research

Red Teaming Language Models with Language Models

In our recent paper, we show that it is possible to automatically find inputs that elicit harmful text from language models by generating inputs using language models themselves. Our approach...

Research

Spurious normativity enhances learning of compliance and enforcement behavior in artificial agents

In our recent paper we explore how multi-agent deep reinforcement learning can serve as a model of complex social interactions, like the formation of social norms. This new class of models could...

Research

Simulating matter on the quantum scale with AI

Solving some of the major challenges of the 21st Century, such as producing clean electricity or developing high temperature superconductors, will require us to design new materials with specific...

Research

Improving language models by retrieving from trillions of tokens

We explore an alternate path for improving language models: we augment transformers with retrieval over a database of text passages including web pages, books, news and code. We call our method...