🐈‍⬛ Edge#216: DeepMind’s New Super Model can Generalize Across Multiple Tasks on Different Domains

Gato is able to master tasks such as image classification, question answering or controlling a robotic arm

On Thursdays, we dive deep into one of the freshest research papers or technology frameworks that is worth your attention. Our goal is to keep you up to date with new developments in AI to complement the concepts we debate in other editions of our newsletter.

💥 What’s New in AI: DeepMind’s New Super Model can Generalize Across Multiple Tasks on Different Domains

Most deep learning models specialize in mastering a single task in a single domain. Recently, we have seen the emergence of multi-task models in single domains, such as transformers like GPT-3 in the language space. We have also seen models like OpenAI’s Dall-E that can combine knowledge from different domains to master a single task. However, having a single model mastering multiple tasks across heterogenous domains remains an elusive goal for deep learning. DeepMind is known for taking some of the toughest challenges in AI – with their new research, they have set their eyes on neural network architectures that can generalize across tasks and domains. What they came up with is fascinating!