The big question is whether OpenAI has now surpassed DeepMind, which rose to fame in 2016 when it produced AlphaGo software that learned how to play the board game Go and grew better than any human player.
Instead, DeepMind has been focusing on proof-of-concept where its agents have beaten humans at very complex games using reinforcement learning techniques, including AlphaGo.
This way, the company is working on building more commercially-applications AI by using a state-of-the-art baseline for Deep Reinforcement Learning algorithms.
OpenAI’s third generation of Generative Pre-Training Transformer (GPT-3) can be used by businesses in finishing human tasks, making it the most coherent language model.
Comparatively DeepMind’s AI doesn’t have many practical applications yet in day to day business operations, but only in niche areas.
As the years go by, Google may probably produce groundbreaking applications using Deep Reinforcement Learning (RL) that DeepMind possesses.
In terms of research, both companies deal with Deep RL and have a similar approach to advancing artificial intelligence.
While it has been focusing on improving Google’s language models till now, DeepMind is now also powering AI agents to perceive dynamic real-world environments, as suggested in a new paper titled AlignNet: Unsupervised Entity Alignment.