Google reveals new AI model that can adapt to new situations

US-based global tech firm Google has introduced a new artificial intelligence (AI) model that translates vision and language for robots to perform certain actions.

"Unlike chatbots, robots need 'grounding' in the real world and their abilities," the company said on Friday, adding that RT-2 will provide knowledge for a robot that can complete tasks such as picking up apples or throwing out the trash.

"In other words, with RT-2, robots are able to learn more like we do — transferring learned concepts to new situations. Not only does RT-2 show how advances in AI are cascading rapidly into robotics, it shows enormous promise for more general-purpose robots," it added.

Robotics Transformer 2, or RT-2, is a vision-language-action model trained on text and images from the internet, which can learn general ideas and concepts and then transfer that knowledge to inform a robot's behavior, Google said in a blog post.

RT-2 can enable a single model to perform complex reasoning, and provide output robot actions, in addition to transferring concepts to direct a robot's actions, it added.

RoboCat

In June, Google introduced a self-improving AI agent for robotics called RoboCat, saying it can learn to perform a variety of tasks across different arms and then self-generates new training data to improve its technique.

While RoboCat can pick up a new task with as few as 100 demonstrations by drawing from a large and diverse dataset, Google said this capability will help accelerate robotics research since it reduces the need for human-supervised training, dubbing it an important step towards creating a general-purpose robot.

AI's potential risks

While discussing the potential benefits of AI, it is also important to consider the risks.

These include job displacement, bias, lack of transparency, privacy and security concerns, ethical considerations, and potential superintelligence.

To mitigate these risks, robust AI governance, research for safety, international collaboration on regulations, and a focus on transparency, fairness, and accountability in AI development are essential.

However in addition to tech companies' hesitation to inspect their innovations' global social impacts, the lack of institutions to investigate and approach to the AI's impact from the ethical, social and psychological perspectives attracts attention.