The world of AI and Robotics is constantly evolving, with new advancements and innovations being made every day. Google DeepMind has introduced a new AI model called RT-2 that translates vision and language into robotic actions. RT-2 is a vision-language-action (VLA) model that can directly output robotic actions, trained on text and images from the web, allowing it to transfer knowledge from web data to inform robot behaviour. This significant advancement in robotics brings us closer to a future of helpful robots that can handle complex, abstract tasks in highly variable environments.
The pursuit of helpful robots has always been challenging, as robots need to handle real-world challenges and complex tasks in environments they’ve never seen before. RT-2 addresses this by enabling a single model to perform complex reasoning and output robot actions, removing the complexity of previous systems that relied on high-level reasoning and low-level manipulation systems playing an imperfect game of telephone. RT-2’s ability to transfer information to actions shows promise for robots to more rapidly adapt to novel situations and tasks, functioning as well as previous models on tasks in their training data and almost doubling their performance on novel, unseen scenarios.
Another exciting development is the emergence of a generally agreed-upon “next big thing” in AI beyond deep learning. According to Rodney Brooks, this is likely to be something that someone is already working on, with published papers about it, suggesting that there is still a tremendous amount of work to be done to enable helpful robots in human-centred environments.
AI is also transforming the global economy, affecting almost 40 percent of jobs around the world. While AI has the potential to replace some jobs, it also has the potential to complement others, leading to a disproportionate increase in labour income for higher-income workers. However, this could also exacerbate inequality, as gains in productivity from firms that adopt AI will likely boost capital returns, which may also favour high earners.
To ensure that AI benefits humanity, policymakers must proactively address the potential negative impacts of AI on the labour market. This includes establishing comprehensive social safety nets and offering retraining programs for vulnerable workers. By doing so, we can make the AI transition more inclusive, protecting livelihoods and curbing inequality.
In conclusion, the world of AI and Robotics is constantly evolving, with new advancements and innovations being made every day. From Google DeepMind’s RT-2 to the emergence of the “next big thing” in AI beyond deep learning, the future of robotics is bright. However, it is crucial for policymakers to address the potential negative impacts of AI on the labour market to ensure that it benefits humanity as a whole.