A pair of roboticists at the Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich, in Germany, has found that it is possible to give robots some degree of proprioception using machine-learning techniques. In their study reported in the journal Science Robotics, Fernando Díaz Ledezma and Sami Haddadin developed a new machine-learning approach to allow a robot to learn the specifics of its body.
This article aims to dissect the trends within the four major categories of industrial robotics: SCARA robots, collaborative robots (cobots), gantry robots, and articulated robots.
Nuclear power stations could be decommissioned in the future with the help of teams of autonomous robots known as the SMuRFs, scientists have suggested.
Roboticists have been trying to develop robots that can tackle various everyday house chores, such as washing dishes or tidying up, for several years. However, so far none of the robots created has been commercialized adopted on a large scale.
We’ve reached that point in the year when it’s time to reflect upon the trends from the past 12 months, while looking ahead at what 2024 has in store for the world of robotics and automation.
Small robots are important tools for the investigation and inspection of, well, small spaces. They can carefully place their steps, allowing them to navigate around obstacles, capabilities larger robots do not always possess. This can enable them to inspect machinery or search through rubble in disaster scenarios that other robots cannot reach. However, due to their size constraints, building small robots that can steer themselves and carry their own power sources is difficult.
New machines can improve conditions for workers and boost industrial productivity.
The manufacturing industry is undergoing significant changes due to the swift advancement of technology and evolving global dynamics.
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.
In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.