The Norwegian robot company 1X has launched the new humanoid robot Neo Gamma designed for home use. Neo Gamma was created to enhance human-robot interaction and is designed to replace its predecessor, Neo Beta. Equipped with abilities to better adapt to home environments and perform various tasks, Neo Gamma is set to assist people in homes, making life easier according to company officials. In the promotional video released by 1X, Neo Gamma is shown making coffee, doing laundry, cleaning the house with a vacuum cleaner, and fetching requested items from one place to deliver them to another. TESTING PHASE CONTINUES It is emphasized that the Neo Gamma model is a prototype developed for testing in home environments. The company mentions that their humanoid robot is still far from commercial scaling and distribution. COMING DRESSED As part of making Neo Gamma appear friendly as a humanoid robot, the company seems to have put in extra effort. It is noted that special attention was paid during the robot’s design process to ensure it does not look threatening. As part of this, Neo Gamma is dressed in a knitted nylon outfit. It was also revealed that serious time was spent on safety tests to make sure the robot is highly reliable in human interactions besides its appearance. THE ONLY COMPANY FOCUSING ON HOMES While companies like Agility, Apptronik, Boston Dynamics, Tesla, and Figure that work on humanoid robots primarily focus on industrial deployment despite training their robotic systems in lab-created home environments. What sets 1X apart from its competitors is their dedicated focus on humanoid robots meant to work in home settings. The Norwegian company is determined to be the winning firm in getting humanoid home assistant robots ready for sale. WILL WE SEE THEM SOON? Tesla plans to release its humanoid robot Optimus in 2025. According to industry leaks, Apple plans to start mass production in 2028. However, experts are skeptical about these timeframes. Many robotic engineers believe that there are still many years needed for training current prototypes, and their high costs may lead to low profitability. Therefore, they believe it will take 5-10 years for technology to reach an adequate level and for correct scaling.