Internsec aims to advance the field of artificial intelligence for industrial robotics on a large scale. Even small businesses should be able to easily integrate robotic technology into their operations in the future – even if individual activities require complex sensory perception and thus actual human labor so far.
Alphabet, the parent company of Google, founded Intrinsic, which specializes in industrial robotics software. A subsidiary of X, Internsec is an Alphabet incubator for particularly promising and often high-risk projects.
According to her own statements, Intrinsic President Wendy Tan White wants to use her new company “to tap into the creative and economic potential of industrial robots for millions of companies, founders and developers.”
“Professional programmers can spend hundreds of hours programming robots to perform specific tasks such as welding two pieces of metal or gluing an electronic package together,” Tan White wrote.
Complex tasks such as plugging in sockets or laying cables are currently useless for robots because they lack the sensors or software needed to understand their environment. The core wants to change that.
Artificial intelligence is the focus of Intersec
Like its sister company Google, Intrinsic Artificial intelligence Up front: The company’s bot software uses technologies from the areas of automatic perception, deep learning, reconfigurable learning, motion planning, simulation, and robotic force control.
“Over the past few years, our team has been researching how industrial robots can automatically recognize, learn and adapt when things are done so that they can operate in a broader range of environments and applications,” Tan White wrote.
According to Tan White, Intrinsic’s technological foundations have been laid under the guise of X over the past five and a half years. Now the company is ready to take the step towards independence.
Two hours of AI training instead of hundreds of hours of coding work
Tan White describes a project in which a robot with force sensors learned in two hours to connect three different types of power cables to a circuit board. Otherwise, this task would have meant “hundreds of hours” of programming work.
Another example shows robot arms that learned by training AI and using sensor data to assemble a simple piece of furniture.
Tan White writes that such challenging tasks for robots are not realistic or affordable to automate. There are “millions of such examples in the business world”. Intersec’s AI software can “dramatically reduce” the time, costs and complexity of using industrial robots, help solve more problems and increase the diversity of manufacturable goods.
Tan White describes the fact that more companies can hire machines rather than people as an environmental and economic advantage: Currently, ten countries produce 70 percent of the world’s goods, which increases emissions for transportation. In addition, there will be 2.1 million job openings in industrial manufacturing in the United States alone in 2030.
In recent years, Google’s AI department has repeatedly demonstrated projects in which machine learning should improve the performance of robots in everyday life, for example Service and care robots or by Dog robots only learn to walk from videos. Google also supplied one with Robel Standard for simulation-trained robots Before.
those: X . Blog
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