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Tech giant Alphabet, which is Google’s parent company, has launched its latest robotics venture after years of limited success in the sector.
Google parent company Alphabet has launched a new subsidiary, Intrinsic, which will focus on building software for industrial robots.
Intrinsic will be one of Alphabet’s ‘other bets’ and will be linked to its ‘moonshots’ research and development segment, X.
Other forward-looking tech projects that have emerged from this unit include self-driving car business Waymo, delivery drone service Wing, and healthcare and biotech-focused Verily.
Intrinsic will focus on developing software tools to make industrial robots easier to use, cheaper and more flexible, with a view to expanding the reach of consumers using them.
The new subsidiary’s CEO, Wendy Tan-White, wrote in a blog post that Intrinsic would work to unlock “the creative and economic potential” of industrial robotics for businesses, as well as making them more accessible.
Alphabet has long harboured ambitions in the robotics sector, but to date has had limited success. It has acquired a number of robotics start-ups that have gone on to be sold or shut down. This includes robotics design giant Boston Dynamics, which Alphabet snapped up in 2013 but offloaded four years later.
The company is still on the lookout for its next big tech venture outside its core Google business. Since its launch in 2010, X has invested in ambitious but costly tech projects. This includes internet balloon business Loon, which was shut down last year as the path to commercial viability proved “much longer and riskier than hoped”.
While Alphabet ended 2020 with $41.2bn in operating income, its R&D-intensive ‘other bets’ division lost $4.5bn.
According to Tan-White, the X team has been testing and researching the technology for Intrinsic for several years and it is now “ready to become an independent Alphabet company”.
“Over the last few years, our team has been exploring how to give industrial robots the ability to sense, learn and automatically make adjustments as they’re completing tasks, so they work in a wider range of settings and applications,” she added.
“Working in collaboration with teams across Alphabet, and with our partners in real-world manufacturing settings, we’ve been testing software that uses techniques like automated perception, deep learning, reinforcement learning, motion planning, simulation and force control.”
