The statistics highlight a significant shift in the AI landscape. In 2024, Hugging Face developed an open-source platform for AI robots, amassing over 3,500 robot data sets. This platform attracts thousands of participants from every continent, engaging in large-scale hackathons. Raspberry Pi, a key player in the maker movement, went public on the London Stock Exchange with a valuation of $700 million. The resurgence of Maker Faire events is notable, with the most recent gathering nearly 30,000 attendees. This year, over 100 Maker Faires are scheduled worldwide. Studies demonstrate that hands-on creativity, a core aspect of the maker movement, reduces anxiety, combats loneliness, and boosts cognitive function. These statistics underscore the growing influence and potential of open-source AI and the maker movement in shaping a more inclusive and innovative future.
NVIDIA Robotics
@NVIDIARobotics
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Jun 16 Training data collection is one of the biggest challenges in #Robotics. We’re solving it with #NVIDIAIsaac GR00T-Dreams.
By using #NVIDIACosmos world foundation models and generative AI, developers can create vast, realistic synthetic data at scale.
Benefits:
Cheaper &
AgileX Robotics
@AgilexRobotics
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Apr 30 your one-stop for embodied AI! Manage your entire data lifecycle—collection, cleaning, annotation & deployment—in one platform. Tap into free & custom datasets and plug-and-play support for ACT, RDT & Diffusion Policy. Say goodbye to infra headaches. http://global.agilex.ai #AI
ALLDEX
@alldexone
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Jun 3 From auxiliary technology to core economic infrastructure, the robotics and #AI industry is reshaping productivity, innovation, labor structures, and the global competitive order—where advantage no longer lies in the quantity of human labor, but in the speed of learning and
Aish
@aish_caliperce
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23h Bob McGrew (Head of Reserach OpenAI) explains why Robotics is finally having its breakthrough moment after years of being too early.
OpenAI spent years teaching a single robot to solve just one task – manipulating a Rubik’s cube. This narrow focus required massive time
vitrupo
@vitrupo
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May 24 DeepMind’s Carolina Parada says Asimov’s Three Laws aren’t enough to keep robots safe.
Her team built the Asimov Dataset, a growing set of safety priors, extracted by AI and refined by humans.
Robots don’t follow rules. They learn to reason about harm.
Aish
@aish_caliperce
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23h Bob McGrew (Head of Research OpenAI) explains why proprietary data no longer provides companies with a competitive advantage in the AI era.
Finance companies once believed their years of accumulated data would give them an edge. They planned to train specialized models on top of
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