Meta AI Is Working at the Intersection of Robotics and Generative AI
By Adam Pease
Meta AI Is Working at the Intersection of Robotics and Generative AI
In collaboration with the University of Washington, Meta’s AI division has released a new technology framework that helps robots learn through generative models. The new research represents another example of how the emerging generative content market can help power up a variety of use cases.
Text-to-Image Powers Up Robotics
In the past year, generative image creation models have sailed into the mainstream through the popularity of tools like OpenAI’s Dalle-2 and Stability AI’s Stable Diffusion.
With these tools, artists, marketers, and other creative professionals have leveraged AI to generate images from nothing but text. So far, however, these tools have not seen widespread applications outside of visual content generation.
Meta’s new framework for data augmentation for AI robotics suggests this might be changing. In the context of robotics, data augmentation refers to the practice of introducing edits and variation into the data that robots learn from to optimize the training process.
Meta’s new tool, called GenAug, generates augmented versions of images from robot training data that greatly increase the variation of the data by, for example, changing the background between a variety of realistic settings.
Meta’s and the Generative Content Market
Meta’s approach with GenAug shows promise, and demonstrates the widespread potential generative content has to disrupt an unexpected variety of different markets. Robots trained on the GenAug data performed significantly better than those trained on the original, non-augmented data. In particular, those trained on the richer dataset could generalize their behaviors to more contexts.
Optimizing the training process by augmenting data is just one way that generative content can transform sectors like robotics. The market is expanding, and Meta has its eye on the pulse. Mark Zuckerberg has framed generative AI as a critical element of the overall vision for the metaverse, promising the ability for users to quickly create custom content just by speaking.
Meanwhile, its AI researchers are at work on a variety of models for generating images, videos, and more, which we expect to come to market in the near future.
Bottom Line
Meta’s new research into data augmentation shows a promising path forward for improving the generality of practical robotics. Moreover, it suggests that generative content act as a force multiplier in a diverse set of unexpected contexts. Stories like these suggest to us that the market will continue to expand rapidly as new areas of application are found.
Learn how to leverage the latest AI tools in our upcoming webinar!
See Adam LIVE on Tuesday, February 28, 2023 at 10 AM PT / 1 PM ET!
Leverage the Latest Generative Content Tools and Trends
Discussion of the generative content market has exploded in the past year as tools like ChatGPT and Stable Diffusion reveal the power artificial intelligence has to automate critical processes for content creation and business communication.
Emerging AI models make it possible to generate text, voice, images, code, and more, as many exciting developments in open source and emerging SaaS products have the market moving at a dizzying speed.
Join Aragon Analyst Adam Pease on Tuesday, February 28, 2023 where he will discuss how to leverage the latest trends and content in generative content.
This webinar with Adam will:
- Bring you up to date on the latest developments generative content
- Give you tools that your business can leverage right now
- Cover recent research about the trends that are shaping the direction of the market.
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