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Home / Technology / AI Builds Digital Clones for Job Training

AI Builds Digital Clones for Job Training

2 Dec

•

Summary

  • Companies create replica websites to train AI agents for tasks.
  • This method generates data for AI reinforcement learning.
  • Legal and ethical questions arise over website cloning for AI training.
AI Builds Digital Clones for Job Training

A new trend in Silicon Valley involves startups meticulously recreating popular websites to train artificial intelligence systems. Companies are building digital clones of sites like United.com, Amazon, and Airbnb to serve as safe environments for AI agents to learn complex tasks through trial and error. This method of "reinforcement learning" is crucial for advancing AI beyond current chatbot capabilities.

These "shadow sites" generate vast amounts of data, overcoming the limitations of scraped internet content and restrictions on bots accessing live websites. Startups like AGI and Plato are at the forefront, developing these replicas to equip AI with skills for booking travel, scheduling meetings, and automating other computing tasks, potentially impacting white-collar employment.

While this innovation fuels AI development, it ventures into uncharted legal territory. Questions about copyright infringement are emerging, as companies like United Airlines have issued takedown notices. Experts debate whether this practice is permissible under current law, highlighting a rapid expansion of AI technology that outpaces legal frameworks.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
Shadow sites are replica websites created by companies like AGI to serve as training environments for artificial intelligence systems to learn tasks like booking flights.
Companies are concerned about replica websites due to potential copyright infringement and brand dilution, as seen with United Airlines' takedown notice.
AI agents learn through reinforcement learning by performing thousands of trial-and-error interactions on replica websites, identifying actions that lead to successful task completion.

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