Forget chatbot training. AI's next big data grab is about learning how humans work.
Tech companies are shifting AI development from training chatbots on text to using reinforcement learning environments to teach AI agents how to perform complex workplace tasks. This involves collecting granular human data, such as keystrokes and mouse movements, to simulate professional workflows.
Why it matters
This shift marks a transition toward AI that can replace human labor in professional settings, raising significant questions about workplace privacy and the future of employment.
Tamay Besiroglu is the cofounder and CEO of the San Francisco startup Mechanize, which aims to automate all jobs. Courtesy Tamay Besiroglu Mechanize aims to automate jobs using RL environments, drawing interest from Google. AI development shifts from chatbot training to RL environments, enabling complex task learning. Meta tried to track employees' workplace actions and workflows, for use in AI development. The AI race is shifting away from teaching chatbots how to answer questions and toward teaching agents how to perform entire jobs. After years spent training models on internet text and paying contractors to rate chatbot responses , tech companies are increasingly focused on something new: creating realistic digital workplaces where AI can practice coding, using business software, making decisions, and completing long-running tasks much like a human employee. These digital training realms are called reinforcement learning environments , or RL environments for short.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in