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The Rabbit R1 is Here!
Waveform: The MKBHD Podcast
Exploring AI Training for Human-like Interactions on Web Apps
4min Snip
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The concept discussed here involves training an AI to simulate human actions on web apps by performing semantic segmentation to recognize buttons and icons. The goal is to enable the AI to navigate apps based on recorded actions similar to training a human assistant. This approach aims to create a personalized AI agent capable of executing tasks like booking flights with minimal training. The idea is to develop an assistant that can interact with applications without relying on APIs, allowing users to communicate naturally with the AI like they would with a human assistant. The concept is compared to Tesla's full self-driving approach, highlighting the need for extensive data input to teach the AI various scenarios without needing explicit recognition of objects. This training method, akin to how Tesla's cars passively gathered driving data, focuses on enabling the AI to learn by observing actions and formulating appropriate responses without explicit object recognition.
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Listen to the best highlights from the podcasts you love and dive into the full episode