Traces how advances in vision-language models enable agents to perceive and act on screens directly, framing why API-free 'computer use' automation is now viable — useful context for anyone building browser or desktop agents.
A Browserbase engineering blog post tracing the history of neural networks from the 1957 Perceptron through reinforcement learning to modern multimodal models, arguing that today's vision-language models can perceive screens, reason, and act like humans, forming the basis of 'computer use agents' that automate software without needing APIs.
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