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AI models capable of reliably guiding driverless cars typically require endless testing and fine-tuning, not to mention computational power out the wazoo. In an effort to bolster AI algorithm training effectiveness and efficiency, Google parent company Alphabet’s Waymo is collaborating with DeepMind on techniques inspired by evolutionary biology, the two companies revealed in a blog postthis morning.

As Waymo explains, AI algorithms self-improve through trial and error. A model is presented with a task that it learns to perform by continually attempting it and adjusting based on the feedback it receives. Performance is heavily dependent on the training regimen — known as a hyperparemeter schedule — and finding the best regimen is commonly left to experienced researchers and engineers. They handpick AI models undergoing training, culling the weakest performers and freeing resources to train new algorithms from scratch.

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