Researchers at MIT and IBM assemble new object recognition dataset that highlights the limitations of current AI techniques

The dataset consisted of an assortment of objects shot at unusual angles and surrounded by clutter. While computer vision performance has increased significantly over the past decade, a top-performing algorithm's accuracy rates fell from a high of 97% on more simple datasets to just 50% to 55% on the new dataset. This study highlights a major challenge for AI, namely, that as the environment becomes more complex and unpredictable, machine learning performance drops off considerably. While clients could wait for the algorithms to become more robust before deploying a solution, a more near-term solution to this challenge is to consider constraining a problem to make it a better fit for today's tools.

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