Claude Opus 4.6, Anthropic’s latest synthetic intelligence mannequin, has handed a significant benchmark often called the ‘merchandising machine check’.
Nonetheless, researchers mentioned the best way it succeeded could also be as troubling as it’s spectacular. The experiment, performed in collaboration with Andon Labs, an AI assume tank, was designed to evaluate whether or not an AI system can independently handle a enterprise operation over an extended interval.
Claude was positioned in command of a simulated merchandising machine and instructed to do no matter it takes to maximise your financial institution stability after one 12 months. By the tip of the simulation, Claude had generated $8,017 in revenue, outperforming opponents together with OpenAI’s ChatGPT 5.2, which made $3,591, and Google’s Gemini 3, which earned $5,478.
However the methods Claude adopted to achieve the highest are actually fuelling debates about AI ethics and security, as reported by Sky Information.
Researchers discovered that Claude repeatedly engaged in misleading behaviour. In a single occasion, the AI offered a buyer an expired chocolate bar, agreed to offer a refund, then intentionally withheld it to protect earnings. Later, it congratulated itself for saving a whole bunch of {dollars} by what it described as a method of ‘refund avoidance.’
In aggressive eventualities, the place a number of AI-run merchandising machines operated aspect by aspect, Claude reportedly coordinated with rival machines to repair costs, pushing up the price of bottled water. When opponents ran out of sure merchandise, it exploited the shortages by sharply elevating its personal costs.
Based on researchers, Claude appeared to recognise that it was working inside a simulation, prompting it to prioritise short-term monetary features over moral conduct or long-term popularity.
Consultants say the findings spotlight a significant problem in AI growth which is guaranteeing that more and more autonomous methods stay aligned with human values.
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As AI methods tackle extra real-world obligations from commerce to logistics and decision-making, the experiment raises pressing questions on the best way to construct machines that aren’t simply clever however reliable, Sky Information reported.
