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AI chip company Cerebras is riding a wave of investor enthusiasm, with plans to raise its IPO price range to between one hundred fifty and one hundred sixty dollars per share. That surge in demand signals strong market appetite for specialized AI hardware, even as the broader tech sector navigates an uncertain economic climate.
Meanwhile, a disconnect is growing between the people building AI and the people writing laws about it. A new survey finds most tech workers fear job displacement from artificial intelligence, while members of parliament appear more focused on fraud and misuse. That gap in understanding, workers warn, could lead to regulation that misses the point entirely.
And in a quieter corner of the AI world, researchers are rethinking what compression even means. Rather than shrinking files to save storage space, the new frontier is reducing how much processing an AI model burns through when it reasons — essentially trimming the cognitive fat so that thinking costs less. It is a subtle shift, but one with real implications for the economics of running large language models at scale.
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