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The Trump administration has lifted restrictions on OpenAI's GPT five point six, clearing the way for broader deployment of one of the most capable language models yet released. The move signals a notable shift in how the current White House views AI regulation, prioritizing access and economic competitiveness over the guardrails some researchers have been pushing for.
That timing is interesting, because a twenty twenty three study making fresh rounds this week asks a question the policy world keeps sidestepping: how much energy does running these models actually cost? Researchers benchmarked the watt-hours consumed during large language model inference and found the numbers climb fast at scale, adding a resource dimension to every conversation about AI expansion.
And on a separate front, an AI-assisted security platform called Zero Day Rubbish is drawing attention after publishing what it claims is a critical vulnerability in Cisco's Unified Communications Manager, version fourteen point zero. The researchers describe a six-stage chain from SQL injection all the way to root access, scoring a nine point eight on the severity scale. The disclosure raises real questions about how AI-driven vulnerability hunting changes the pace and politics of responsible disclosure.
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