The government said the changes would ensure everyone who needs to be seen quickly would be.
Sheriff Hall testified again. His sense of betrayal had not subsided. “As a person who’s spent thirty-five years believing the criminal-justice system should provide better opportunities and second chances, I stand before the court asking for neither,” he said. Describing the danger Friedmann had put his staff in, he choked up. “Friedmann has had second chances and deserves no more.”
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"One day I just woke up and after a year-and-a-half on the streets I thought, 'I need to do something'," he says, remembering how he approached a local charity for support.
The threat extends beyond accidental errors. When AI writes the software, the attack surface shifts: an adversary who can poison training data or compromise the model’s API can inject subtle vulnerabilities into every system that AI touches. These are not hypothetical risks. Supply chain attacks are already among the most damaging in cybersecurity, and AI-generated code creates a new supply chain at a scale that did not previously exist. Traditional code review cannot reliably detect deliberately subtle vulnerabilities, and a determined adversary can study the test suite and plant bugs specifically designed to evade it. A formal specification is the defense: it defines what “correct” means independently of the AI that produced the code. When something breaks, you know exactly which assumption failed, and so does the auditor.
For SAT problems with 10 variables and 200 clauses, it usually output SAT as expected, but the assignment was never valid (Examples: first, second). Once it claimed a SAT formula was UNSAT. For this reason I didn't bother testing with more variables for the SAT case.