The National Highway Traffic Safety Administration (NHTSA) has identified at least 80 instances in which Tesla's Full Self-Driving (Supervised) software violated road rules by running red lights or crossing into the wrong lane, according to a new letter sent to the automaker this week. NHTSA said in the letter it has received 62 complaints from Tesla drivers, 14 reports submitted by Tesla, and four media reports that describe potential violations. That's up from around 50 violations NHTSA cited when it opened an investigation into the behavior in October. The federal safety agency's Office of Defects Investigation (ODI) is probing whether Tesla's driver assistance software can 'accurately detect and appropriately respond to traffic signals, signs and lane markings,' according to the letter. ODI is also evaluating whether Tesla's software is providing sufficient warnings to drivers in these situations. Tesla's responses are due January 19, 2026. The increase in complaints is notable in part because the original batch reported by ODI in October included multiple reports from one particular intersection in Joppa, Maryland. Tesla told the agency at the time that it had already 'taken action to address the issue at this intersection.' The agency didn't say where, geographically, these newly reported incidents took place. Tesla heavily redacts its own submissions to the agency....

Companies eager to adopt generative AI often launch numerous pilots across departments, chasing quick wins and marginal efficiencies. But a scattershot approach won't deliver transformative impact. The global consumer packaged goods company Reckitt took a different approach. It chose to go deep in one domain'marketing'where gen AI could be applied across interconnected tasks like insight generation, content creation, and product development. The lesson' To unlock gen AI's full potential, organizations should resist the urge to experiment broadly and instead go deep and narrow'concentrating efforts where scale and synergy can drive meaningful change. They should begin by selecting a single strategic domain where gen AI can be applied across interconnected tasks. They should then build on existing strengths'such as data assets or technical capabilities'to scale AI adoption meaningfully. By rethinking core processes within that domain and aligning teams around transformation rather than experimentation, companies can unlock deeper insights, accelerate innovation, and achieve measurable impact....

In his run for governor of Maine, Nirav Shah holds standard Democratic positions. He aims, his campaign says, 'to fix housing, fund health care, feed kids, and fuel growth, while fighting back against the overreaches of the Trump administration.' But Shah's background is less conventional: In addition to being a lawyer, he's an epidemiologist who directed Maine's CDC during the coronavirus pandemic and was the principal deputy director of the federal CDC until earlier this year. Shah decided to resign from the CDC in part because of Robert F. Kennedy Jr.'s confirmation as the secretary of health and human services. If he wins in 2026'a big if this early in the race'Shah suspects that he might be one of the first, if not the first, top CDC officials to secure such a prominent elected office. Many science and health professionals have shied away from politics in the past. But as the Trump administration has rescinded its support for scientific research, restricted vaccine access, dismissed expert advisers, attacked doctors and scientists, and worked to curtail health-insurance coverage, researchers and health-care workers have had a surge of interest in running for office. Shaughnessy Naughton, the president of 314 Action, a political-action committee focused on electing Democrats with science backgrounds, told me that since January her team has seen almost 700 applications for candidate guidance, training, or funding, about seven times what the group would expect during an election off year....

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