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Stanford University
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- 1Stanford violated its own AI policy by race-swapping students in ad●Stanford violated AI policy after race-swapping students in ad
Stanford University altered the appearance of students in a promotional image, changing their race, and was found to have violated its own generative AI policy in the process. The incident, reported by the San Francisco Chronicle, has drawn criticism over consent, diversity marketing and universities' rules on AI-edited imagery.
- 2Stanford dean warns AI labs are poaching university faculty▼Stanford dean says AI labs are competing with universities for faculty: 'I won't lie, I worry about this'
A Stanford dean has voiced concern that leading AI laboratories are competing directly with universities to hire faculty members, saying the situation worries him. As companies like OpenAI and Anthropic offer lucrative packages to top researchers, universities are struggling to retain professors whose expertise in machine learning is increasingly valuable to industry.
- 3MIT ranked top US university for engineering and computer science●MIT named best university in the United States for engineering and computer science https:// lemmy.zip/post/72207712
MIT has been named the best university in the United States for engineering and computer science. The ranking reinforces the institute's long-standing reputation as a leader in technology education and research, drawing comment from academics and technology enthusiasts discussing how its programs compare with rivals like Stanford and Caltech.
- 4Stanford and Nvidia release CLM-8B agent model▼Stanford and Nvidia's open CLM-8B caches reusable agent actions and runs up to 9x faster than Jev in tests
Stanford University and Nvidia have open-sourced CLM-8B, an AI model built for software agents that caches reusable actions instead of recomputing them. In tests the model ran up to nine times faster than Jev, a comparable agent system. The open release is drawing attention for offering large speed gains on agentic workloads, an area where inference cost is a major bottleneck for developers.