AI research

AI companies like Anthropic, OpenAI, Meta, and DeepMind are hiring top researchers from universities, shifting significant AI research from academia to industry. This trend includes hiring professors from institutions such as UC Berkeley, Stanford, and UT Austin, with concerns about research becoming proprietary and reducing open academic collaboration.

Google is investing $75 million in A24 as part of a new AI research initiative focused on developing filmmaking tools. The collaboration aims to advance AI applications in the film industry.

A Google DeepMind distinguished engineer, Vladimir Feinberg, outlined key qualities for securing a job at a top AI lab: 'intent,' 'mathematical maturity,' and 'grit.' He emphasized taking challenging academic courses, coding rigorously, and working intensively to develop competitive skills in AI research.

ByteDance has lost Gu Quanquan, a key AI researcher behind Seed models, as the company shifts focus to monetizing its AI offerings like Doubao. Gu Quanquan, also a UCLA computer science professor, announced his departure from ByteDance.

A research paper by Peter Degen is being cited excessively, with hundreds of citations in a short period, sparking an investigation. The paper assessed statistical analysis on epidemiological data and was published in 2017. This unusual citation pattern is causing concern among scientists.

The National Science Foundation (NSF) awarded a record number of PhD fellowships in a surprise move, with quantum science and AI research benefiting significantly. This follows a previous 50% reduction in Graduate Research Fellowship Program awards by the NSF a year earlier.