🏫 NYC State School Aid To Rise Amid Cuts. OpenAI’s Open Source Model Was the Fastest. Brazil’s Tobacco User Count Down.
Chart of the Day #469 Looks at NYC’s State School Aid, Brazil’s Tobacco Usage, and Large AI Model Response Speeds.
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Today's Topics
🏫 Education Funding. NYC state school aid per pupil to reach >16K by 2028, amid funding cuts
⚕️ Health Skills. Brazil’s overall tobacco user count decreased since 2008
🤖 Artificial Intelligence. OpenAI’s open source model tops response speeds
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🏫 NYC State School Aid per Pupil To Reach >16k by 2028, Amid Funding Cuts
NYC per-pupil state aid will look to rise continuously to over $16K by 2028, but 2024 reductions stemmed from Foundation Aid formula changes, and $1.9B federal pandemic relief expiration will impact these allocations. Gov. Hochul proposed cutting $131M from NYC and 337 districts to address enrollment declines. Mayor-elect Zohran Mamdani promises universal childcare expansion, ending mayoral control for "co-governance," and $12M teacher recruitment. However, his funding depends on tax increases requiring state approval, creating uncertainty amid ongoing budget pressures.
⚕️ Brazil’s Overall Tobacco User Count Decreased Since 2008
Despite ranking 8th globally in total tobacco users, Brazil's male smoking declined 6%+ (2008-2023), through comprehensive tobacco control. Price increases, smoke-free laws, marketing bans, and pictorial warnings are measures taken to minimise tobacco usage. However, approximately 147,000 annual tobacco-related deaths persist, mainly from lung cancer, COPD, and cardiovascular disease. Mortality from cardiovascular and respiratory diseases has declined over the years, though recent policy stagnation may threaten continued progress.
🤖 OpenAI’s Open Source Model Tops Response Speeds
OpenAI's gpt-oss-120B model dominates October 2025 output speed benchmarks at 345 tokens/second, significantly outpacing competitors. This open-source leadership demonstrates industry-wide emphasis on inference optimization, where companies achieve 2-3x speedups through quantization and batching. Major tech firms are investing invest heavily to optimise their speeds, such as Microsoft developing proprietary MAI models, Meta deploying Llama 4, while NVIDIA's TensorRT delivers 5x faster time-to-first-token.
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