Echo Ubertube | Outdoor Research
November 30, 2025The Peter Attia Drive Podcast – Peter Attia
November 30, 2025https://peterattiamd.com/podcast/
longevity podcast
Steps of cellular respiration | Biology (article) | Khan Academy
November 29, 2025Nice overview of the key reactions in the 3 steps (Lysis => cycle => transport)
Frankenstein (2025 film) – Wikipedia
November 29, 2025NYTimes.com: Robert A.M. Stern, Architect Who Reinvented Prewar Splendor, Dies at 86
November 29, 2025Designed 15 CPW
Robert A.M. Stern, Architect Who Reinvented Prewar Splendor, Dies at 86
He designed museums, schools and libraries before winning
international acclaim late in life for 15 Central Park West in Manhattan, hailed as a rebirth of the luxury apartment building.
https://www.nytimes.com/2025/11/27/arts/design/robert-am-stern-dead.html
56 Leonard Street – Wikipedia
November 27, 2025https://en.wikipedia.org/wiki/56_Leonard_Street
821′ tall Jenga tower
Stochastic gradient descent – Wikipedia
November 24, 2025https://en.wikipedia.org/wiki/Stochastic_gradient_descent
QT:{{”
Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties (e.g. differentiable or subdifferentiable). It can be regarded as a stochastic approximation of gradient descent
optimization, since it replaces the actual gradient (calculated from the entire data set) by an estimate thereof (calculated from a randomly selected subset of the data). Especially in high-dimensional optimization problems this reduces the very high computational burden, achieving faster iterations in exchange for a lower convergence rate.[1]
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SGD by selecting randomly just one pt.
