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Interests: climate, science, sci-fi, fantasy, LGBTQIA+, history, anarchism, anti-racism, labor politics
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Sally Strange wants to read The Adventures of Mary Darling by Pat Murphy
Based on this rave review from Cory Doctorow, I am putting this high up on my to-read list!
pluralistic.net/2025/05/06/nevereverland/#lesser-ormond-street
Sally Strange wants to read Sky Full of Elephants by Cebo Campbell

Sky Full of Elephants by Cebo Campbell
In a world without white people, what does it mean to be Black?
One day, a cataclysmic event occurs: all …

otter replied to Sally Strange's status
@SallyStrange she deserves better behavior than smidges and tads tbh
Sally Strange replied to otter's status
@thief@weirder.earth Certainly. The wording reflects my opinion of the effort that would have been involved in not being so racist as to drive her away completely.
Sally Strange commented on The Disordered Cosmos by Chanda Prescod-Weinstein
This chapter about melanin is so fascinating and surprising. Melanin is a conductor, that is also an insulator, depending on the presence or absence of water? Melanin could be a building material? Melanin could be the key to constructing materials for bioelectric implants? Awesome stuff, and Dr. Prescod-Weinstein is right to consistently rail against the exclusion of Black people from academia and physics in particular. Damn, Fedi, she was here and then she left. Imagine how much cooler this place would be if us white folks had been a smidge more hesitant to do microaggressions, a tad less disbelieving of the direct first-hand reports of racism and white supremacy from her and others like her.

Sasu reviewed How Emotions Are Made by Lisa Feldman Barrett
Fascinating Theory with Practical Applications
5 stars
Even though it's been a few years since I listened to this one, it often resurfaces in my thoughts. In short, the theory of #emotion presented in this book is powerful because of its flexibility and its ability to explain: - how #reframing is even possible - how there can be such large #emotional differences between cultural groups - how it could have been possible that the way humans construct emotion has changed over the course of #history
Sally Strange started reading The Chromatic Fantasy by H.A

Soh Kam Yung reviewed Why Machines Learn by Anil Ananthaswamy
A mathematical look at how machines learn and make decisions.
4 stars
A fascinating book that looks at the history of Machine Learning (ML) to show how we arrive at the machine learning models we have today that drive applications like ChatGPT and others. Mathematics involving algebra, vectors, matrices, and so on feature in the book. By going through the maths, the reader gets an appreciation of how ML system go about the task of learning to distinguish between inputs to provide the (hopefully) correct output.
The book starts with the earliest type of ML, the perceptron, which can learn to separate data into categories and started the initial hype over learning machines. The maths are also provided to show how, by adjusting the weights assigned to its testing input, the machine discovers the correct weights which can allow it to categorize other inputs.
Other chapters then cover other ways to train a machine to categorize its input is shown, based on …
A fascinating book that looks at the history of Machine Learning (ML) to show how we arrive at the machine learning models we have today that drive applications like ChatGPT and others. Mathematics involving algebra, vectors, matrices, and so on feature in the book. By going through the maths, the reader gets an appreciation of how ML system go about the task of learning to distinguish between inputs to provide the (hopefully) correct output.
The book starts with the earliest type of ML, the perceptron, which can learn to separate data into categories and started the initial hype over learning machines. The maths are also provided to show how, by adjusting the weights assigned to its testing input, the machine discovers the correct weights which can allow it to categorize other inputs.
Other chapters then cover other ways to train a machine to categorize its input is shown, based on Bayes Theorem and nearest neighbour. They have their advantages and disadvantages: choosing the right (or wrong) way to train a machine will have an impact on how well the machine can categories its data.
Matrix manipulation, eigenvalues and eigenvectors are then introduced. When there are many input parameters, it can be hard to categorize them based on all the factors. By using eigenvalues and eigenvectors, it is possible to discover which factors cause the most variation among the data, and thus categorize them. And, in an interesting reversal, it is also possible to manipulate the input by putting them into more categories, which can reveal patterns that can then be used to categorize the input.
These ML models categorize input data using one level of 'neurons'. The next step would be to introduce a 'hidden layer' of neurons that can be used to combine the incoming data in many ways, which provides new ways to manipulate the data for categorization. This would provide a boost in the abilities of machines to recognize input data.
Lastly, the book catches up to current day ML models, which feature a huge increase in the number of hidden layers and weights used to manipulate input data. The book then points out that this huge increase has caused the theory of how machines learn to fall behind: the machines now exhibit abilities that theory cannot account for. The ability of such machines to pick out patterns in data through self-learning, rather than being pre-fed known data, is also an unexpected feature that current ML theories cannot account for.
These unaccounted features of current day ML systems are a probable cause of concern. So too is the concern over the kind of data being pre-fed to the systems: data that comes with various biases that only cause the system to make yet more biased decisions. Until we know better how these systems behave, it would be best to treat their outputs with caution.

radio-appears started reading Adulthood Rites by Octavia E. Butler (Lilith's Brood, #2)

dvo started reading The Ice Wanderer by Jiro Taniguchi
Sally Strange finished reading A Fire Upon The Deep by Vernor Vinge

A Fire Upon The Deep by Vernor Vinge
Thousands of years in the future, humanity is no longer alone in a universe where a mind's potential is determined …
Sally Strange reviewed A Fire Upon The Deep by Vernor Vinge
Sci-fi classic I can't believe I didn't read before
5 stars
I have so many questions. Sound-based thought waves? The galaxy has speed zones? Ultimately though it was such a good story that I don't care much about the answers. I was super impressed by (since he was writing in 1993) and absolutely love Vinge's idea of a galaxy-wide internet that's hundreds of millions of years old and nobody knows who started it. That to me seems extremely plausible, given a universe with multiple sentient space-faring species. This was SO much fun, and anyone who loves science fiction should definitely read it.
Sally Strange reviewed Zero Sum Game by S. L. Huang
Mercs and psychics, oh my!
4 stars
Mostly action adventure with scifi accents. Cas makes a sympathetic protagonist, and there is some good character development. The background info about the scifi stuff leaves us wondering and wanting more, but that's a pretty minor concern since the action scenes are top notch. Fun read.