A reply-post analyzing a reader's use-after-free bug in a limit-order matching engine argues that object pools change the nature of memory bugs rather than eliminating them. The author explains that without pooling, a freed-and-reused memory slot can let two different object types collide, potentially turning a stale pointer into a code-execution exploit via a mismatched function pointer. With pooling, the same logical use-after-free persists, but because the recycled memory always holds the same type, the dangerous type confusion is avoided—unless the object itself contains an inline tagged union, which reopens the original hazard.
matklad.github.io
· 2026-09-02
The Trump administration filed a statement of interest in The New York Times' copyright lawsuit against OpenAI and Microsoft, siding with OpenAI's claim that training AI models on copyrighted text qualifies as fair use. Government attorneys warned that narrowing fair-use doctrine could hinder scientific and economic progress tied to large language models.
theverge.com
· 2026-09-02
A research paper compiles evidence that widespread adoption of large language models is homogenizing written language, drawing on decades of linguistics and computational research into personality, gender, regional and cultural markers in text. The authors argue that as LLMs become the dominant tool for writing assistance, they risk flattening distinctive dialects, sociolects and individual voice patterns documented in prior sociolinguistic studies.
nature.com
· 2026-08-30
A new Use.AI survey of over 15,000 respondents found that 53% now verify explanations from doctors, teachers, and other professionals using AI before accepting them, while 46% say professional credentials carry less weight than before. Use.AI calls this shift an 'expertise recession,' describing a decline in automatic trust toward trained professionals as AI tools let people independently investigate claims.
techspot.com
· 2026-08-28
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