Why English doesn’t use accents
English spelling was heavily shaped by Norman French scribes post-1066, who preferred letter combinations (e.g., sh, th) over diacritics to represent non-Latin sounds.
English inherited this diacritic-free approach, resulting in complex and sometimes ambiguous spelling without accent marks.
French, influenced later by Renaissance printers like Geoffroy Tory, introduced systematic diacritics (acute accents, cedillas, circumflexes, diaereses) to clarify pronunciation and preserve traditional orthography.
The Norman French legacy ironically removed English from diacritic traditions despite French’s increased accent use.
This history explains English’s reliance on multiletter graphemes rather than diacritics, shaping its unique orthographic complexity.Adding a feature because ChatGPT incorrectly thinks it exists
Soundslice’s sheet music scanner was unexpectedly flooded with ASCII tablature uploads due to ChatGPT falsely recommending Soundslice for ASCII tab import and audio playback.
The feature did not exist; the AI hallucination created false user expectations, risking the company’s reputation.
Rather than disclaim misinformation, Soundslice developed a bespoke ASCII tab importer to meet this emergent demand—an example of “hallucination-driven development.”
The story highlights complex product decisions faced when AI-generated misinformation impacts user behavior and company roadmaps.
Raises broader questions on whether responding to AI hallucinations should guide feature development.Neanderthals operated prehistoric “fat factory” 125,000 years ago on German lakeshore
Archaeological evidence from Neumark-Nord 2 shows Neanderthals systematically extracted bone grease by smashing and boiling bones of at least 172 large mammals.
This reveals sophisticated understanding of nutrition and resource management previously attributed only to modern humans.
The processing required planning, coordination, and ecological knowledge, challenging outdated views of Neanderthals as unsophisticated.
The site preserves a wide ecological context, showing diverse Neanderthal activities and significant environmental impact through intensive hunting.
This discovery pushes back timelines for complex subsistence strategies and highlights Neanderthal cognitive capabilities.Mercury: Ultra-Fast Language Models Based on Diffusion
Mercury introduces diffusion-based Transformer LLMs that predict multiple tokens in parallel, achieving up to 10× faster token generation than speed-optimized autoregressive models.
Mercury Coder Mini and Small models reach throughputs of 1109 and 737 tokens/sec on NVIDIA H100 GPUs with comparable code generation quality.
Independent benchmarks and developer feedback (Copilot Arena) rank Mercury as both the fastest and among the highest quality code generation models.
The approach marks a technical advance in overcoming the speed-quality tradeoff inherent in previous LLM architectures.
A public API and free playground encourage community experimentation and broader adoption.Why dinosaur films after Jurassic Park struggle to match its success
Jurassic Park balanced awe-inspiring visuals, early but credible paleontological science, and nuanced character development, giving dinosaurs quasi-character status.
Subsequent dinosaur films often sacrificed scientific depth and storytelling coherence for spectacle and simplistic narratives.
Spielberg’s film integrated cautionary themes about scientific hubris (e.g., Ian Malcolm’s critiques) that resonated meaningfully, unlike many sequels.
The original’s depiction of dinosaur behavior combined imagination with plausible science known at the time, preserving cultural fascination.
The article highlights the challenge of evolving dinosaur cinema while honoring both scientific authenticity and compelling narrative.
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