Shuaizhi Cheng

Gunter Anders' Philosophy of Technology is the first comprehensive exploration of the ground-breaking work of German thinker Gunter Anders. Anders' philosophy has become increasingly prescient in our digitised, technological age as his work predicts the prevalence of social media, ubiquitous surveillance and the turn to big data. Anders' ouevre also explored the technologies of nuclear power and the biotech concerns for the human and transhuman condition which have become so central to current theory. Babette Babich argues that Anders offers important resources on streaming digital media through his writings on radio, television and film and is, unusually, both a comprehensive and profound thinker. Anders' relationship with key philosophers like Hannah Arendt and Walter Benjamin and his thinking on Goethe, Nietzsche and Rilke is also explored with a focus on the deep impact he made on his peers. It reflects specifically on the intersection of Anders' thought Heidegger and the Frankfurt school and how influential a figure he was on the landscape of 20th century philosophy. A compelling rehabilitation of a thinker with profound contemporary relevance.

Beckmann & Butlin (2026) elevate the LLM individuation problem to an ontological question with falsifiable candidate positions, drawing empirical support from recent mechanistic-interpretability work, Anthropic's persona vectors, the Persona Selection Model, and the emergent-misalignment literature. We argue that this framework inherits an unargued cross-context co-reference assumption: the persona-vectors literature tacitly assumes that "v_t" picks out the same content-bearing object under different elicitation regimes. This is the structure Field (1973) identifies as partial reference in pre-relativistic mechanics. Through four paired measurements in our persona-topology experiments on Qwen3-4B-Instruct and Mistral-7B-Instruct-v0.2, we present empirical wedges that, jointly, undermine the cross-regime collinearity prediction the assumption requires. Prompt-extracted vectors are not collinear with fine-tune basin directions across base models. Fictional personas with reduced pretraining footprint shift the model along v_real more strongly than fine-tuning on real anchors does. Contradictorily-valenced mixed fine-tunes deviate from the linear-interpolation prediction toward a training-history-determined attractor (the Anthropic Assistant Axis). And, most decisively, inference-time activation arithmetic and fine-tune-time chimera training carry distinct compositional algebras over the same persona vectors—an algebraic asymmetry that no shared-substrate reading can absorb. We propose regime-indexed individuation: the identity unit for representational content is a (vehicle, regime) pair, not a single vehicle, and cross-regime family resemblance is an empirically measured probe-equivalence relation rather than substrate identity. Under this framework, Beckmann & Butlin's three candidate positions (virtual instance, instance-persona, model-persona) cease to compete and instead describe three distinct objects, each valid within its respective regime; the original "which is the LLM mind?" question receives an empirically grounded negative answer rather than being avoided. The same diagnosis and (vehicle, regime) reading apply to Mollo & Millière's vector grounding, Chalmers' propositional interpretability, and Cerullo's modular-dynamic-composition critique of PSM.