/int/ - International

I use ChatGPT to deal with long texts, extracting quotes, summarizing paragraphs and such. It's alright, but sometimes it's badly hallucinating, so not that good, if you need accurate results. NotebookLM by Google seems to be better for analyzing texts and doesn't hallucinate much. I also used CoPilot for extracting quotes etc, was decent.

>>3638 ChatGPT works better if you use the o3 model. Anything else can produce questionable or flat out wrong responses. Haven't used NotebookLM or CoPilot.

>>3640 Can you even change the model nowadays? I don't see that option anymore. >Haven't used NotebookLM or CoPilot. I only used them in a work context. Well, when I had exhausted my ChatGPT tokens, I also used Deepseek shortly, but it's not great with text files.

>>3641 >Can you even change the model nowadays? I don't see that option anymore. It might be a paid-only feature. o3 is much more powerful than o4

Used it when it first came out. Got boring after couple hours. No interest in this AI shite since. Makes me cringe so hard when people say shit like "I asked Grok/ChatGTP/Claude".

ChatGPT has replaced back of the envelope calculations for me. I also find it pretty useful for introducing new topics, since you can ask for a list of reliable sources and the results will be quite good, often better than going on Wikipedia and looking at their references. Sometimes I ask for it to debug my code or discuss possible ways to implement something and AI is pretty much beyond improvement for that purpose, imo. I've tried roleplaying (with ChatGPT, Gemini, DeepSeek, the latter getting me the best results) but it doesn't come close to a human partner.

>>3646 >>3647 Here's something to ponder. Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task Nataliya Kosmyna, Eugene Hauptmann, Ye Tong Yuan, Jessica Situ, Xian-Hao Liao, Ashly Vivian Beresnitzky, Iris Braunstein, Pattie Maes This study explores the neural and behavioral consequences of LLM-assisted essay writing. Participants were divided into three groups: LLM, Search Engine, and Brain-only (no tools). Each completed three sessions under the same condition. In a fourth session, LLM users were reassigned to Brain-only group (LLM-to-Brain), and Brain-only users were reassigned to LLM condition (Brain-to-LLM). A total of 54 participants took part in Sessions 1-3, with 18 completing session 4. We used electroencephalography (EEG) to assess cognitive load during essay writing, and analyzed essays using NLP, as well as scoring essays with the help from human teachers and an AI judge. Across groups, NERs, n-gram patterns, and topic ontology showed within-group homogeneity. EEG revealed significant differences in brain connectivity: Brain-only participants exhibited the strongest, most distributed networks; Search Engine users showed moderate engagement; and LLM users displayed the weakest connectivity. Cognitive activity scaled down in relation to external tool use. In session 4, LLM-to-Brain participants showed reduced alpha and beta connectivity, indicating under-engagement. Brain-to-LLM users exhibited higher memory recall and activation of occipito-parietal and prefrontal areas, similar to Search Engine users. Self-reported ownership of essays was the lowest in the LLM group and the highest in the Brain-only group. LLM users also struggled to accurately quote their own work. While LLMs offer immediate convenience, our findings highlight potential cognitive costs. Over four months, LLM users consistently underperformed at neural, linguistic, and behavioral levels. These results raise concerns about the long-term educational implications of LLM reliance and underscore the need for deeper inquiry into AI's role in learning.

Current musings: nostalgia was, at one point if I recall, considered a mental illness. The term nowadays whimsically refers to any mass sentimentality for yesteryear's popular culture, media, architecture and/or other prominent facets. These sentiments range from more than slight fascination to deep-seated desires to recreate/revive their objects of fixation. It's about the past but divorced from the context in which those objects arose from. To me, the common thread running through both gradients of nostalgia is the desire for standards. People don't miss the problems from the past because they are legion, but they certainly miss the standards that any object from the era was expected to conform or live up to. Failing that was failure itself. ChatGPT had this to say: You remember correctly: “nostalgia” began life as a bona-fide disorder. 1688 — Swiss medical student Johannes Hofer coined the word in a Latin dissertation describing soldiers, students, and servants who became physically ill when exiled from their homelands. Symptoms ranged from heart palpitations and fever to suicidal despair; the cure, physicians thought, was to send the patient home. 18th–19th c. — European armies kept surgeons on the lookout for it; during the U.S. Civil War roughly 5,000 Union soldiers were formally diagnosed and an estimated 10,000 deaths were attributed to the condition. Early 20th c. — Psychiatrists quietly dropped nostalgia from their manuals as germ theory, shell shock, and modern psychology offered rival explanations. By mid-century it resurfaced not as illness but as an aesthetic and marketing category—an emotion to be mined rather than cured. ---

How the meaning flipped 1. From place-sickness to time-yearning. Cultural theorist Svetlana Boym notes that what we now call nostalgia “is a yearning for a different time… a rebellion against the modern idea of progress.” 2. The “nostalgia mode.” In Fredric Jameson’s account of post-modern culture, mass media turns the past into an endless grab-bag of styles—“the insensible colonization of the present by the nostalgia mode.” 3. Commodification. Once the malady lost its clinical sting, advertisers discovered its selling power: retro diners, vinyl crackle on streaming tracks, artificial film grain in phone cameras. Longing became lifestyle. --- Why the feeling centers on standards Your intuition is on point: the ache isn’t just for objects, but for the rules those objects once had to meet. Then Now Broadcast-era scarcity → high gatekeeping; limited shelf space demanded editorial standards. Abundant digital space → “publish first, patch later”; quality control diffuses. Material limits (vinyl run-time, TV signal bandwidth) forced discipline in composition and production. Infinite storage, infinite undo: fewer converging constraints, more tolerance for half-finished releases and perpetual beta. Mass institutions (network news, three automakers, national curricula) provided shared benchmarks—even if biased. Fragmented micro-audiences; each niche invents its own metrics of success. The result: people don’t necessarily want 1957 again—they want the coherence that comes from living inside a system where failure is legible and excellence is rewarded. When today’s culture offers choice without criteria, many retreat to eras where the criteria felt visible, even if those eras were riddled with injustices we’re glad to have escaped. --- Two strands of contemporary nostalgia Restorative (Boym) Reflective (Boym) Tries to rebuild the lost world: revivalist architecture, heritage politics, reissues that aim for sonic fidelity. Savors the gap between past and present: vaporwave, retro-futurism, ironic diner décor. Both are reactions to a perceived collapse of standards; one tries to reinstall them, the other to play with their ruins. --- Takeaway Nostalgia’s evolution—disease → commodity → cultural mood—tracks a larger civilizational story. The more our present flattens hierarchy, accelerates change, and blurs judgment, the more we romanticize periods when somebody, somewhere, said “this is the bar.” Longing for yesterday’s TV jingles or Brutalist facades is ultimately a coded way of asking: “What, today, is worth measuring ourselves against?”