questions and answers on various topics.
the extremes of left and right wing politics both seem to point to authoritarian regimes and a rigid ideology that does not change further. a single axis seems insufficient to capture the political spectrum, two axes may also be insufficient. perhaps multivariate analysis is useful to gain insight. what is the currently best model to map the political spectrum?
the complexity of political ideologies and the limitations of a single or even two-dimensional axis to fully capture this spectrum have led to the development of more sophisticated models. one of the most comprehensive and widely recognized models in contemporary political science is the political compass, which uses two axes: economic (left-right) and social (authoritarian-libertarian). however, even this model can be limiting.
eight values model:
the 16 personalities model expands on the eight values by combining them into four primary categories: economic, diplomatic, civil, and societal. each category is split further to account for more specific nuances.
in politics, how does left and right, progressive and conservative, and openness and conscientiousness relate to novelty and stability?
political leftism and progressivism, along with the personality trait of openness, are inherently aligned with novelty and change. conversely, political rightism and conservatism, alongside the trait of conscientiousness, are intrinsically linked to stability and tradition.
what are differing expectations between the relationship with parents and a romantic relationship with a partner?
dependency vs. partnership
unconditional support vs. reciprocal support
hierarchical vs. egalitarian
lifelong bond vs. chosen commitment
guidance vs. companionship
cultural and social norms
why is sign language irreplaceable even for people mostly consuming media solitarily and despite the widespread use of text?
for a solitary person who enjoys media, using text for activities like watching movies with subtitles or reading books may suffice for many needs. however, sign language remains irreplaceable for in-person communication and other contexts where non-verbal cues, cultural identity, or rapid interaction are essential. sign language provides a depth of expression and immediacy that text alone cannot fully replicate, maintaining its critical role in effective and nuanced communication within the deaf community.
ignoring the importance of proper training, to what extent does chatgpt derive its capabilities from time-series prediction?
chatgpt does not directly derive its capabilities from time-series prediction. it derives its capabilities from learning patterns in text data through a process called language modeling. while time-series prediction involves predicting future values based on past values in a sequence, language modeling in chatgpt involves predicting the next word in a sequence of words based on the context provided by previous words. this process is somewhat analogous to time-series prediction but is specifically tailored to understanding and generating human language rather than numeric sequences.
how does predicting the next word in a sequence of words relate to knowledge?
predicting the next word in a sequence of words relates to knowledge in the following ways:
in essence, predicting the next word requires the model to draw on its learned knowledge of language, facts, and context to make informed and accurate predictions.
how similar is this to human thinking and expression?
the similarity between chatgpt's word prediction and human thinking and expression can be summarized as follows:
pattern recognition:
similar: both humans and chatgpt recognize patterns in language to predict what comes next. humans use experience and intuition, while chatgpt uses statistical patterns from its training data.
different: humans understand deeper meanings and nuances, including emotions and intentions, while chatgpt relies solely on patterns without true comprehension.
context utilization:
similar: both utilize context to make sense of the current conversation or text.
different: humans can infer from a broader range of context, including personal experiences and common sense, while chatgpt is limited to its training data and immediate text context.
knowledge retrieval:
similar: both retrieve knowledge to inform their responses. humans recall from memory, and chatgpt draws from its training data.
different: humans can verify facts and learn new information continuously, whereas chatgpt's knowledge is static, based on its last training cut-off.
expression:
similar: both can generate coherent and contextually relevant sentences.
different: humans express with a personal touch, including emotions and subjective perspectives, while chatgpt generates text without personal feelings or consciousness.
in summary, while there are superficial similarities in pattern recognition and context utilization, the underlying processes and depth of understanding differ significantly between human thinking and chatgpt's word prediction.
how far have human-made electromagnetic signals traveled into space so far?
human-made electromagnetic signals have traveled vast distances into space due to radio and television broadcasts, radar signals, and other communication technologies. these signals propagate outwards from earth and continue traveling indefinitely, albeit becoming increasingly weaker over distance.
the farthest human-made electromagnetic signals have traveled into space are from intentional radio transmissions, including those from high-power communication satellites and radar systems. some of these signals have reached beyond our solar system into interstellar space. however, they become extremely weak over such vast distances, making them virtually undetectable by the time they reach even the nearest stars.
as for specific distances, it's challenging to pinpoint an exact figure, but some of the earliest television broadcasts from earth have reached distances of over 80 light-years. for example, the first episodes of "i love lucy" which aired in the 1950s, have traveled roughly 80 light-years into space. since then, signals from more powerful transmitters and satellites have traveled even farther.
when giving ratings on scales of 1 to 5 or 1 to 10 about movies, music, photos, companies, et cetera, different users may use different rating strategies. for example, some users report tending towards a gaussian distribution of ratings, whereas i use a triangular series distribution. what are some common rating strategies that have been observed?