The recent explosion of performance of large language models (LLMs) has changed the field of Natural Language Processing (NLP) more abruptly and seismically than any other shift in the field's 80-year history. This has resulted in concerns that the field will become homogenized and resource-intensive. The new status quo has put many academic researchers, especially PhD students, at a disadvantage. This paper aims to define a new NLP playground by proposing 20+ PhD-dissertation-worthy research directions, covering theoretical analysis, new and challenging problems, learning paradigms, and interdisciplinary applications.
Interesting, can you elaborate? What part of the city or surrounds do you find this to be true? I've found the reliability and mix of routes via tunnelbana, pendeltåg, trams, buses, and boats to be really good and know many Stockholmers without cars. Of course, road trips and moving large items become more of a hassle without a car, but can often be worked around with rentals/delivery srevices. Further, the more remote you get, the density of public transport options do become sparse, if an option at all. But within the radius of the tunnelbana, living without a car is very achievable. [edit: saw your other comment about further out areas, late night journeys and MTR, which are fair points. Cars are super convenient in many ways, no argument there.]
Per year, they used the following scale in the questions: "The frequency of milk tea consumption was measured by the item, “In the past year, what was the average frequency of your milk tea consumption? (Lee et al., 2022)”. Item was rated on a 10-point Likert scale, coded as 1 = 3 cups per day, 2 = 2 cups per day, 3 = 1 cup per day, 4 = 4–6 cups per week, 5 = 2–3 cups per week, 6 = 1 cup per week, 7 = 2–3 cups per month, 8 = 1 cup per month, 9 = 6–11 cups per year, 10 = Almost never drink milk tea." The distribution of drinkers is shown in the figure: https://ars.els-cdn.com/content/image/1-s2.0-S01650327230108...
The reason why it may be useful to avoid blue light at night is that circadian rhythms and melatonin production can be disrupted due to ganglion cell stimulation. They are a class of photoreceptors that have peak sensitivity to blue light. They do not appear to contribute much in the way of spatial vision but are important to entrain day night cycles and for pupillary responses. https://en.wikipedia.org/wiki/Intrinsically_photosensitive_r...
Minsky and Papert showed that computing XOR requires a 3 layer artificial neural net: Input, Hidden Layer, Output - which has 2 layers of weighted connections.
This[0] research shows a single neuron can compute XOR, thus the artificial neuron has less computational power than a real one.
