  |
はてなキーワード: Writeとは
Laziness: The quality that makes you go to great effort to reduce overall energy expenditure. It makes you write labor-saving programs that other people will find useful and document what you wrote so you don't have to answer so many questions about it.
Impatience: The anger you feel when the computer is being lazy. This makes you write programs that don't just react to your needs, but actually anticipate them. Or at least pretend to.
Hubris: The quality that makes you write (and maintain) programs that other people won't want to say bad things about.
「怠惰」を美徳とする元々の文脈では、「後先めんどくさいことにならないように、今努力する」ことを怠惰と呼んでいたので、本当の意味で怠けることは意味していない
Laziness: The quality that makes you go to great effort to reduce overall energy expenditure. It makes you write labor-saving programs that other people will find useful and document what you wrote so you don't have to answer so many questions about it.
vibe codingがはやって、AgentモードでAuto Approveでどんどん実装をすすめておいて、負債がたまるーていっているヤツがうっとうしい。
LLMのモデルが全部のコードや仕様を把握している訳ではないので、間違った方向に進むことはしょっちゅうあるのはあたりまえ。
編集する前にdiffを見て、間違っていたら間違っているとを伝えてどのようにしたらいいかまで伝えれば、LLMにまかせても負債がたまっていかない。
たまにちょっとおかしい時に間違っている説明して再生成がたいへんだから、いったんその編集内容で保存してから、修正結果に対して再度修正を依頼をすることはあるけど。
間違った方向にすすめばその分LLMのAPIのコストもかかるので、コストのことも考えていないということも腹だたしい。
Auto ApproveでWriteまで許可しているやつは、LLMが動作している間、何してるん？どうせ生産性を産むようなことをしてないんだからおとなしくLLMの動作を見守っとけ。
> アプリ内のデータかバックアップしたのを自分でダウンロードしてテキスト化する方法ないかなあ／できたわ。設定→位置→タイムライン→タイムラインのエクスポートでjson化可能。あとは誰かが処理系を作るだけだ！
https://b.hatena.ne.jp/entry/4766225990155446401/comment/punychan
これを使えばXXXX-XX-XX.kml 形式で日付別のタイムラインデータを出力できる(ChatGPT製)。
KMLファイルはGoogle Earth Proなどで開くことが可能で、ビジュアルとして行動履歴を見ることができる。
ただ、以前GoogleMapsタイムラインが吐いていたKMLではPlacemarkという項目に直接建物名などが書かれていたが、現在出力されているjsonではplaceIdというものに変更されていて具体的な名前がわからない。
placeIdを実際の建物名などに変換するにはGoogle Maps API の Place Details APIを使うしかないようだが、膨大なリクエスト(有料)をしなければならず非現実的。
もともと欧州のプライバシー関係の規制のせいでGoogleのサーバ上でのタイムライン履歴が行われなくなったのが今回の問題の起点。
ユーザーの自由を尊重するなら、個人が行動履歴を自己管理する自由ももっと尊重してもらいたいものだな、と思った。
import json
import os
from xml.etree.ElementTree import Element, SubElement, tostring
from xml.dom.minidom import parseString
with open("タイムライン.json", "r", encoding="utf-8") as f:
data = json.load(f)
output_folder = "kml_output"
os.makedirs(output_folder, exist_ok=True)
# `semanticSegments` に移動データが含まれている
if "semanticSegments" in data:
date_segments = {} # 日付ごとにデータをまとめる辞書
for segment in data["semanticSegments"]:
# `startTime` から日付部分（YYYY-MM-DD）を抽出
if "startTime" in segment:
date = segment["startTime"].split("T")[0]
date_segments[date].append(segment)
for date, segments in date_segments.items():
kml = Element("kml", xmlns="http://www.opengis.net/kml/2.2")
document = SubElement(kml, "Document")
for segment in segments:
for point in segment["timelinePath"]:
coords = point["point"].replace("°", "") # 度記号を削除
time = point.get("time", "Unknown Time")
# Placemarkを作成
placemark = SubElement(document, "Placemark")
# タイムスタンプ
timestamp = SubElement(placemark, "TimeStamp")
when = SubElement(timestamp, "when")
# 座標
point_element = SubElement(placemark, "Point")
coordinates = SubElement(point_element, "coordinates")
lat, lon = coords.split(", ")
coordinates.text = f"{lon},{lat},0" # KML形式: lon,lat,alt
kml_str = tostring(kml, encoding="utf-8")
formatted_kml = parseString(kml_str).toprettyxml(indent=" ")
kml_filename = os.path.join(output_folder, f"{date}.kml")
Please consider the histroy of humanity from biological perpsecitve and current known fact in nearby universe, which expo-planet (from the Sol system perspective) is most likely to have civlizaed society? Please add percentage next to it in the chart
ChatGPT
Reasoned about exoplanet civilization likelihoodを28 秒行う
Evaluating planetary prospects
OK, I’m looking at the likelihood of a civilized society on an exoplanet within our Solar System. I’ll consider biological history and current space knowledge, aiming to identify the most promising candidate.
Identifying potential candidates
I'm considering exoplanets like Proxima Centauri b and TRAPPIST-1e, which might suggest they are within or observed from our Solar System.
Assessing potential candidates
I’m evaluating Proxima Centauri b, Barnard's Star, LHS 1140, and TRAPPIST-1, focusing on their habitable zones and available data. The Drake equation might help estimate their civilized society likelihoods.
Identifying promising exoplanets
I’m noting key exoplanets like Proxima Centauri b and TRAPPIST-1, which have Earth-like characteristics and are in habitable zones. This narrows down the potential candidates for advanced civilizations.
I'm gathering info on planets like Proxima Centauri b and TRAPPIST-1, considering factors like magnetic fields, atmospheres, and proximity to G-type stars for their potential to support advanced civilizations.
Evaluating exoplanet prospects
I'm noting that Proxima Centauri b, despite being close and around a red dwarf star, might support life if it has a magnetic field and atmosphere. This makes me think about its potential.
Charting probabilities
I'm estimating civilization probabilities for exoplanets like Proxima Centauri b and TRAPPIST-1 e, using speculative percentages based on the Drake equation and the lack of evidence for intelligent life.
I'm crafting a chart with exoplanet names and civilization likelihood percentages, grounded in the long timeline of life's evolution, despite the speculative nature of these figures.
Identifying exoplanet contenders
I’m evaluating exoplanets like Proxima Centauri b, TRAPPIST-1 e, and Kepler-186f, considering their star types and distances, to gauge their potential for supporting advanced civilizations from our solar system's viewpoint.
Weighing proximity and observation
I'm leaning towards Proxima Centauri b due to its closeness and observational potential, despite concerns about its flare star dynamics. TRAPPIST-1 e, f, or g are also worth considering.
I'm focusing on exoplanets like Proxima Centauri b, Ross 128 b, LHS 1140 b, TRAPPIST-1 e/f/g, and K2-18b, aiming to chart their likelihood of hosting a civilized society based on current knowledge.
Assessing exoplanet potentials
I'm gathering speculative probabilities for exoplanets like Proxima Centauri b and TRAPPIST-1 e/f/g, using the Drake equation and current understanding, to better estimate their chances of hosting a civilized society.
Refining speculative probabilities
I’m refining speculative probabilities for exoplanets, including Proxima Centauri b and TRAPPIST-1 e/f/g, to estimate their chances of hosting a civilized society, considering Earth's long biological history.
Refining odds
I'm considering the astronomical timeline for intelligent life on Earth, leading me to assign even lower speculative odds for exoplanets like Proxima Centauri b and TRAPPIST-1 e.
I’m crafting a simplified chart with arbitrary percentages, clearly noting the speculative nature and lack of scientific data, while considering the target audience's basic understanding of the topic.
I’m charting arbitrary percentages for exoplanets, clarifying their speculative nature, and ensuring the data is accessible for young audiences with minimal scientific detail.
Crafting a chart
I’m creating a markdown table with speculative percentages for the likelihood of civilized life on exoplanets, emphasizing their purely theoretical nature and considering the understanding level of an 8-year-old.
Integrating speculative analysis
I’m mapping out a markdown chart with speculative percentages for the likelihood of a civilized society on exoplanets, mindful of the complexity and simplifying for an 8-year-old's understanding.
I’m piecing together markdown for exoplanets, noting Proxima Centauri b's reduced civilized life chance due to the red dwarf's activity. This inclusion highlights the speculative nature of the analysis.
Piecing together speculative odds
I’m detailing a markdown chart for audience-friendly exoplanet likelihoods, considering environmental challenges and adding a disclaimer about the speculative nature and lack of evidence.
Piecing together
I’m leaning towards Proxima Centauri b for its proximity and silent star, but I’ll add a speculative chart ranking nearby exoplanets, noting their advanced civilizations' hypothetical likelihood.
Assessing civilization probabilities
I'm emphasizing the slow emergence of intelligent life on Earth, which suggests that the odds of any habitable planet developing a complex civilization might be as low as a few percent.
Below is a very speculative chart that—based on what we know about Earth’s long, winding path from simple life to a “civilized society” and our limited observations of nearby exoplanets—gives some fun, made‑up percentage chances for a few of our best candidate exoplanets. Remember: Scientists have not yet found any proof of life (let alone advanced civilizations) on any exoplanet. These numbers are just playful estimates to help you think about the ideas!
Speculative Chances of Finding an Advanced Civilization on Nearby Exoplanets
Exoplanet Estimated Likelihood of a Civilized Society
Proxima Centauri b ~2%
LHS 1140 b ~0.5%
How Did We (Very Roughly) Guess These Numbers?
Earth’s Example:
On Earth, life began as simple single‑celled organisms and took billions of years to evolve into a species that built complex societies. This long journey suggests that—even if a planet is in the “habitable zone” (where liquid water could exist)—developing an advanced, civilized society might be rare.
Proxima Centauri b:
This is the closest exoplanet to us. Even though its star (Proxima Centauri) is a red dwarf that sometimes sends out strong flares (which might harm life), its closeness makes it one of our most interesting candidates. That’s why we give it a slightly higher guess (~2%).
These planets are part of a group orbiting a very cool star. Their environments might be challenging (for example, they could be tidally locked, meaning one side always faces the star), so the chance of a complex, advanced civilization might be a bit lower.
LHS 1140 b:
This planet is promising in some ways but is a little farther away and around a dimmer star, so our playful estimate is even lower.
All of these percentages are extremely rough guesses based on what little we understand about the conditions for life and intelligence. Scientists use ideas like the Drake Equation to think about these chances—but until we have concrete evidence, these numbers remain just for fun and imagination.
Enjoy exploring these ideas—and remember, space is full of mysteries waiting to be discovered!
あなた:
Please examine the Drake Equation itself and see if this euqation is acculate or more opition in the equation you will use
ChatGPT
Reasoned about the Drake Equationを6 秒行う
re-examining the Drake Equation
evaluating the Drake Equation's value
OK, let me see. The Drake Equation isn't a precise formula; it's more of a guiding heuristic that tackles numerous uncertainties regarding extraterrestrial civilizations.
Thinking through the Drake Equation, I’m evaluating its conceptual nature, its uncertain parameters, and its criticism to conclude on its reliability as an accurate predictive model.
Understanding the Drake Equation
I’m mapping out the Drake Equation as a conceptual guide, detailing its parameters, which are often based on estimates or opinions, to evaluate its reliability for predicting extraterrestrial civilizations.
The Drake Equation is a famous formula that was created to help scientists think about the many factors involved in estimating the number of detectable extraterrestrial civilizations in our galaxy. However, when we look at the equation closely, we see that it is more of a conceptual framework or heuristic tool than a precise, predictive formula. Let’s break down why:
The equation is usually written as:
𝑁
=
𝑅
∗
×
𝑓
𝑝
×
𝑛
𝑒
×
𝑓
𝑙
×
𝑓
𝑖
×
𝑓
𝑐
×
𝐿
N=R
∗
×f
p
×n
e
×f
l
×f
i
×f
c
×L
Where:
𝑅
∗
R
∗
: The average rate of star formation per year in our galaxy.
𝑓
𝑝
f
p
: The fraction of those stars that have planetary systems.
𝑛
𝑒
n
e
: The average number of planets that could potentially support life per star with planets.
𝑓
𝑙
f
l
: The fraction of those planets where life actually develops.
𝑓
𝑖
f
i
: The fraction of planets with life where intelligent life evolves.
𝑓
𝑐
f
c
: The fraction of civilizations that develop technology that releases detectable signals into space.
𝐿
L: The length of time such civilizations release detectable signals.
Why the Drake Equation Is More of a Guideline Than a Precise Formula
Uncertain Inputs:
𝑅
∗
R
∗
𝑓
𝑝
f
p
(fraction of stars with planets), have become better known through modern astronomy.
The parameters related to the development of life and intelligence—
𝑓
𝑙
f
l
,
𝑓
𝑖
f
i
,
𝑓
𝑐
f
c
, and
𝐿
L—are based on very limited data. For example, Earth is the only planet we know where life has developed, so we have no way to compare or derive a statistically robust estimate for these factors. This means that the values chosen for these parameters are largely subjective estimates or educated guesses.
Wide Ranges of Possible Values:
Because many of these factors are not well-constrained, if you change one of the more uncertain parameters even slightly, the final estimate for
𝑁
N (the number of civilizations) can vary by many orders of magnitude. This wide range shows that the equation can lead to very different outcomes based on personal or theoretical assumptions.
The Drake Equation was never meant to provide a precise answer. Instead, it serves as a way to organize our thinking about what conditions might be necessary for the development of extraterrestrial civilizations. It encourages discussion about the relative importance of different factors and highlights where our scientific knowledge is limited.
Is the Drake Equation Accurate or More Opinion-Based?
Accurate?
In the sense of being a strict mathematical model with well-defined inputs and predictable outputs, the Drake Equation is not accurate. Its accuracy is limited by the extreme uncertainties in several of its key parameters.
Many of the terms in the equation, especially those concerning the evolution of life and intelligence, are based on opinion, interpretation, and the single example of Earth. Therefore, while the structure of the equation is logical, the numbers you put into it (and hence the final result) are often more reflective of our current opinions and assumptions than of robust empirical data.
The Drake Equation is a valuable tool for framing the question of extraterrestrial life. It helps scientists and enthusiasts break down a complex problem into smaller, more manageable questions. However, because several of its factors are highly uncertain and subject to personal interpretation, it is more of a conceptual guide—or even a way to stimulate discussion—than a formula that provides a definitive, accurate prediction of the number of extraterrestrial civilizations.
In summary, while the Drake Equation is useful for thinking about the various factors that might lead to the emergence of a civilization, its outputs should be taken as highly speculative estimates rather than precise measurements.
あなた:
Please also consider the possiblities of non-human intelligent emrgencing from the long history of Sol system and nearby planets and see if there is any possiblites that in one time intelligent life emerged in nearby planets and see this to the equation
ChatGPT
Reasoned about non-human intelligence and the Drake Equationを19 秒行う
Evaluating non-human intelligence
I'm thinking about the potential for non-human intelligent life forms in the Sol system and neighboring planets, and how this might factor into the equation.
Piecing together possibilities
I'm thinking about how to integrate the emergence of non-human intelligent life, possibly on Mars or Europa, into the Drake Equation for the Sol system and neighboring planets.
It's interesting to think about the hypothesis of intelligent life emerging on Mars or Venus, though Earth remains the only known life-supporting planet in the solar system.
Considering other realms
I'm examining if intelligent life could have emerged on planets like Mars, Venus, or Europa, and how this possibility aligns with the predictions of the Drake Equation.
Hmm, I’m thinking about how non-human intelligent life on Mars or Venus could intersect with the assumptions of the Drake Equation, which seems to focus solely on Earth-based evolution.
I’m piecing together the hypothesis of non-human, advanced, intelligent life in the solar system. Mars, Venus, and Titan present challenges, but Europa and Enceladus might harbor microbial life.
Please consider the histroy of humanity from biological perpsecitve and current known fact in nearby universe, which expo-planet (from the Sol system perspective) is most likely to have civlizaed society? Please add percentage next to it in the chart
ChatGPT
Reasoned about exoplanet civilization likelihoodを28 秒行う
Evaluating planetary prospects
OK, I’m looking at the likelihood of a civilized society on an exoplanet within our Solar System. I’ll consider biological history and current space knowledge, aiming to identify the most promising candidate.
Identifying potential candidates
I'm considering exoplanets like Proxima Centauri b and TRAPPIST-1e, which might suggest they are within or observed from our Solar System.
Assessing potential candidates
I’m evaluating Proxima Centauri b, Barnard's Star, LHS 1140, and TRAPPIST-1, focusing on their habitable zones and available data. The Drake equation might help estimate their civilized society likelihoods.
Identifying promising exoplanets
I’m noting key exoplanets like Proxima Centauri b and TRAPPIST-1, which have Earth-like characteristics and are in habitable zones. This narrows down the potential candidates for advanced civilizations.
I'm gathering info on planets like Proxima Centauri b and TRAPPIST-1, considering factors like magnetic fields, atmospheres, and proximity to G-type stars for their potential to support advanced civilizations.
Evaluating exoplanet prospects
I'm noting that Proxima Centauri b, despite being close and around a red dwarf star, might support life if it has a magnetic field and atmosphere. This makes me think about its potential.
Charting probabilities
I'm estimating civilization probabilities for exoplanets like Proxima Centauri b and TRAPPIST-1 e, using speculative percentages based on the Drake equation and the lack of evidence for intelligent life.
I'm crafting a chart with exoplanet names and civilization likelihood percentages, grounded in the long timeline of life's evolution, despite the speculative nature of these figures.
Identifying exoplanet contenders
I’m evaluating exoplanets like Proxima Centauri b, TRAPPIST-1 e, and Kepler-186f, considering their star types and distances, to gauge their potential for supporting advanced civilizations from our solar system's viewpoint.
Weighing proximity and observation
I'm leaning towards Proxima Centauri b due to its closeness and observational potential, despite concerns about its flare star dynamics. TRAPPIST-1 e, f, or g are also worth considering.
I'm focusing on exoplanets like Proxima Centauri b, Ross 128 b, LHS 1140 b, TRAPPIST-1 e/f/g, and K2-18b, aiming to chart their likelihood of hosting a civilized society based on current knowledge.
Assessing exoplanet potentials
I'm gathering speculative probabilities for exoplanets like Proxima Centauri b and TRAPPIST-1 e/f/g, using the Drake equation and current understanding, to better estimate their chances of hosting a civilized society.
Refining speculative probabilities
I’m refining speculative probabilities for exoplanets, including Proxima Centauri b and TRAPPIST-1 e/f/g, to estimate their chances of hosting a civilized society, considering Earth's long biological history.
Refining odds
I'm considering the astronomical timeline for intelligent life on Earth, leading me to assign even lower speculative odds for exoplanets like Proxima Centauri b and TRAPPIST-1 e.
I’m crafting a simplified chart with arbitrary percentages, clearly noting the speculative nature and lack of scientific data, while considering the target audience's basic understanding of the topic.
I’m charting arbitrary percentages for exoplanets, clarifying their speculative nature, and ensuring the data is accessible for young audiences with minimal scientific detail.
Crafting a chart
I’m creating a markdown table with speculative percentages for the likelihood of civilized life on exoplanets, emphasizing their purely theoretical nature and considering the understanding level of an 8-year-old.
Integrating speculative analysis
I’m mapping out a markdown chart with speculative percentages for the likelihood of a civilized society on exoplanets, mindful of the complexity and simplifying for an 8-year-old's understanding.
I’m piecing together markdown for exoplanets, noting Proxima Centauri b's reduced civilized life chance due to the red dwarf's activity. This inclusion highlights the speculative nature of the analysis.
Piecing together speculative odds
I’m detailing a markdown chart for audience-friendly exoplanet likelihoods, considering environmental challenges and adding a disclaimer about the speculative nature and lack of evidence.
Piecing together
I’m leaning towards Proxima Centauri b for its proximity and silent star, but I’ll add a speculative chart ranking nearby exoplanets, noting their advanced civilizations' hypothetical likelihood.
Assessing civilization probabilities
I'm emphasizing the slow emergence of intelligent life on Earth, which suggests that the odds of any habitable planet developing a complex civilization might be as low as a few percent.
Below is a very speculative chart that—based on what we know about Earth’s long, winding path from simple life to a “civilized society” and our limited observations of nearby exoplanets—gives some fun, made‑up percentage chances for a few of our best candidate exoplanets. Remember: Scientists have not yet found any proof of life (let alone advanced civilizations) on any exoplanet. These numbers are just playful estimates to help you think about the ideas!
Speculative Chances of Finding an Advanced Civilization on Nearby Exoplanets
Exoplanet Estimated Likelihood of a Civilized Society
Proxima Centauri b ~2%
LHS 1140 b ~0.5%
How Did We (Very Roughly) Guess These Numbers?
Earth’s Example:
On Earth, life began as simple single‑celled organisms and took billions of years to evolve into a species that built complex societies. This long journey suggests that—even if a planet is in the “habitable zone” (where liquid water could exist)—developing an advanced, civilized society might be rare.
Proxima Centauri b:
This is the closest exoplanet to us. Even though its star (Proxima Centauri) is a red dwarf that sometimes sends out strong flares (which might harm life), its closeness makes it one of our most interesting candidates. That’s why we give it a slightly higher guess (~2%).
These planets are part of a group orbiting a very cool star. Their environments might be challenging (for example, they could be tidally locked, meaning one side always faces the star), so the chance of a complex, advanced civilization might be a bit lower.
LHS 1140 b:
This planet is promising in some ways but is a little farther away and around a dimmer star, so our playful estimate is even lower.
All of these percentages are extremely rough guesses based on what little we understand about the conditions for life and intelligence. Scientists use ideas like the Drake Equation to think about these chances—but until we have concrete evidence, these numbers remain just for fun and imagination.
Enjoy exploring these ideas—and remember, space is full of mysteries waiting to be discovered!
あなた:
Please examine the Drake Equation itself and see if this euqation is acculate or more opition in the equation you will use
ChatGPT
Reasoned about the Drake Equationを6 秒行う
re-examining the Drake Equation
evaluating the Drake Equation's value
OK, let me see. The Drake Equation isn't a precise formula; it's more of a guiding heuristic that tackles numerous uncertainties regarding extraterrestrial civilizations.
Thinking through the Drake Equation, I’m evaluating its conceptual nature, its uncertain parameters, and its criticism to conclude on its reliability as an accurate predictive model.
Understanding the Drake Equation
I’m mapping out the Drake Equation as a conceptual guide, detailing its parameters, which are often based on estimates or opinions, to evaluate its reliability for predicting extraterrestrial civilizations.
The Drake Equation is a famous formula that was created to help scientists think about the many factors involved in estimating the number of detectable extraterrestrial civilizations in our galaxy. However, when we look at the equation closely, we see that it is more of a conceptual framework or heuristic tool than a precise, predictive formula. Let’s break down why:
The equation is usually written as:
𝑁
=
𝑅
∗
×
𝑓
𝑝
×
𝑛
𝑒
×
𝑓
𝑙
×
𝑓
𝑖
×
𝑓
𝑐
×
𝐿
N=R
∗
×f
p
×n
e
×f
l
×f
i
×f
c
×L
Where:
𝑅
∗
R
∗
: The average rate of star formation per year in our galaxy.
𝑓
𝑝
f
p
: The fraction of those stars that have planetary systems.
𝑛
𝑒
n
e
: The average number of planets that could potentially support life per star with planets.
𝑓
𝑙
f
l
: The fraction of those planets where life actually develops.
𝑓
𝑖
f
i
: The fraction of planets with life where intelligent life evolves.
𝑓
𝑐
f
c
: The fraction of civilizations that develop technology that releases detectable signals into space.
𝐿
L: The length of time such civilizations release detectable signals.
Why the Drake Equation Is More of a Guideline Than a Precise Formula
Uncertain Inputs:
𝑅
∗
R
∗
𝑓
𝑝
f
p
(fraction of stars with planets), have become better known through modern astronomy.
The parameters related to the development of life and intelligence—
𝑓
𝑙
f
l
,
𝑓
𝑖
f
i
,
𝑓
𝑐
f
c
, and
𝐿
L—are based on very limited data. For example, Earth is the only planet we know where life has developed, so we have no way to compare or derive a statistically robust estimate for these factors. This means that the values chosen for these parameters are largely subjective estimates or educated guesses.
Wide Ranges of Possible Values:
Because many of these factors are not well-constrained, if you change one of the more uncertain parameters even slightly, the final estimate for
𝑁
N (the number of civilizations) can vary by many orders of magnitude. This wide range shows that the equation can lead to very different outcomes based on personal or theoretical assumptions.
The Drake Equation was never meant to provide a precise answer. Instead, it serves as a way to organize our thinking about what conditions might be necessary for the development of extraterrestrial civilizations. It encourages discussion about the relative importance of different factors and highlights where our scientific knowledge is limited.
Is the Drake Equation Accurate or More Opinion-Based?
Accurate?
In the sense of being a strict mathematical model with well-defined inputs and predictable outputs, the Drake Equation is not accurate. Its accuracy is limited by the extreme uncertainties in several of its key parameters.
Many of the terms in the equation, especially those concerning the evolution of life and intelligence, are based on opinion, interpretation, and the single example of Earth. Therefore, while the structure of the equation is logical, the numbers you put into it (and hence the final result) are often more reflective of our current opinions and assumptions than of robust empirical data.
The Drake Equation is a valuable tool for framing the question of extraterrestrial life. It helps scientists and enthusiasts break down a complex problem into smaller, more manageable questions. However, because several of its factors are highly uncertain and subject to personal interpretation, it is more of a conceptual guide—or even a way to stimulate discussion—than a formula that provides a definitive, accurate prediction of the number of extraterrestrial civilizations.
In summary, while the Drake Equation is useful for thinking about the various factors that might lead to the emergence of a civilization, its outputs should be taken as highly speculative estimates rather than precise measurements.
あなた:
Please also consider the possiblities of non-human intelligent emrgencing from the long history of Sol system and nearby planets and see if there is any possiblites that in one time intelligent life emerged in nearby planets and see this to the equation
ChatGPT
Reasoned about non-human intelligence and the Drake Equationを19 秒行う
Evaluating non-human intelligence
I'm thinking about the potential for non-human intelligent life forms in the Sol system and neighboring planets, and how this might factor into the equation.
Piecing together possibilities
I'm thinking about how to integrate the emergence of non-human intelligent life, possibly on Mars or Europa, into the Drake Equation for the Sol system and neighboring planets.
It's interesting to think about the hypothesis of intelligent life emerging on Mars or Venus, though Earth remains the only known life-supporting planet in the solar system.
Considering other realms
I'm examining if intelligent life could have emerged on planets like Mars, Venus, or Europa, and how this possibility aligns with the predictions of the Drake Equation.
Hmm, I’m thinking about how non-human intelligent life on Mars or Venus could intersect with the assumptions of the Drake Equation, which seems to focus solely on Earth-based evolution.
I’m piecing together the hypothesis of non-human, advanced, intelligent life in the solar system. Mars, Venus, and Titan present challenges, but Europa and Enceladus might harbor microbial life.
同じコードを数年前にExcelVBAでしこしこ作ってたのがなつかしい
function Zip-Subfolders { param( [string]$directory ) # 指定されたディレクトリ内のサブフォルダを取得 $subfolders = [System.IO.Directory]::GetDirectories($directory) | % { [System.IO.DirectoryInfo]::new($_) } foreach ($folder in $subfolders) { # 圧縮ファイルの保存先パス $zipFilename = "$($folder.Name).zip" $zipFilepath = Join-Path -Path $directory -ChildPath $zipFilename # サブフォルダをZIP圧縮 Write-Host "圧縮中..." [System.IO.Compression.ZipFile]::CreateFromDirectory($folder.FullName, $zipFilepath) Write-Host "$zipFilepath に圧縮しました。" } } # ユーザーにフォルダパスを入力させる $folderPath = Read-Host "圧縮する親フォルダのパスを入力してください" # パスが存在するか確認 if ([System.IO.Directory]::Exists($folderPath)) { Zip-Subfolders -directory $folderPath }
Programming proficiency necessitates a comprehensive understanding of multifaceted concepts, paradigms, and philosophies that underpin the art and science of software development. The Unix philosophy, with its emphasis on modularity, simplicity, and composability, serves as a foundational ethos for elegant code design. This philosophy advocates for creating small, focused programs that excel at singular tasks, facilitating the construction of complex systems through the judicious composition of these atomic units.
Proficient programmers must possess an encyclopedic knowledge of algorithms and data structures, enabling them to architect solutions with optimal time and space complexity. This encompasses a deep understanding of sorting algorithms (e.g., quicksort, mergesort), searching techniques (binary search, depth-first search), and advanced data structures (red-black trees, B-trees, Fibonacci heaps) The ability to analyze algorithmic efficiency using Big O notation is paramount for creating scalable solutions.
OOP principles—encapsulation, inheritance, and polymorphism—form the bedrock of modern software architecture. Mastery of design patterns (e.g., Singleton, Factory, Observer) and SOLID principles is crucial for creating maintainable and extensible codebases.
The FP paradigm, with its emphasis on immutability and pure functions, offers a powerful approach to managing complexity and facilitating parallel execution. Proficiency in higher-order functions, currying, and monads is essential for leveraging FP's full potential.
Expertise in language-specific advanced features, such as C++'s template metaprogramming or Python's metaclasses, allows for the creation of highly generic and reusable code. Understanding compiler theory and the ability to write domain-specific languages (DSLs) further expands a programmer's capabilities.
In an era of multi-core processors and distributed systems, mastery of concurrent programming models (e.g., actor model, communicating sequential processes) and parallel algorithms is indispensable. This includes proficiency in lock-free data structures, memory models, and synchronization primitives.
A deep understanding of computer architecture, operating systems, and memory management enables the creation of highly optimized, low-level code. This encompasses knowledge of cache coherence protocols, CPU pipeline optimization, and assembly language programming.
In an increasingly interconnected world, a thorough grasp of cryptographic principles, secure coding practices, and common attack vectors (e.g., buffer overflows, SQL injection) is crucial for developing robust and secure systems.
Proficiency in distributed version control systems (e.g., Git) and collaborative development practices (code reviews, continuous integration) is essential for effective team-based software development.
Advanced testing methodologies, including property-based testing, fuzzing, and formal verification techniques, are indispensable for ensuring software reliability and correctness.
In conclusion, the pantheon of programming knowledge extends far beyond mere syntax mastery. It encompasses a rich tapestry of theoretical concepts, practical skills, and philosophical approaches that, when harmoniously integrated, enable the creation of elegant, efficient, and robust software systems. The relentless pursuit of this multifaceted expertise is the hallmark of a truly accomplished programmer.
https://www.geonames.org から取れる、人口500人以上の都市の名前に限定すると、
Santa Maria Magdalena Cahuacan
import logging import tempfile import zipfile from collections import Counter import httpx FILE_NAME_BASE = 'cities500' GEONAME_FIELDS = ( 'geoname_id', 'name', 'ascii_name', 'alternate_names', 'latitude', 'longitude', 'feature_class', 'feature_code', 'country_code', 'cc2', 'admin1_code', 'admin2_code', 'admin3_code', 'admin4_code', 'population', 'elevation', 'dem', 'timezone', 'modification_date', ) def retrieve_cities(): """Retrieve city names from a remote server.""" response = httpx.get(f'https://download.geonames.org/export/dump/{FILE_NAME_BASE}.zip') response.raise_for_status() tmpdir = tempfile.TemporaryDirectory() with open(tmpdir.name + f'/{FILE_NAME_BASE}.zip', 'wb') as f: f.write(response.content) with zipfile.ZipFile(tmpdir.name + f'/{FILE_NAME_BASE}.zip', 'r') as z: z.extractall(tmpdir.name) with open(tmpdir.name + f'/{FILE_NAME_BASE}.txt', 'r') as f: for line in f: yield line.split('\t') def count_characters(to_check='ascii_name', filter_func=lambda _: True): """Count characters in city names.""" cities = {} for city_fields in retrieve_cities(): city = dict(zip(GEONAME_FIELDS, city_fields)) if not filter_func(city): continue counter = Counter() for c in city[to_check]: counter[c] += 1 cities[city['geoname_id']] = {'characters': counter, 'city': city} return cities def count_chars_of_city_names(cities, char=None): """Find the city with the most occurrences of a given character.""" cities_by_char_count = {} max_count = 0 max_count_char = None for city_id, data in cities.items(): if 'characters' not in data or not data['characters']: logging.debug(f'No characters found for city {city_id}', data) continue count = 0 if char and char in data['characters']: count = data['characters'][char] cities_by_char_count.setdefault(count, []).append(data) elif char is None: most_common = data['characters'].most_common(1)[0] char, count = most_common cities_by_char_count.setdefault(count, []).append(data) if count > max_count: max_count = count max_count_char = char cities_by_char_count.setdefault(count, []).append(data) return cities_by_char_count.get(max_count, []), max_count_char def not_contain_invalid_chars(city): return ( '(' not in city.get('ascii_name', '') and '/' not in city.get('ascii_name', '') ) def main(): cities = count_characters(filter_func=not_contain_invalid_chars) for char in 'abcdefghijklmnopqrstuvwxyz': cities_counted, char = count_chars_of_city_names(cities, char) max_count = cities_counted[0]['characters'][char] print(f'The character "{char}" appears the most ({max_count} times) in the following cities:') for city in cities_counted: print("\t", city['city']['ascii_name']) if __name__ == "__main__": main()
import os
# ファイルが存在するか確認し、存在しない場合は初期値を設定
if not os.path.exists(file_path):
with open(file_path, 'w') as file:
# 現在の年数を読み込み
with open(file_path, 'r') as file:
year_count = int(file.read())
# メッセージを表示
print(f"{year_count}年間で最も暑い夏")
with open(file_path, 'w') as file:
file.write(str(year_count + 1))
インデントつけれね
It's sudden, but right now in Japan, creativity is facing a true crisis. Characters like Uzaki-chan, Onsen Musume, and Tojo Rika are being targeted and flamed, game character designs are being infiltrated by political correctness, Johnny's Entertainment is being dismantled, swimsuit photo sessions in parks are being canceled, Hitoshi Matsumoto is being publicly shamed, and the new AV law was enacted without considering the opinions of those directly involved. Every form of expression in every venue is currently under unreasonable pressure.
How does this connect to the Tokyo gubernatorial election? In fact, a major event directly linked to this is occurring in the 2024 Tokyo gubernatorial election. As a creator, I hope this message reaches you.
What I am about to share is a story about someone named Himasora Akane, who you should know about to resist such pressures. But before I dive into that story, I want to express my deep gratitude to my old friend Nozomi for giving me the opportunity to post this article in a place where many creators will see it. As someone who also loves manga, anime, and games, I hope this information will benefit Japanese society and support Nozomi's activities.
Himasora Akane Should Be the Governor of Tokyo
First, I would like to make a straightforward request to you as a creator: please support Himasora Akane for governor. In this election, please write "Himasora Akane" on your ballot. The voting day is July 7th. Even if you are not a Tokyo resident, I ask that you at least listen to this story. If you find it interesting, please share it with your friends, family, and acquaintances. You can check Himasora Akane's campaign promises and the background of their candidacy on their Twitter (X) posts linked below:
Himasora Akane (Tokyo gubernatorial candidate)
https://x.com/himasoraakane/status/1804846779399324095
Himasora Akane Will Not Allow Our Culture to Be Burned
Himasora Akane is an ordinary otaku who loves manga, anime, and games. Known as "Cognitive Profiling Detective Akane Himasora," he has been active on Twitter (X) and YouTube, and now he is running for governor. Akane, who is deeply concerned about the repression and destruction of otaku culture, is challenging those who seek to destroy our culture alone. Akane will never allow those who try to burn our culture.
As mentioned at the beginning, all forms of expression are currently under pressure. Otaku culture, in particular, seems to be a prime target.
Uzaki-chan Blood Donation Poster Controversy (2019): A collaboration between the Japanese Red Cross Society and the manga Uzaki-chan was flamed for allegedly being overly sexual in its PR illustration.
V-Tuber Traffic Safety Video Controversy (2021): A V-Tuber hired by the Matsudo Police Department in Chiba Prefecture was deemed too sexual for public agency PR.
Onsen Musume Controversy (2021): Characters personifying local hot springs were criticized as sexist.
Mie Transport Official Character Controversy (2024): A character in a bus driver's uniform released by Mie Transport was flamed for evoking sexual images.
These controversies are often fueled by so-called political correctness and feminism. For creators, these are direct threats. If these factions label your work as sexual and demand it be burned to ashes, could you resist? How would you feel if your painstakingly created work, like your own child, was trampled by people who have no regard for your efforts? Could you continue your creative activities while constantly shrinking away?
Himasora Akane saw something behind these flaming incidents. He started investigating the key figure behind the Onsen Musume controversy, a representative of a general incorporated association in Tokyo. This association's core business, the Young Female Victims Support Project, received substantial public funds from Tokyo. Akane submitted public document disclosure requests to Tokyo and thoroughly dug into the organization. During his investigation, Akane uncovered many suspicions suggesting this project was unworthy of public funding, which he exposed one by one on social media.
Negligent accounting reports, taking protected girls to the Henoko base protest in Okinawa, Communist Party members waiting in the bus used to protect girls—these revelations drew significant attention online. The investigation extended beyond this general incorporated association to other NPOs receiving public funds, and Akane named this cluster of issues the "WBPC problem" after the initials of these organizations.
Akane's YouTube Channel (WBPC Problem Playlist)
https://www.youtube.com/playlist?list=PLI5gTciLKtAXRyzv9j5FiNMcc8eoEBbMN
From here, Akane's story expanded to resident audits, resident lawsuits, and national compensation lawsuits concerning the Tokyo Young Female Victims Support Project. Akane discovered that behind many flaming incidents, there is no clear command structure but a group of various political organizations and activists working together like an amoeba. He named this group the "Nanika Group" (Nanika means "something" in Japanese), a reference to the mysterious, ominous "something from another place" in the manga HUNTER×HUNTER, which Akane loves. The Nanika Group is also connected to welfare interests, where public funds flow unchecked. Akane called this phenomenon "Public Fund Chu-Chu" (siphoning).
For creators, this means the tax money they earn through hard work is used to burn their precious works. It's an intolerable situation.
Himasora Akane Is Fighting Against Those Who Burn Our Culture
In November 2022, a major event marked a turning point in this series of controversies. The general incorporated association under scrutiny held a press conference at the parliamentary office building, gathering media and announcing a lawsuit against Akane. This "Legal Harassment Press Conference," as it was called online, involved multiple layers of power: the government, the media, and a team of seven lawyers targeting a single individual.
However, Akane did not back down. Instead, he intensified his pursuit, exploiting the opponent's careless statements as lawsuit fodder. This led to an outpouring of support on social media, with his Twitter follower count skyrocketing and 160 million yen in donations for legal fees.
The following year, a resident audit request filed by Akane resulted in Tokyo's official website recognizing some improper points and deciding to audit the organization. However, Tokyo's lenient audit led Akane to file a resident lawsuit. Suspicion also turned towards Governor Yuriko Koike for allocating public funds through dubious sole-source contracts. Tokyo began excessively redacting documents in response to public document requests, attempting to conceal the issue. Koike's promise to end document redaction quietly disappeared from her campaign page.
Throughout this battle, Akane has been a target of criminal complaints and faced threats, yet he persists. His book "Netoge Senshi" was released amid bookstore threats, but only the criminal complaint was widely reported by the media, portraying Akane negatively.
Himasora Akane is an ordinary otaku, a top-tier online gamer during his student days, and a talented game creator who worked for a major game company and later a venture company. His meticulous work on the game "Shin Goku no Valhalla Gate" was betrayed by the company's CEO, leading to a seven-year legal battle that Akane ultimately won, securing 600 million yen. This experience fuels his fierce opposition to having his creations burned.
Before investigating the Young Female Victims Support Project, Akane exposed fraudulent feminist "knights" on his YouTube channel, shaking the internet. He detests lies and has an uncanny ability to detect them.
Akane is a special individual with extraordinary abilities, honed through his experiences in games, court battles, and extensive document analysis. His pursuit of truth and justice makes him a suitable candidate for governor, promising a world without lies and where honest people do not suffer.
What We Can Do to Protect Our Culture
Creative expression can be crushed if we are not vigilant. Even in modern Japan, otaku culture is on thin ice. The recent cessation of Visa transactions for DMM (Fanza) is a reminder of how a single card company can wield its power to dictate what is deemed appropriate expression. Expression freedom is fragile and constantly under threat.
To those reading this, I urge you to vote for Himasora Akane. Support him to protect our culture. Despite his harsh demeanor and preference for solitary battles, he is now seeking help for the first time. Akane feels the danger in this gubernatorial election and believes that if he does not become governor, everything will end. He has taken a stand for the people of Tokyo and Japan.
I wrote this article to support his spirit and spread the word. Please vote for Himasora Akane and help create a miracle.
To you, the creator, I sincerely hope this message reaches you.
I am not a gambler, but I would like to stay with Ippei Mizuhara in a hotel in an entertainment district in the middle of the desert.
He and I would never gamble.
But as he grips the slot lever with his buttocks tightened, I secretly burn with jealousy as I watch the pile of medals that gradually emerge from the seat next to me.
I would shift in my seat and play poker. I try desperately to drive the anxiety from my face, to imagine the joy of victory, but I know it is pointless.
And I will return to my original seat, angry and sad.
Sometimes we will look at each other over the baccarat table. In those moments, we would tell each other our own moves in the blink of an eye, and we would take care that one of us would win.
One day one of us will be penniless and the other will bury him outside the city. Then he will write a little poem to his friend who has traveled, and then he will kill himself, having found no reason to live without a last-minute bargaining chip.
私はギャンブルの依存症ではありません、ですが、水原一平さんと一緒に砂漠の真ん中にある歓楽街のホテルに泊まりたいです。
私と彼は賭け事をすることはないでしょう。
しかし彼が臀部を引き締めながらスロットのレバーを握るとき、次第に出てくるメダルの山を、隣の席で見ていた私は密かに嫉妬の炎を燃やします。
私は席を移って、ポーカーをするでしょう。私は不安感を表情から追い出そうと、必死に勝利の喜びを想像しますが、それが無意味なことを知っています。
最終的に私は勝てないでしょう。
そして私は怒りと切なさを感じながら元の席に戻ります。
時々私たちはバカラのテーブル越しに目配せしあうことがあるでしょう。その瞬間、私たちは自分自身の手の内を、瞬きの回数で教え合い、そしてどちらかが勝てるように配慮していくのです。
ある日、私たちの一人が無一文になり、もう一人が街の外に彼を埋めます。それから彼は旅だった友人にちょっとした詩を書いて、そしてギリギリの駆け引きなしには生きる理由を見出せずに自殺するでしょう。
Could you check my sentence? Grammar and 単数形、複数形 and so on. Re write please.
I think career planning is not essential for a successful work life especially for woman. I would like to show example in Japan.
In Japan usually woman starts their carrier after graduated from the university. I saw statistics shows that woman’s salary starts from 1 to 3 million yen in the biggening. The peak of the salary will be around the age of 25 as 5 to 6 million yen. After that it will drop harshly to 100 million to 0 yen. Why we have this huge drop?
The reason is that most of Japanese woman retire after their marriage called “Hanayome Taisha” and some of them will be housewives, that means no longer to continue their carrier. However, these days it is very hard to live rely on man’s income to live in metropolis. Some of woman start working as a part timer to take care of their children while husband works fulltime and this makes woman not to be able to paid well. The statics shows that woman’s carrier restart between 30 to 35 years old but the salary will not be the peak like their 20s anymore. From these statistics, I think woman’s carrier depends on what kind of lifestyle they want.
ChatGPT
I think career planning is not essential for a successful work life, especially for women. I would like to provide an example from Japan.
In Japan, women usually start their careers after graduating from university. Statistics show that women's salaries start from 1 to 3 million yen at the beginning. The peak of their salary is typically around the age of 25, ranging from 5 to 6 million yen. However, after that, it drops sharply to 100 million to 0 yen. Why do we see this huge drop?
The reason is that most Japanese women retire after getting married, a phenomenon called "Hanayome Taisha," and some become housewives, meaning they no longer pursue their careers. However, these days it is very hard to rely solely on a man's income to live in a metropolis. Some women start working as part-timers to take care of their children while their husbands work full-time, which results in women not being paid well. Statistics show that women's careers restart between 30 and 35 years old, but the salary is not at its peak like in their 20s anymore. From these statistics, I believe a woman's career depends on the kind of lifestyle they want.
why you use women ? I used woman.
ChatGPT
I used "women" instead of "woman" because your original text seemed to refer to women in general, rather than a specific individual. When discussing women as a group, it's more common to use the plural form. However, if you prefer to use "woman" to refer to women in general, I can adjust the text accordingly.
英会話スクールに払うお金がもったいなく感じ始めて、退会してしまいました。私のような低収入の人間とって、節約は生活の要です。
収入を増加させるために英語を習おうと考えましたが、効果のない学習にお金を払ってももったいないのです。それなら英語学習用のアプリを無料で試した方がまだ効果的というものでしょう。
といっても、Duolingoは簡単すぎて、まったく勉強になりません。私はリーディングであればWeb記事をすらすら読むことができる程度の英語力があるようです。
なので鍛えたいのはスピーキング、リスニング、ライティングです。ライティングであれば、ケンブリッジのWrite and Improveというサイトがあります。
リスニングについては英語コンテンツをYoutubeで視聴すれば良いでしょう。スピーキングについても、スピーキング練習用のコンテンツがYoutubeに転がっています。
このようにして、無料で十分学習コンテンツは存在するのです。しかし、33歳にもなって、英語力を身につけて転職を成功させるなど可能でしょうか。
給料を上げる一番簡単な方法は、労働時間を増やすことです。私は短時間勤務で働いているので、これをやめれば給料は増えるのです。
今のようにリモートで働けて、仕事がそれほどキツくなく、給料がもっともらえるような、プログラミングの仕事はないのでしょうか。
やはり足るを知るべきかもしれません。もし私が結婚をすることを考えるのであれば、給料をもっと増やした方が良いでしょう。
しかし結婚を考えないのであれば、お金を使う先もないので、わざわざ転職する必要はないとも思うのです。転職するとしたら、今の会社が潰れた時です。
さて、私はなぜ英語を習うんでしたっけ？
オリジナルの文を見ると
Laziness: The quality that makes you go to great effort to reduce overall energy expenditure. It makes you write labor-saving programs that other people will find useful and document what you wrote so you don't have to answer so many questions about it.
怠慢: 全体的なエネルギー消費を削減するために「多大な努力」をすること。他の人が役に立つと思うような省力化プログラムを書き、書いたことを文書化して、それについて多くの質問に答える必要がなくなる。
It's an amazing time to be able to casually write Masuda in English like this.
I can't read or write in English.
Of course, I am Japanese, so I can understand the level of English I learned at school.
But writing in English is a bit different from that, isn't it?
I am not a Japanese person, so I can understand what I learned in school, but that is a little different from writing in English.
What a wonderful world we live in!
僕はプログラミング歴2週間の初心者です。キーと値を入力できるデータベースを作っています。
以下のコードを実行してデータを追加し続けると、一定のサイズを超えるとエラーが出てしまうみたいです。
理想は、データが追加された後にサイズが足りなくなったら動的に自動拡大されることです。
もし詳しい人がいたらご教示お願い致します。
import sys import os import mmap import hashlib def h(x): return int(hashlib.sha512(x.encode()).hexdigest(), 16) def create_db(filename): with open(filename, 'wb') as f: f.write(b'\0' * 1024 * 1024) # 1MBの空ファイルを作成 def set_key(filename, key, value): with open(filename, 'r+b') as f: mm = mmap.mmap(f.fileno(), 0) pos = h(key) % mm.size() while mm[pos:pos+1] != b'\0': pos = (pos + 1) % mm.size() if pos == h(key) % mm.size(): f.seek(0, os.SEEK_END) f.write(b'\0' * mm.size()) # ファイルサイズを2倍にする mm = mmap.mmap(f.fileno(), f.tell()) # ファイルサイズを反映させる pos = h(key) % mm.size() # ハッシュ値を再計算する data = key + '\0' + value + '\0' data = data.encode() mm[pos:pos+len(data)] = data mm.close() # mmapオブジェクトを閉じる def get_key(filename, key): with open(filename, 'r+b') as f: mm = mmap.mmap(f.fileno(), 0) pos = h(key) % mm.size() while mm[pos:pos+1] != b'\0': end = mm.find(b'\0', pos, mm.size()) # 第2引数と第3引数を指定する if end == -1: end = mm.size() if mm[pos:end].decode() == key: pos = end + 1 end = mm.find(b'\0', pos, mm.size()) # 第2引数と第3引数を指定する if end == -1: end = mm.size() value = mm[pos:end].decode() mm.close() # mmapオブジェクトを閉じる return value pos = (pos + 1) % mm.size() if pos == h(key) % mm.size(): break mm.close() # mmapオブジェクトを閉じる return None def main(): cmd = sys.argv[1] if cmd == 'create': create_db(sys.argv[2]) elif cmd == 'set': set_key(sys.argv[2], sys.argv[3], sys.argv[4]) elif cmd == 'get': print(get_key(sys.argv[2], sys.argv[3])) if __name__ == '__main__': main()
megumin1 一般にはfdがterminalだと行単位でflushされる、結果write等のsyscallの回数が増えるなどの違いがありますよ。まずはその辺りから疑うべき話だと思うのですが、記事中で一切言及がないのはつまりはそういうことでしょうか？
https://b.hatena.ne.jp/entry/s/qiita.com/ko1nksm/items/f6c033c194935b642a39
つまりバッファリングの問題だということ…… ではないよね。日本語的に考えて。
はてなのテクノロジーの人気記事人気コメントでも、何だかよく分からない含みのあるコメントが最近増えてきた気がするのは俺だけかな。支持してる人たちは何を意味してる（と思った）のか解説してほしい。
フタ・ピェニャツカの虐殺
Zbrodnia w Hucie Pieniackiej – Wikipedia, wolna encyklopedia
https://pl.wikipedia.org/wiki/Zbrodnia_w_Hucie_Pieniackiej
人口1000人ほどのポーランド人が住むフタ・ピェニャツカ村で、ドイツ軍から命令を受けたウクライナ人親衛隊が、周辺から避難してきた市民を含めて500人～1500人を虐殺した事件。
各国の思惑から被害調査がされずにいたが、2000年代にポーランドとウクライナがそれぞれ調査報告書を出し第14SSによる虐殺と認められた。（両国間で被害人数に差がある）
日本語版には項目が単独では無い。（第14SS武装擲弾兵師団の項目に小見出しで解説されている）
だからカナダ議会が元ナチスでこの部隊にいたウクライナ移民のカナダ人を称えた件について、ポーランドが激怒した。ポーランドの教育大臣は旧ツイッターで「彼をポーランドに引き渡すことをカナダに要求する」と投稿した。
「非常に傷ついた」：ポーランド大使、ナチス退役軍人のカナダ議会への招待を非難
Polish envoy condemns Nazi veteran invite to Canada's Parliament | CTV News
「カナダ議会において、ゼレンスキー大統領も同席のもと、ナチスの犯罪組織SSガリツィエンのメンバーを称えるというスキャンダラスな出来事があったことから、私はこの人物のポーランドへの引き渡しの可能性に向けた措置を講じた。」
Wobec skandalicznych wydarzeń w kanadyjskim parlamencie polegających na uhonorowaniu w obecności także prezydenta Zełenskiego członka zbrodniczej, hitlerowskiej formacji SS Galizien, podjąłem kroki w kierunku ewentualnej ekstradycji tego człowieka do Polski.… https://t.co/92qK1voktN pic.twitter.com/5J4lljH5JX— Przemysław Czarnek (@CzarnekP) September 26, 2023
この問題は何もロシア侵攻が起きたから騒ぎになっているわけではない。ウクライナ系移民を多く抱えるカナダの「戦争犯罪問題」としてずっと前から議論されていたことだ。
October 30, 2020
Whitewashing The SS: The Attempt to Re-Write the History of Hitler’s Collaborators — espritdecorps
カナダでは1985年にWW2の戦争犯罪人に対する調査をした。この報告書が現在も「カナダの歴史問題」に影響を及ぼしている。
Deschênes Commission - Wikipedia
https://en.wikipedia.org/wiki/Desch%C3%AAnes_Commission
第14SS武装擲弾兵師団の集団的戦争犯罪を無罪とした委員会の決定は、特に物議をかもした。SSはすでに以前の戦争犯罪裁判で、組織としての戦争犯罪を犯したと判断されていたからである。
ant(アリ) aunt(叔母)
bear(クマ) bare(裸の・むき出しの)
break(壊す) brake(ブレーキ)
eye(目) I(私)
for(〜のために) four(4)
hear(聞く) here(ここ)
heel(かかと) heal(～を癒す)
meet(会う) meat(肉)
one(1) won(勝った)
our(私たちの) hour(時)
right(正しい・右) write(書く)
see(～を見る) sea(海)
tail(しっぽ) tale(物語)
two(2) too(〜も・〜すぎる)
wait(待つ) weight(重さ)
weak(弱い) week(週)
The fact you speak more definitively in a formal setting, and the fact "going to" is informal (or not) are 2 different things. Cambridge dictionary is correct in that "going to" is used in more informal setting. It's that YOU are reading it wrong. It is not an informal expression. And by the way, some people take being proficient in one language not being in another, but they can actually co-exist. I write more in English than Japanese. Have been for over 10 years.
英検SCBTという1日で受けれるヤツをやった。
最初にスピーキング（マイクに吹き込む）、次にリスニング（ヘッドホン装着）、最後にリーディングとライティング。
でも他はボロボロ。英検二級は簡単に受かったから次は準一級頑張るぞー、くらいの気持ちで受けたら全然難しくてビックリした。
調べてみたら英検二級はTOEIC換算で550くらい、準一級で785点くらいらしい。
そりゃ難しいわ……こちとら最後に受けたTOEIC400点やぞ……でも成長はしてるっぽいから嬉しい。
I had taken the Eiken SCBT test because it takes one day.
First is the speaking part(speaking for the mic)
Second is the listening part(Wearing the headphone)
The last two are the reading part and the writing part.
I passed only the speaking part as the result.
However, I bombed other parts so badly.
I could pass the Grade 2 easily then I assumed I can pass Grade Pre-1 it, but it was really difficult for me.
According the result of Google, Eiken Grade 2 is about 550 of TOEIC and Pre-1 is about 785 of TOEIC.
No wonder... My TOEIC score was 400... However, I am glad because my EN skill grows that I felt,
As a practice of my studying English of the writing, I tried to write this diary in English.