  |
はてなキーワード: Aimingとは
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.
・崩壊：スターレイル：説明不要 HoYoverseの看板タイトル
・アズールレーン：中国開発タイトルを日本に拠点を構えたYosterがローカライズで大成功
・ブルーアーカイブ：ヲタク心を掴む事に成功、色々あってユーザー増加
・鳴潮：Kuro Gameが投入した新規IP、ストーリーは人を選ぶが秋葉原でのイベント等が盛況
これらに加え更に複数タイトルが近々リリース予定、破竹の勢いで開発が行われる
対する
■日本勢
■セガ & Colorful Palette(旧Craft Egg)
アクティブ数１年で半減、ただの音ゲなので今後の新規獲得難しく
６月に起きた作曲者ぷす氏の殺人未遂で逮捕が追い打ちからの全楽曲削除
・馬娘プリティダービー：コナミのパワプロアプリをパクリすぎてコナミと特許侵害で争っている最中
・馬娘プリティダービー熱血ハチャメチャ大感謝祭（ウマ娘版くにおくん）
steam版では完全に空気、steamが過疎すぎてマッチすらせず、ゲームとしての評価すらされていない状況
初月５億以下の売上で爆死、集客、及び課金者への配慮何もかもが上手くいかず
・リリステ
平均１００位～２００位をうろうろ：爆死 アニメ放送バフがあり、集英社が絡んで起きながらこのザマ
■任天堂
腋の甘さゆえにパルワールドの登場を許してしまう。この後、訴訟問題に
・とある魔術の禁書目録 幻想収束（イマジナリーフェスト）
２０２４年１２月にサービス終了が決定
・ロマサガ２
・打ち切りタイトルは130本と余りに多い事から誰もスクエニ製ソシャゲに手をださなくなる
・エンバーストーリア
「本当に令和のゲームか？平成のゲームだろ」等の声が多数あがってしまう
・FF14（番外）
グラフィック班をこれまで携わってきた中国チームから日本内製に切り替えたところその質が低下
モバイル版を
ポリコレに屈し改悪要素多数、この会社自体、スイートベイビーの公式サイトにスクエニの名前を載せていた事実もあり
既に利権団体の犬となっているので開発ごときは社の方針に逆らなかったか
本来であればクール・ジャパンでこの分野は日本の企業が独占的に支配していなければなかったのではないですか？
日本のアニメが好きというだけの中国人達が作ったゲームサービスにこうも簡単に負けるって
一体今まで何をしてきたのでしょう？ 日本の企業、経営者は何にお金を使ってきたのでしょう？
ネトウヨが原因らしいです
マリオと言えば変身。
キノコを食べて大きくなったスーパーマリオ、フラワーを食べて火を出せるファイアーマリオなどがいます。
産みの親である宮本茂だって、色々なものを食べて変身できるに違いありません。
変身した宮本茂さんにもっと色んなマリオを作ってもらいましょう。
遊ぶたびにステージが変わり1000回遊べる不思議なマリオを作れる。
・秋元才加を食べて広井茂
ハイクオリティな映像美が堪能できるアニメーションが流れ大正桜に浪漫の嵐なマリオ大戦を作れる。
高速感が売りの時代が求めた16ビットなマリオザヘッジホッグを作れる。
ボールに入ったマリオを動かすたべごろなマリオボールを作れる。
16連射でなんかする。
家でも買いたかったんだろうかね
一時金ボーナスのために逮捕されるような危ない橋を渡るのは、そういう社員だったってことでしょう
インサイダーの警告も当然のごとく社内でトレーニングされてるはずだし
スクウェア・エニックス（スクエニ）は、オンラインゲーム制作会社「Aiming」（渋谷区）と共同で「ドラゴンクエストタクト」を制作。Aimingが2020年2月に共同開発を発表し、ゲームは同年7月に配信された。
発表によると、佐崎容疑者は、共同開発の公表前だった19年11月下旬、ゲーム開発が配信を見込める段階まで進んでいたことや、Aimingがスクエニとの業務提携を決定したという重要事実を把握した。そのうえで19年12月上旬～20年2月上旬、自身の名義でAimingの株を計約7万2千株、約2080万円で買い付けた疑いがある。
さらに知人の鈴木容疑者にも利益を得させようと、情報を19年12月下旬に伝えた。鈴木容疑者は自身の名義で計約9万のAiming株を約2640万円で購入した疑いがあるという。
関係者によると、佐崎容疑者は共同開発チームのメンバーだった。2人は共同開発の公表でAimingの株価が上がった後に売り抜け、合わせて数千万円の利益を得たという。
https://georgebest1969.typepad.jp/blog/2020/03/事実に誠意を.html
これが原文です。
外国から問い合わせが来ているけれども時間がなくて訳せないということで、DeepLの性能確認ついでにやってみました。
この私訳と岩田健太郎先生は無関係なのでよろしくお願いします。
訳された文章を原文と見比べ、翻訳で文章がおかしくなったところや慣用句は「必ず日本語側の文章をいじることで」できるだけ解消しました。
よって改変した文章だけをこちらに載せ、改変する必要がなかったところは段落番号しか載せていません。元文章は元ブログを当たってください。
英語に詳しいパーソンが精査していただけると幸いです。
1 Most of what I'm about to write is no different from what I've said and done in the past. However, I have been asked the same question repeatedly, so I would like to reiterate it. We have received many inquiries from overseas as well, so we should have prepared the same content in English, but due to time constraints, I'm afraid I'll have to skip it. This article is designed to be read without basic knowledge of infectious diseases and jargon, but it is rather difficult to understand. Please forgive me for that.
感想：「Chromeかなにかでそれぞれ母国語に訳してお読みいただけると幸いです。」がきれいさっぱり消えている。DeepLの自負心だろう。
2 The fact that the number of COVID-19 reports in Japan is very low compared to other countries is attracting attention from home and abroad. Is it true? It has been pointed out that the number of tests is so small that we may be misreading the actual number of infected people.
3 However, this point is wrong at various layers. In the first place, Japan does not aim to capture all the numbers of COVID-19. Whether it's administrative testing or insured care, the state basically has a testing strategy in mind to diagnose, hospitalize, and isolate critically ill patients who need to be hospitalized. It is natural that they "haven't figured it out" and they don't intend to. That's not a bad thing.In fact, the situation is the same in every country, large or small, and no country, whether in the United States, Europe, or Asia, is aiming to "capture the whole number.
感想：最後の文はなぜか他の文と一緒に入力すると訳してくれなかった。この文一つだけ入力すると訳してくれた。
よく考えると「多かれ少なかれ」は通じないだろうから直した方がよかった。なぜかDeepLに繋がらなくなったのでもう直せない。
WHOもそんなことは求めていない。もっとも、そのわりに日本は帰国者無症状者にPCRをやってみたり、無症状な検査陽性者を入院隔離させてみたり（軽症者は自宅じゃなかったの？）、プリンシプルにおいて首尾一貫していない。だから、「彼らがなにがやりたいか私たちはよくわからない」ので、人々は不安になる。リスコミにおける失敗と言えよう。
The WHO is not asking for such a thing. But instead, Japan gives PCR to asymptomatic returnees and isolates asymptomatic test-positive people in hospital (wasn't it home for people with minor illnesses?). It has not been coherent in its principles. So, people get anxious because "we're not sure what they want to do". It's a failure in the press.
感想：「なにがやりたいかよくわからない」に主語を付与する必要があった。リスコミがpressになった。よくわかったな。
「〜は自宅じゃなかったの？）、」の、が.になっているのがよくわからない。なぜかDeepLに繋がらなくなったのでもう直せない。
4 The difference between Korea and Japan is the "result" and not the "purpose". In South Korea, where the number of infected people had surged in one place, we had to focus on inspections in and around the area. If such a phenomenon (let's call it an overshoot) occurs in Japan, the number of inspections will increase. When the situation is different, arguing only on the basis of the number of tests without observing the situation is like trying to say, "That team made 50 sliding tackles while this team made only one," without watching a football game. In games where you don't have to slide (e.g., when you're in possession the whole time), even 0 times isn't a "mistake," and of course 50 times isn't a mistake.
5 全数把握ができていない疾患など山のようにある。日本ではインフルエンザの「全数」把握はしておらず、定点観測である。疫学上、感染対策上、それで十分な情報が得られているからだ。日本で毎年風邪が何例発生しているか、正確に把握したデータはない。レセプトデータを見ればわかるじゃないか、というのも間違いで、なぜなら多くの風邪患者は（ぼくのように）受診せずに自然に治るまで待っている。医療に限らず、経済学でも政治学でもデータはサンプリングから母数を推定するのがほとんどで、「全数」は非効率的な状態把握法なのだ。
There are many diseases for which the total number of patients is not known. In Japan, we do not have a "total" number of influenza cases, but only a fixed-point observation. Because that's enough information, both epidemiologically and in terms of infection control. There is no accurate data on how many cases of the common cold occur each year in Japan. It's also a mistake to say that you can tell by looking at the receipt data, because many cold patients (like me) don't see a doctor and wait until they are cured naturally. Not only in medicine, but also in economics and political science, data are mostly based on sampling to estimate population numbers, and "whole numbers" is an inefficient way of grasping the situation.
感想：ちょこちょこ変えてある。日本語の文章が多少おかしくなっているのは勘弁してほしい。接続詞を適切に入れると格段に翻訳が正確になる。
6 We have not seen the devastation in Japan as in Italy, Spain or New York City. There is no medical collapse in a critically ill patient, no use of the operating room as an ICU, no piling up of bodies on a skating rink with no place to put them. Even if the "numbers" are not known, it is a fact that the current situation in Japan (including Tokyo) is much better controlled than in other countries.
7 Even so, you may be interested in "Well, what about the actual situation? There are estimates. For example, Dr. Hiroshi Nishiura and his group estimate that the number of mild illnesses in Japan may be twice the reported number. The catch rate is 0.44, with a 95% confidence interval of 0.37-0.50.
8 Although the study was based on data from China, there is no guarantee that the Chinese COVID-19 demographic is the same as the Japanese one. Also, since the original study did not include asymptomatic patients or those with minor illnesses that did not require hospitalization, the number of infected patients estimated on that basis would inevitably be an underestimate. If you are more paranoid, it's not unreasonable to believe that "the Japanese and Chinese viruses are different because of the mutation" (although I don't think so).
9 This does not diminish the value of the paper itself. The model must always use existing parameters, and it is often impossible to prove the external validity of these parameters. If the underlying parameters are not reasonable, the predictions will not be correct. A model assumes a simplified world insofar as it is a model. A model without simplification, which is an adjectival contradiction.
数理モデルのこうした「前提」にイチャモンを付けるのは、例えばAという疾患を対象にランダム化比較試験をしたときに、「Bという疾患については説明できないじゃないか」と文句を言うようなもので、業界の仁義に反する意味のない揚げ足取りである。
To complain about these "assumptions" of the mathematical model is like complaining, for example, "You can't explain disease B," when a randomized controlled trial is conducted for disease A. This is a meaningless tirade against the honor of the industry.
感想；「分からない」を「説明できない」に変えた。多分これでいいと思う。思いたい。
However, it is different for the reader of the paper.
A mathematical model that assumes a certain hypothesis should have internal academic validity, but it is the responsibility of the reader, as a resident of the real world, to appraise it in the real world.
Aという疾患を対象にしたRCTの知見をBという疾患に使ってはならないように、数理モデルの制限を理解し、現実世界にアプライするときに十分注意するのは当然だ。
Just as the RCT findings for disease A should not be used for disease B, it is natural to understand the limitations of the mathematical model and to be careful when applying it to the real world. For example, it would be wrong to read the paper and conclude that the total number of infected people in Tokyo is about 500 as of March 26.
感想；「読み手は別である」を「読み手にとっては別である」に変更し、「制限や限界」は「limitations and limitations」になったので片方削った。
11 People make mistakes. The models are also wrong. Being wrong is not a big deal. The problem is to notice your mistakes and make corrections. Already, a group at Imperial College London has admitted that its original estimate that the peak of the infection should be moderated was "wrong" and has revised its prediction that the ICU will soon fail if it does not fight the virus fairly aggressively.
Ichinose must have been very disappointed.
You're the first like-minded friend he's ever had.
Your performance yesterday was inspiring. I'm impressed though not surprised.
I was hoping your praise in particular wouldn't be so generic.
Sensei!
Can I ever hope to move people with my playing the way Kai did? Can I someday..?
I want the honest truth, so please don't hold back.
Fair enough. Since you're aiming to be a professional, I'll give you the unfettered, honest truth. Amamiya, you need to learn to appreciate your own piano playing more. Do that, and you'll understand. You need compare yourself against others. you gave a good performance. Your future excites me.
