「RaTe」を含む日記

■anond:20250311143607

MTGのデッキレシピサイトでそういう項目があった。

開始時のWin-rateもあるしある程度やってる人なら皆知っているんだろうね。

Permalink | 記事への反応(0) | 14:39

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■[今日知った言葉]GIHWR

Games-In-Hand Win Rateの略。

対戦カードゲームにおいて「このカードを手札に引いたプレイヤーが勝利した割合」を求めた統計上の数値（初手で引いたかゲームの途中で引いたかは問わない）。特定のカードがその環境においてどれくらい強いかを数値化する指標となる。

急に知らん略語が説明抜きで出てきてびっくりしたけど、英語圏ではもう当たり前に定着してるのか

Permalink | 記事への反応(1) | 14:36

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■Chatgptが答えた異星人の存在可能性とのそのロジック

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.

Assessing habitable zones

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.

Charting speculative odds

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.

Revisiting exoplanet options

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.

Clarifying speculative nature

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.

Mapping out speculative odds

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.

Assessing likelihoods

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%

TRAPPIST-1 e ~1.5%

TRAPPIST-1 f ~1%

TRAPPIST-1 g ~1%

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.

Nearby Exoplanets:

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%).

TRAPPIST-1 System (e, f, g):

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.

A Final Note

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

Clarifying the Drake Equation

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.

Assessing the Drake Equation

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 Drake Equation

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:

Well-Known Parameters:

Some factors, like

𝑅

∗

R

∗

(star formation rate) and

𝑓

𝑝

f

p

​

(fraction of stars with planets), have become better known through modern astronomy.

Highly Speculative Factors:

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.

Heuristic, Not Predictive:

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.

Opinion-Based?

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.

Conclusion

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.

Reflecting on potential

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.

Analyzing parallel evolution

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.

Evaluating life exploration

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.

Adapting the equ Permalink | 記事への反応(0) | 21:12

ツイートシェア

■Chatgptが答えた異星人の存在可能性とのそのロジック

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.

Assessing habitable zones

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.

Charting speculative odds

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.

Revisiting exoplanet options

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.

Clarifying speculative nature

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.

Mapping out speculative odds

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.

Assessing likelihoods

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%

TRAPPIST-1 e ~1.5%

TRAPPIST-1 f ~1%

TRAPPIST-1 g ~1%

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.

Nearby Exoplanets:

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%).

TRAPPIST-1 System (e, f, g):

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.

A Final Note

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

Clarifying the Drake Equation

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.

Assessing the Drake Equation

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 Drake Equation

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:

Well-Known Parameters:

Some factors, like

𝑅

∗

R

∗

(star formation rate) and

𝑓

𝑝

f

p

​

(fraction of stars with planets), have become better known through modern astronomy.

Highly Speculative Factors:

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.

Heuristic, Not Predictive:

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.

Opinion-Based?

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.

Conclusion

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.

Reflecting on potential

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.

Analyzing parallel evolution

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.

Evaluating life exploration

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.

Adapting the equ Permalink | 記事への反応(0) | 21:12

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■anond:20250115220244

将来に非伝統的な政策手段を実施する場合にも、shadow rate自体、あるいは自然利子率ないし中立金利との相対関係を示すことで、金融政策のスタンスの説明にも資することが期待される。

その上で、改めて感じることは、政策効果をフォーマルに分析する上でのインプットは金利であるという事実である。実際、多くの分析はshadow rateの引下げが実体経済を下支えしたことを実証的に示している。

物価は長期的には貨幣的な事象であるとすれば、政策的にマネーを増やした場合の実体経済への効果は調整過程の期間に止まり、新たな均衡では物価や名目賃金の上昇のみが残るという問題が残る。

もちろん、結果として名目値だけが上昇してもインフレ予想の変化に繋がるのであれば、QQEの目標達成に資すると考えることはできる。また、「レビュー」の一部の論文やアンケートの結果が示唆するように、実質の経済変数が不変でも名目値が変動した方が、経済活動が活性化される面もあるだけに、上記のような「マネーの中立性」が長期的にも妥当しない可能性もある。

Permalink | 記事への反応(1) | 22:05

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■日本のマスコミが伝えない

➤「救いようが最もうない、極東の自称他称の〝ジャーナリスト〟や〝学者〟、〝知米派〟は読まなくても構い。読んでもその肥大化した自己承認欲求、度し難い自己愛性人格では読むことはできないし、理解もできない。ただ見下した目線で見やるだけで、そこに自分が利用できる素材がなければ鼻で嗤うだけだ。この文章は、我がU.S.を領りたい、領ろうと下向きの反省的眼光で欲する諸君に読んで貰いたい。

I Traveled to 46 States in America This Summer. Here’s Why Trump Won.

By Frank S. Zhou

By Ezekiel A. Wells

Ezekiel A. Wells ’27 is a Double Concentrator in Environment Science & Engineering and Economics in Eliot House. He spent last summer traveling to 46 American states conducting interviews for his YouTube series, “Crossroads America.”

3 days ago

A week after Democrats’ election loss, accusations have flown in every direction within their Party. Some fault President Joe Biden for an egoistic refusal to drop out of the race earlier. Some blame the Harris campaign for failing to serve key demographics and communicate a clear vision for the country. And some blame Americans, claiming that racism and sexism drove voters toward Trump.

These factors certainly exist, but we’re missing a larger piece of the picture.

Over the summer, I traveled to 46 states in the U.S., creating a YouTube series highlighting slices of life across the country. In conversations from my nearly three-month road trip, I spoke with Republicans who were certain that inflation is entirely Biden’s fault and Democrats who, despite their frustrations with corporate profits and desires for universal healthcare, hoped for a more moderate candidate. From supporters of all candidates, I heard a shocking amount of misinformation.

After combing through hundreds of hours of interview footage from swing state Trump voters, I am certain that, as much as other factors influenced the outcome of the election, our crumbling media landscape — which has caused a rift in our democracy — is most to blame.

In the postwar period, news was dominated by three main channels, and because of the Fairness Doctrine, each station reported the same stories and covered multiple sides of each issue. Viewers picked which channels they watched mainly based on their preferences for news anchors’ personalities. Of course, this model had its problems, but, at the end of the day, it meant that Americans worked with a shared set of facts.

A shared set of facts is not the world we live in today.

Throughout my interviews, conspiracy theories were rampant, and on at least five separate occasions across separate states, I was told that Bill Gates tampers with our food, adding plastic to our fruits and vegetables to make his medical investments more profitable.

In conversations with voters, neither side seemed able to name many specific policy issues they cared about; everyone just seemed to repeat the words of their favorite pundits, podcast hosts, and internet personalities.

Although this behavior is harmful, I don’t blame everyday Americans. Blame falls on the media that has ostracized, disillusioned, and misinformed them.

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I first saw this trend with low-wage workers in West Virginia, who — despite falling inflation rates — have seen stagnated salaries and clear increases in food costs. Channels like Fox News bred anger and resentment for many of them.

Take July of this summer, for example, when for the first time in his presidency, prices actually fell under the Biden administration. Traditional media establishments rushed to celebrate this victory, with one article from CNN declaring, “The White House can finally cross out ‘inflation’ on its list of presidential liabilities.” However, outside these bubbles, I observed many Americans held a different view.

In late July, I was welcomed at a massive family reunion in Tylertown, Mississippi, where one Trump voter — a middle-aged, Black, family man, pastor, and soul food enthusiast — made this clear.

“When I go in the grocery stores, and I gotta spend my last to get groceries, you mean to tell me I’m not gonna look and see who’s gonna vote to help me? I voted for Trump and I’d vote for him again, because he put money in our pocket,” he told me.

In their coverage, mainstream news organizations obsess over the Federal Reserve’s next rate cuts while failing to connect with people concerned with their next meals. With titles like “Vance: Young Americans ‘Are Becoming Paupers’ Due To Inflation, High Housing Costs,” sites like The Daily Wire had their fingers on the pulse of American sentiment, welcoming new readership from those who felt neglected by traditional media.

This problem was not just confined to the economy. While Biden’s mental state was deteriorating, liberal media outlets seemed to under-cover these stories, sheltering him from scrutiny of his declining capabilities, until the infamous presidential debate.

Formerly trusted networks slowly made themselves indigestible to the polarized American public, and in 2024, for the third year in a row, a Gallup poll found that more Americans indicated having “no trust” in the media than those who trust it a “great deal/fair amount”.

So where does the average American turn when the nation’s media cannot be trusted? For many people, it was YouTube talk shows, Newsmax, and podcasters such as Joe Rogan.

While Democrats seek to blame various internal factors for this election’s loss, I cannot help but think of Joe Rogan’s Trump endorsement, the many blind lies I heard from ordinary citizens across the country, and declining trust in American journalism.

As Harvard students and members of higher education institutions, we have a part to play in the problem. At Harvard’s Institute of Politics, those who denied the 2020 election results have been precluded from speaking at the JFK Jr. Forum. While the goal is understandable, it shields students from understanding the American viewpoints they represent.

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There is a difference between platforming intentional and manipulative misinformation and listening to and learning about where people are and what they believe.

As a pipeline to mainstream media, Harvard, and its future journalists, have to consider the audience they lose when they stay inside of their bubble and ignore the issues of everyday Americans.

The disappearance of factual importance in our world is alarming and dangerous, but if we, as aspiring journalists, politicians, and engaged citizens, want to be taken seriously in communicating Trump’s threat to democracy, inflationary tariff policies, and so on, we owe American voters that seriousness, too.

Ezekiel A. Wells ’27 is a Double Concentrator in Environment Science & Engineering and Economics in Eliot House. He spent last summer traveling to 46 American states conducting interviews for his YouTube series, “Crossroads America."

Permalink | 記事への反応(1) | 16:45

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■anond:20241105152759

性能的にはほぼ同じ

https://www.techpowerup.com/gpu-specs/arc-a750.c3929

Theoretical Performance

Pixel Rate

268.8 GPixel/s

Texture Rate

537.6 GTexel/s

FP16 (half)

34.41 TFLOPS (2:1)

FP32 (float)

17.20 TFLOPS

なお、P5Proの場合、16GBのVRAMを積んでるといっても、グラフィックスのために丸々使えるとは限らない。

※ちなみにPCも16GBのRAMを積んでいれば、8GBぐらいはグラフィックスとしても使うこともできるので、仕組みとしては実は似てる。

Permalink | 記事への反応(1) | 15:33

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■冷笑してたアニメのグッズを気づいたら買い漁ってた

前クールの放送前、『しかのこのこのここしたんたん』の公式MAD（？）が大バズりしていたのを覚えている人は多いと思う。

「（電通）マーケティングの巧みさ」が賞賛されていたように記憶している。

が、俺は懐疑的だった。

「本当にこの勢いに見合うアニメなのか？」と。

また、「ボーボボの再来」とも言われていたように覚えているけど、あれは常人が描ける漫画ではない。本当にそんなことが可能なのか？と。

それが放送を見るうちたちまち夢中に……とはならなかった。

「やっぱり俺の言ったとおりじゃないか！」と思った。顔芸にしろスローモーションにしろ率直にいえばスベッていて、これで１クール持たせるつもりだとは到底思えなかった。

２話を見る。スベってる。３話を見る。スベってる。……と見ていくうち、しかしこの作品は何ごとかではある、と思うようになった（５話は普通にちょっと面白かった）。

愛すべきスベりっぷり？　それはある。しかし確実に「愛せない」スベりっぷりもこの作品には刻み込まれている。

その両者を浴びていくうち……なんだかシビれてくるものがあるのだ。

作者や製作陣に敬意を表すると、意欲作ではある。

キャラクターがいわゆる「百合媚び」をしないからこそのキャラの可愛さがある。

これ見よがしに「関係性の進展」を描かないところも個人的な好みだ（終盤にばしゃめとあんこに関しては描かれたが）。

それから最終回。

のこたんが消えると言う「フリ」があった。

なのでこしたんが奮闘し、色々あった末に魔法が起きてのこたんが帰ってくるみたいな話なのかな……と思っていたら消えるのは「ウソ」で、のこたんがせんとくんとの試合で爆弾を落としまくると言うエンド（？）。

あれは痺れた。日常系では「魔法」が問題を解決するわけだが、『しかのこ』では「爆弾」が問題を解決するのだなと。

ここでの本題ではないので省略するが、他にも「日常系との違い」が強く意識された作品ではあった。

話を戻そう。

この『しかのこ』のくだらなさ、そして見続けていると痺れてくる感じ……これは貴重な体験のようにも思うのだ。

だって考えてみてほしい。タルコフスキーの映画だってカフカの小説だって基本的には退屈だ。

ただそれを味わっていくうちにビリビリくるものがある……と言うものではなかったか？（個人の感想です）

少なくともこうは言えるだろう。「つまらない」は「贅沢」なのだと。

アニメに限らず、今の世の中（主語がデカすぎるが、続ける）、面白いもので溢れかえっていると思う。

寸分も目を離さないように設計されているもの、気が利いているもの、巧みな工夫が施されたものetc.

そしてこのサブスク化によって、私たちは時間さえあれば無限に面白いものに触れられるようになった。『Rate your music』など、最近はレビューサイトも充実してきている。

もちろん、それは良いことだ。クソアニメばかり掴まされてきた若い頃と比べると、良い時代になったなと思う。

でも裏面では、面白いものに内心うんざりもしているんじゃないか？

大げさにいえば、「面白さというエコノミー」にナッジされ搾取されている私たち……ということだと思う。

ただ具体的に、「面白くない作品、感動させられない作品、心を揺さぶられない作品」があってもいいと思うのだ。

（これはいわゆる"クソアニメを面白がる"態度と近い。俺はそれを認めた上で、ズレる面があると言いたいのだが、ここでの本題ではないので置いておこう）

そして勘違いしないで欲しいのは、俺の『しかのこ』への想いは決して"いわゆる"作品愛ではないことだ。

上に書いたとおり、ギャグはかなり滑ってると思った。またそのゆるさ・たわいのなさを愛でるにしても「愛せない」と感じる側面がある。

しかし、一見矛盾しているように感じるかもしれないが、この愛せる部分と愛せない部分の共存、それこそが真の「愛」じゃないか？　と感じるようにもなった。

俺が講釈を垂れるまでもなく、今は「いいね！」が氾濫する時代である。「推し」も然りだ。

またアニメ評論に関していえば、一見客観的・中立的な技術的分析が背後に大きな「好き！」を隠し持っているというケースは多々ある（そういう世界なんです）。

それらを否定する気は全くない。

自分はどちらかといえば「批評（批判）」には懐疑的な立場だ。作品のポテンシャルを引き出すよりも削いでしまっている、あるいは作品を読めてないだけ、ということの方が多くないか？　と思う。

何より、好きな作品の批判を見るのは嫌なものだ。それから推しのVtuberもいる（複数）。

しかし、単なる全肯定とも違う、あえて名付けるならば「愛」と呼ぶしかないものがあるのではないだろうか？

少なくとも自分は、この『しかのこ』を通じてそれを体験した。幸福な体験だったと思う。

Permalink | 記事への反応(8) | 17:37

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■anond:20240828211356

PS5 proのスペックと同じスペックのPCを用意しようとした場合、モニターとOSこみで14万円かかる。

本体のみだと11万円となりPS5 Proと値段がほぼ変わらないことになる。

（PS5 ProはASK税込みの1ドル180円で計算した場合、108,000から126,000円ぐらいと思われる）

G.SKILL F4-3200C16D-16GIS (DDR4 PC4-25600 8GB 2枚組)

　4,820円

XPG PYLON 550W PYLON550B-BKCJP

　6,667円

中古 Intel Core i7-12700 (2.5GHz/TB:4.8GHz) Bulk LGA1200/8C/16T/L3

　42,980円

中古 _MSI PRO B660M-E DDR4 (B660 1700 mATX DDR4)

　8,590円

Ultimate SU630 ASU630SS-480GQ-R

　4,980円

Define C FD-CA-DEF-C-BK

　13,262円

SPARKLE Intel Arc A750 ORC OC Edition SA750C-8GOC

　31,700円

フィリップス 221V8/11

　11,000円

Windows 11 Home 日本語版

　16,090円

合計　140,089円

Intel arc a770（16GB）はfp16だと39tflops程度で、中古だと3.2万円から4万円台で売られており、新品だと4万円から5万円台程度なので、運が良ければps5 proとメモリー以外全く同じやつが手に入ってしまうことになる。

以下、そうなる根拠。

公式発表では、PS5におけるGPUの処理能力は「10.3TFLOPS」。この数字は、RTX2080に相当します。しかし「TFLOPSの数字」と「実際のグラボの性能」は、百パーセント一致するものではなく、性能ほど実パフォーマンスは高くならないのが一般的です。

https://digitaldiy.jp/article/esportsgame/16914/

CPU：CPU周波数最大4.4GHz、Zen4ベースアーキテクチャ、5nmプロセス製造。台湾TSMCが製造を担当。CPUのクロック周波数を10%増加させ、3.85GHzで動作させるモードが搭載される。

（Apple M2と同じく、TSMC製4nmプロセスSoC搭載の可能性もあるとのこと）

CPUキャッシュ：コア毎に64kBのL1キャッシュ、512kBのL2キャッシュ、8MBのL3共有キャッシュ

性能：PS5標準モデルと比べ、通常時で2倍、レイトレーシングでは2.5倍の性能アップ

プロセッサ：30基のWGP（Work Group Processors）、60基のCU演算コア

ROP（Rasterize OPeration unit）：96~128基

※現行PS5はROPが64基、CUが36基。

メモリ：18gbps GDDR6 256bitメモリ、メモリ容量16GB、バス幅576GB/s、18000MT/s（現行PS5のメモリは14000MT/s）

CPUアーキテクチャ：RDNA3(Radeon DNA3)

GPU：GFX1115。GPUコアが現行の18個から30個に増加。これは約1.66倍の増加

テラフロップス（浮動小数点演算）：33.5テラフロップス

GPU周波数：2.18GHz、ブーストで最大2.35GHz

GPUキャッシュ：L1キャッシュが128KBから256KBに倍増、L0キャッシュが16KBから32KBに倍増

グラフィック性能：PS5比で45%向上。可変レートシェーディングやハイブリッドMSAAのサポートなど、DirectX 12 Ultimateの新機能を搭載。GPUのアーキテクチャがRDNA 2からRDNA 3に変更される可能性があり、これにより各GPUコアの演算機が2倍になる。

超解像技術：ソニー独自の超解像技術を搭載。高精細と高フレームレートを両立。AMD FSR2等の採用は無し。アップスケーリング／アンチエイリアスソリューション

（AMDのFSR（FiedelityFX Super Resolution）を搭載との話も）

https://socius101.com/matome-of-ps5-pro/

Intel ARC A750のスペックは

Theoretical Performance

Pixel Rate

268.8 GPixel/s

Texture Rate

537.6 GTexel/s

FP16 (half)

34.41 TFLOPS (2:1)

FP32 (float)

17.20 TFLOPS

https://www.techpowerup.com/gpu-specs/arc-a750.c3929

PS5 ProのGPUと同じ性能である。

PSのCPUはRayzen 7 7700X相当で、Intel Core i7-11700だと7割の性能で、Intel Core i7 12700で同じぐらいの性能となる。

Permalink | 記事への反応(1) | 01:09

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■チートではないがソシャゲで不正アクセスを繰り返していました

https://www.bengo4.com/c_1009/n_17833/

この記事を見て思い出した

10年前はソシャゲに対して不正アクセスを繰り返していました。

思い出せる限りは3タイトルくらい

とある上場企業のモバイルゲーム

APIとレスポンスを分析して、自動で戦闘し続けるプログラムを作成していました。

内容としては時間で体力が回復するゲームだったが、常にポチポチしてられないので自動化したというだけです。

無課金ユーザでしたが上位課金勢に食い込めるところまで行きました。三ヶ月ほど遊んで、飽きてやめました。

非上場企業のアプリゲームA

数年に渡ってiOSではランキング10位以内にいたゲームでした。サービス終了しています。

APIが穴だらけでした。win=1を送信すると勝利が確定するみたいな。

ガチャでも rate=5 を送信すると激レア確定の作りでした。

招待コードと一緒にユーザ登録すると、実質ゲーム内コインを300円分もらえるAPIが無限に実行できたので、1分毎に実行していました。

そのゲームに存在するアカウントの10%は私が不正アクセスで作成したユーザでした。

次第に飽きて短期間でゲーム内ランキング1位になってしまったため、ある日ログインしたら凍結されていました。

半年くらいは遊んでいました。

非上場企業のアプリゲームB

こちらはサービス提供中です。

win=1を送信すると勝利が確定するみたいな作りでした（今は知らない)

廃課金勢チームに連続勝利を収めて一斉に通報を頂き、朝起きたらBANされていました。

----------

怪しいと疑われ始めると、ゲーム内の個別チャットで罵詈雑言は飛んできます。

一方で印象的なのは、2割くらいは「どうやるんですか？」「どうしたらそういう事を自分で作れますか？」という質問は多かった。

やっぱり好奇心は掻き立てられるよね

Permalink | 記事への反応(9) | 00:24

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■国内VPS価格から国内サービスを使うインセンティブ価格を調査

さくらのVPS最安プラン1年支払い7078円 590円

amazon lightsail 最安プラン(IPv6only) 3.5USD

valtr 最安プラン (IPv6only) 2.5USD

• Lightsail: ドル円レートが168を超えると、さくらVPSの方が安くなる。
• Vultr: ドル円レートが235を超えると、さくらVPSの方が安くなる。

1ドル170円を超えたあたりからポツポツと国内利用のほうがお得になる場面も出てくるかもしれない。

国内サービス使うのがお得。ってレベルになるには200円超える必要がありそう。

Permalink | 記事への反応(1) | 03:05

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■[稀ドメインはてブ]2024年4月滅多にホットエントリを出さないドメインからのホットエントリ

ここ1年で初めてはてなブックマーク日毎の総合人気エントリ入りしたドメインからのホットエントリ、ブクマ数順トップ30

Permalink | 記事への反応(0) | 11:38

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■

介入来てるぽい

他は「It is unclear how long it will take for rate cuts to begin」で全戻し

リアルタイムでいいもの見れた

Permalink | 記事への反応(0) | 05:21

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■claudeとChatGPTの使い勝手を比較する

プロンプトの精度はよくわからんので使い勝手について評価してみる。claudeは、rate limitに達すると最上位モデルが使えなくなることもあるし、haikuまで使えなくなることもあった。まじで最悪。しかし、レスポンスは軽快なのでChatGPT4よりは便利。

ChatGPT4は、固まることが多くレスポンスが遅い反面、rate limitに達しても3.5は使えるのでマジで助かる。

まとめ

両方に金を払え。

Permalink | 記事への反応(0) | 10:10

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■financial times

Will the Bank of Japan raise rates above zero?

No. 2024 will be the year the Japanese central bank finally ditches yield curve control and negative interest rates. Contrary to market expectations of several further increases, however, rates will end the year no higher than zero.

With mediocre wage growth, a stronger yen in prospect as US rates peak and reasons to prefer a steeper yield curve, the BoJ is unlikely to set a positive rate — although as with any central bank forecast, much depends on the incoming data. Robin Harding

Permalink | 記事への反応(1) | 06:45

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■例のケーキの顛末

全ては想像でしかない

Tl;dr

• 製造元が能力を超えて（デパート側から）受注を受けた
• 間に合わないので冷凍後出荷のプロセスを飛ばした
• 結果固まってないものが出荷されて箱内で崩れた

配送の問題ではないのか

「ケーキに配送は無理」「荷物は投げられるから」と

いうブコメは宅配ケーキへの風評被害なので反省してください。

Cake.jp等、冷凍ケーキを一定以上の品質で宅配しているサービスは多数存在します。

一方で、数年前に「荷物が溢れて冷凍保管すべき荷物が露天保管になっている配送業者」のような問題点も指摘されました。しかし今回は特定の店舗の、特定の品物に問題が集中しており、配送の問題ではないことは明白です。

出荷時に間違えたという可能性は

本来「冷凍」でおくるものを「冷蔵」「常温」で出荷してしまうケースです。これは日常的に発生し得ます。

とくに冷凍冷蔵便は送料が高いので、何らかのロジックで合理化を進めようとして、ミスが生じてしまう現場は稀によくあることです。

ただ、この場合消費者の手元に届いた時点で「冷凍」のシールが貼られていない、伝票に冷凍の記載が無いなどで消費者で判断が可能です。

今回の件は「崩れた状態で凍ってた」ポストが複数あることからこの可能性は低いのだと考えています。

何故冷凍後出荷のプロセスを飛ばしたと判断するのか

かんたんで「まともに届いているポスト」を確認したからです。

推測に推測を重なることになりますが通常のオペレーションであればきちんと配送できるが、なんらかのオペレーションエラーが生じたことが考えられます。

そしてこの時期おこるエラーといえば、生産販売能力を超えた過剰な受注です。

固まってもいないケーキを箱に入れて配送業者に引渡したら、中でどうなるかは容易に想像できますよね。でも「24日に着かせるにはx日のy時に配送業者に渡さないといけない！でも間に合わないからとりあえず出荷してしまえ」が発生したのです。

都内近郊としても冷凍便なら前日午前には引き渡しでしょうか。そうすると現場では23日の明け方まで製造・梱包・出荷に追われていたのではないでしょうか。現場の人はかわいそうですね。

食品の非対面受付は生産量・出荷可能量に応じた受注調整をしろ

ネット販売はrate limitによる機会損失が少ないのが魅力であり、食品の場合「作れば売れる」的な発想になりがちです。

ただ、その発想において販売の現場は物流オペレーションを軽視しがちで、今回のようなトラブルは枚挙に暇がありません。

• バレンタインにスイーツの受注をしすぎて間に合わない
• おせちの受注をしすぎて品質低下
• ピザのキャンペーンが当たりすぎて行列がえぐい

と、いうような例を少なからず見聞きしたことがあるのではないでしょうか。

おおくは、販売が跳ねた場合の限界値について検討されていない、もしくは検討されても適切に販売可能値（普通のカートシステムなら在庫設定するだけでよいが、食品は無限販売すること前提の運用がおおい）に反映されていないことが問題です。

今回の事業者も、写真を見るにデパートの先はお菓子のOEM企業のようです。複数経路からの受注を受け付けているのだとすれば、受注管理システムなどを運用していたら100%とは言いませんがかなり防げそうです。

通販業界利益少なすぎ問題

これは通販というか小売業がそうなのですが、基本的多くの会社は利益率がITの水準から見ると驚くほどに低いです。

その中で適切なシステム化・運用が求められ、そのバランスを見誤ると今回のような事故が生じるわけで大変難しい状況にあると思います。一方で小売の考えを中心にしシステム・オペレーションを二の次にしがち、ということが事故頻発のおおきな要因であることもしっかり受け止め、他山の石としていただきたい。

Permalink | 記事への反応(6) | 09:20

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■anond:20230925204113

My way rich, My way rich

Book flower tape and know　

Wednesday your car rate

Permalink | 記事への反応(0) | 22:15

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■anond:20230816120651

x APIを使わせないから

o APIを使わせたとしても、課金式 and rate limit付きにするつもりだから

Permalink | 記事への反応(0) | 12:08

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■SDXLのLoRaの学習がわからん

learning rate: 4e-7

LR Scheduler: constant

LR warmup(% of steps): 10

Optimizer: Adafactor

Maxx resolution: 1024,1024

Network Rank: 128

Network Alpha: 64

Epoch: 20

でやっている。YouTubeでSDXL学習させている人のを参考にした。

学習させているのは人物写真。

LoRa適用前後で絵柄は変わるものの、学習させたのとは全然反映されない。

SDXLだとLoRaのデータが1GB近くにもなっているのに変わらん。

Permalink | 記事への反応(0) | 14:10

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■anond:20230618010533

原文

Japan review

Japan review it's been a year since I

moved to Japan and I thought it made

sense to finally rate Japan I will talk

about things I like and the things I

don't like which seems to be the only

two options available if you have

opinions about this country

so sugoi or did you know Japan is

actually really bad it's got a lot of

survival issues okay I will list one

good thing and bad thing and I will not

hold back there's no trash bins

where I'm gonna put my trash

I have to put in my pocket

oh

there's always these generic things that

you hear or yes when we you visit it's

kind of weird but then you realize it's

not a big deal anyway let's start off

with number one reason I like Japan

it feels like a giant playground no I

don't mean in the Logan Paul kind of

sense of doing whatever the hell you

want

but rather there's a infinite things all

right lazy feels like to explore and

experience and I've been here a year now

and I don't think I'm gonna get bored

anytime soon although I am having a

child so I don't know how much more I

have time to experience

but it really feels like a whole new

world and if you visited you can

probably relate to it and I'm glad that

even a year in it still feels incredibly

fresh and I even would say that you

realize that the best part of Japan

aren't the touristy places kind of

obviously but there are so many areas

that I found that I really enjoy

visiting and this is probably more

specific to me but you know Tokyo is

very busy and so many times I just catch

myself surrounded by what feels like

hundreds of people and they have no idea

who I am

everyone is just doing their own thing

and that feels so [ __ ] good

now once it was staring at me no one's

following me no one's being weird you

guys are weird and I'm just kidding I

just love the feeling of being able to

exist in public and uh not worrying

about what everyone else is doing like

I've said this before but I genuinely

enjoy talking to fans or when people

approach me it always makes me happy but

it can be kind of frustrating to always

wanting to just do your own thing and

always be

you know so yeah let's move on to the

bad things of Japan number one reason

Japan is bad it's kind of a heavy

subject and I haven't seen anyone else

really talk about it it's not brought up

very often at least and that is cones

there's too many cones in Japan once you

see it you cannot unsee it they're

everywhere they say oh Japan has so many

vending machines there's like five per

one person no the opposite

there's more cones than people why are

there so many cones I need to know we

got the tall ones we got the small ones

we got the funny ones the cute ones the

sexy ones I do like those I just don't

understand that whoever plays these

cones think I'm just gonna barge through

oh thank God there's cones here

otherwise I had no idea what I was gonna

and I realized the cone history of Japan

stretches centuries okay if you played

Animal Crossing sometimes it's a

Japanese game so sometimes you get these

items right you're like oh that's kind

of weird I don't know exactly what that

is but it's probably something Japanese

and then you get the bamboo thing and

you're like what the hell is that what

am I even gonna do with that and then

you see it in real life here in Japan

you're like holy [ __ ] it's a cone that's

a cone they're everywhere

I feel like they are following me

I'm glad I was able to talk about this

I'm for one and willing to call out

Japan knock it off man no more cones

there's enough cones let me tell you

something even better than cones you may

have noticed new merch finally it's been

forever my mom came over she had

unofficial merge because I literally

have no other merch I've hadn't hadn't

merch I'm sorry Mom so we spruced up the

logo got a cool back design the team

that worked on it really truly

understand how my brand and I think they

did such a good job these pieces look

amazing and I think you guys are gonna

really like them as well these are

available for limited time only so make

sure you order now so excited to finally

have this merch available thanks to

amaze for making this happen we are

gonna have one piece that will stay on

the store so my mom will not buy the

wrong merch but for a limited time that

piece will be available in this color

off-white kind of color it looks really

nice and then after that you can still

get it but not in this color that's

you want this one yeah I get it

so yeah check that out if you're

interested I'm so happy about these

designs and I hope you guys would like

them as well all right reason number two

I like Japan yay when we first announced

that we were gonna move to Japan there

was so many people just saying how bad

Japan is actually did you know Japan is

really bad did you know this I have to

list all these reasons now because

everyone is like thing and then thing

Japan ah so I have to tell them and I

it's actually but one thing in

particular that people said was that old

people really don't like foreigners they

hate them so when I was gonna stop by to

say hi to our neighbors who was a little

older at least some of them I was

terrifying I heard all these stories you

know like what are they gonna do to us

so I had my guard up ready for the worst

and I was met with nothing but kindness

and welcoming and I felt like a total

dick for having this preconceived ideas

thanks to other people

and just a side comment like yes there

are definitely probably people that

don't like foreigners and all that stuff

but I realized I should let my own

experience is dictate how I feel about

certain things maybe that's just

ignoring a problem I don't know it just

feels like it's a bad way to approach

life if you always have a negative

expectation you know it's smiling people

may Smile Back

smiled back

thank you sometimes they don't and

that's okay you know anyway my point

being Japanese people are very in my own

experience

are very nice and friendly the majority

at least and yes even to foreigners I

feel like they are especially nice to

foreigners because they think we're like

a kid lost at Disneyland or something

I just asked for directions I didn't

need you to walk me for half an hour to

this specific place I was going but

thank you I appreciate it a lot of times

I go bouldering alone and there's always

other groups of people being supportive

and yelling like I'm about there like go

you can do it I love it I think it's

great you know or if you're small

talking with people people generally

want to communicate with you and I love

having those moments but of course

there's times where people are like oh

you're a foreigner I don't feel like

even trying

which again it's fine speaking of which

reason I don't like Japan number two

their language

I have lived here for a year and I'm not

fluent in Japanese

I am dumb I am very dumb I remember the

moment we moved here I had studied some

Japanese and I was like

Let's test out this knowledge that I

have acquired let's go I'm just gonna

come in it's gonna be dangerous and you

enter a store for the first time and

they're like

what

what oh

what the classic the most common

experiences that you have aren't

necessarily what you're taught in the

textbook yay I know I think that's the

same for anyone learning a language for

the first time but don't even get me

started on the kanji main what the [ __ ]

is this I feel like Japanese is such a

hard language obviously but I don't

think people realize how hard it is at

least me personally because the more you

learn the more you realize you don't

know [ __ ]

for English speakers Japanese is

considered one of the most difficult

languages and because it's just so

different I listed it as bad because

that was my first kind of experience

with it coming here but the more I

interact with people the more it feels

like I'm unlocking new skills you know

oh I made a phone call for the first

time oh I could ask someone over the

phone I know big deal but it's like oh I

can actually do that or even just having

a small tiny yes shittiest conversation

with a stranger it's still something and

it feels good you start to all of a

sudden understand you know a movie if

you're watching oh I understand actually

what's going on here or I can play games

and kind of get what this they're saying

I have to look up words obviously but to

me all those new experiences that it

unlocks to me is very rewarding even

though it's such a challenge I would

actually now say it's a good thing I

played it on its head it was a good

thing all along but I obviously have a

long [ __ ] way to go

and it just I don't think it will damage

time reason number three I like Japan

this is nothing to do with Japan to say

it's more related to me taking a more

relaxed approach to YouTube for my

entire 20s I did nothing but YouTube

that was my life and that's okay but I

also think it was a little toxic

probably you know if I wasn't making

videos I sure as hell was thinking about

making videos I uploaded videos during

our honeymoon

and it feels really good to finally be

free from it you know and I can discover

other things in life there are other

things in life

a new hobbies and interest that I've

always wanted to do I can do and have so

much fun with it surfing I know I would

love for the longest time and I finally

get to do it and it's so [ __ ] amazing

I love learning new things anything that

isn't necessarily connected to all of

this on the internet and that is

something I'm very very grateful that I

discovered so yeah it's not really Japan

I could have done that anywhere but it's

largely why I enjoyed so much here

reason I don't like Japan number three

this is probably the most trickiest one

and it's the rules what are the rules

Japan has so many rules and it's a bit

conflicting for me to complain about

because a lot of the best stuff about

Japan not the best stuff but a lot of

the reasons why Japan works so well is

because of the rules you know the trains

are always on time things just work in

general it's hard to explain the streets

are clean people aren't loud in public

and so on and these are sort of societal

rules that make it happen more or less

but sometimes There are rules that just

don't make any sense and I have no

problem following rules as long as I

understand the reason for it you know

don't talk on the phone on the train

because it's generally annoying when

other people do that to you A lot of it

is just be thoughtful of other people

it's not just about you and that just

makes it more pleasant for everyone but

one rule is especially which I talked

about before is the fact that because of

kovid I'm not allowed to be in the

delivery room for our baby for more than

two hours that's because of covered

rules it just doesn't make sense to me

and I tell people about this like uh

family and friends and they're always

like well why don't you just ask them or

like why don't you talk to them I'm sure

you can there's got to be somewhere and

it's like no it's Japan okay there are

rules and people follow the rules for

better or worse you know so the more I

time I spend Permalink | 記事への反応(0) | 01:06

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■少子化対策指標としてのジェンダー・ギャップ・ランキングの卓越について(2)

anond:20230224010244の続き。

計算

ジェンダー・ギャップ・ランキングの数値の中でも、GGIスコア（ジェンダー指数）は、0.001刻みで比べると、

お互いにほとんど同じ値をとる国が多い。ほんの小さな差では、扱いにくい面がある。

そこで、スコアのかわりに、ランキングの順位を使用する。

153か国での相関係数

まず、153か国で、単純に順位と出生率の相関係数を計算すると、0.43になった。

単純に見ると、これは、順位が下がった国ほど、出生率が上がっていると読める。

しかし、これは単純に比較できない、社会進出をチェックする以前に、女性の基本的な権利や生命が脅かされたり、

工業化が進んでいないといった、発展途上国も多く含まれている。

そのような国では、過去の時代から改善されなかったまま、子沢山の社会が続いていることも多い。

明らかに、同じ基準で比較できないものを比較するのは不適切であるので、

次に、出生率が0.2未満の国を残して計算する。

出生率が0.2未満の国だけでの相関係数

これを計算すると、相関係数は0.06になった。

これでも、まだ日本と単純に比較するには難しい、様々な文化の違いなどを考慮する必要があるので、

比較する国を見直し、OECD諸国に限定する。

OECD諸国での相関係数

OECD諸国とは、次の国々である。

OECD（経済協力開発機構）

https://www.meti.go.jp/policy/trade_policy/oecd/index.html

2. OECD加盟国

現在、OECDの加盟国は以下の38か国となっています。

EU加盟国（22か国）

ドイツ、フランス、イタリア、オランダ、ベルギー、ルクセンブルク、フィンランド、スウェーデン、オーストリア、デンマーク、スペイン、ポルトガル、ギリシャ、アイルランド、チェコ、ハンガリー、ポーランド、スロヴァキア、エストニア、スロベニア、ラトビア、リトアニア

その他（16か国）

日本、イギリス、アメリカ合衆国、カナダ、メキシコ、オーストラリア、ニュージーランド、スイス、ノルウェー、アイスランド、トルコ、韓国、チリ、イスラエル、コロンビア、コスタリカ

この中で、出生率が2.9のイスラエルも、再び入れて計算した。

相関係数は-0.06になった。

かろうじて、順位と出生率の関係が負という結果が出たが、やはりOECD諸国の中でも、明らかに比較の難しい、

遠い文化圏の国を同時に比較している、無理な計算があることは否定できない。

OECD諸国のうち、日本と文化的に近い国での相関係数

そこで、日本と、現在の日本と文化的に近い韓国、北米、ヨーロッパ、オセアニアの国々だけを残して、

再計算する。OECD諸国のうち、コスタリカ、コロンビア、チリ、イスラエル、トルコを除いた。

計算すると、相関係数は、-0.43になった。

良好な結果ではあるが、やはり、比較の難しい国を含めている可能性がある。

経済的な規模も、少子化問題対策の参考にするために、揃えて考える。

残った国の中から、更に、G20にも含まれている国だけを残して計算する。

OECD諸国のうち、日本と文化的に近く、経済的規模も近い国での相関係数

OECD諸国とは、次の国々である。

G20に関する基礎的なQ＆A

https://www.mofa.go.jp/mofaj/ecm/ec/page25_001040.html

問．G20とは何ですか？

　G20とは、G7（フランス、米国、英国、ドイツ、日本、イタリア、カナダ、欧州連合（EU）（G7の議長国順））に加え、アルゼンチン、豪州、ブラジル、中国、インド、インドネシア、メキシコ、韓国、ロシア、サウジアラビア、南アフリカ、トルコ（アルファベット順）の首脳が参加する枠組です。G20の会議には、G20メンバー以外の招待国や国際機関などが参加することもあります。

比較して、最終的に、次の国々を残した。

北欧がない問題が残るものの、妥当な組み合わせであり、日本の少子化対策にも役立つと考えられる。

上の国で計算すると、相関係数は-0.71となった。

結果的に、日本と、文化も経済規模も近い国々の間で計算すると、非常に強い相関があると分かった。

ジェンダー・ギャップ・ランキングの順位が、低くなる国ほど、合計特殊出生率も低く、順位が高くなる国ほど、

出生率も高くなることが分かる。

まとめ

ジェンダー・ギャップ・ランキングの順位が、少子化の指標として卓越していることが、

今回の計算でも示すことができた。

日本のジェンダー・ギャップ・ランキングの順位は、2020年は121位に低迷している。

岸田が、ジェンダー・ギャップを改善することで、少子化対策として、異次元の効果を持つことが期待できる。

Permalink | 記事への反応(1) | 01:03

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■少子化対策指標としてのジェンダー・ギャップ・ランキングの卓越について(1)

はじめに

異次元の少子化対策が求められている、岸田令和日本である。しかし、具体的には、どのような対策が有効なのか。

対策の効果を測定するためにも、出生率と結びつきが強く、しかも、分かりやすい指標が求められている。

そこで、今回は、世界経済フォーラムが発表する、ジェンダー・ギャップ・ランキングに注目したい。

ジェンダー開発学の分野では、ジェンダー・ギャップ・ランキングの順位が高い国で、ジェンダー平等が達成され、

女性が子育てと社会進出を両立しやすく、結果的に、少子化も改善されていることが知られている。

少子化とジェンダー・ギャップ・ランキング

日本の少子化対策についての記事の中で、ジェンダー・ギャップ・ランキングの順位の低迷と、

少子化の関連性が議論される。

例えば、次の記事では、題名の中にジェンダー・ギャップ・ランキングの順位と出生数が盛り込まれている。

ジェンダーギャップ121位、出生数90万人以下の日本で、女性たちの未来への備えとは

https://woman.nikkei.com/atcltrc/blog/shirakawatouko/post/dddad1acb2e14d2a9ad1acb2e1cd2a4b/

更に、次の記事では、ジェンダー分野の専門家の対談の中で、GDPや労働生産性と共に出生率、そして、

ジェンダー・ギャップ・ランキングの順位の恥ずかしさについての問題が指摘されている。

ジェンダー指数から、いわゆる、ジェンダー・ギャップ・ランキングの順位が計算される。

上野千鶴子×酒井順子「単身世帯は38％、最も多い家族の姿に。1985年から86年は『女・女格差』元年。女性が3分割された結果、中高年女性単身者の貧困が生まれた」

【連載】酒井順子の大人は知りたいことばかり：女、家族、社会はどう変わった？＜後編＞

https://fujinkoron.jp/articles/-/7486?page=5

酒井　2022年の日本のジェンダー指数は、世界146ヵ国中116位。それを永田町のおじさんたちは、恥ずかしいとは思っていないんでしょうね。国際会議に出席する日本代表が男性だけでも平気でいられる。

上野　でもこのままだと、日本はジリ貧になりますよ。一人当たりGDP（国内総生産）の順位も、労働生産性も低下しています。

酒井　出生率も落ちる一方。出生率が高いのは、共働きでケアの公共化がされている場合だと海外ではデータがはっきり出ているのに、なぜ変えようとしないのでしょう。

上野　おじさんたちが合理的選択をしないのは、ホモソーシャルな組織文化を守りたいからだとしか私には思えません。ホモソーシャルな集団のなかで、男として認められたい。そのためには自己犠牲もいとわない。

上で紹介したような関連性の指摘のみならず、実際に、ジェンダー・ギャップ・ランキングや、

類似する、ジェンダー・ギャップを示す指標と、少子化の関係性の分析もなされている。

ジェンダー格差の解消が最高の少子化対策（前編）

https://news.yahoo.co.jp/byline/shirakawatoko/20211029-00265552

日本のジェンダーギャップと少子化。この二つはリンクしているとずっと言い続けてきた。日本は世界経済フォーラムが算出するジェンダーギャップ指数では156カ国中120位と先進国では最下位。下から数えた方が早い。先進国に限ってはジェンダーギャップ指数と出生率がリンクしていることがOECD（経済協力開発機構）の分析でわかっている。

2020年4月の内閣府政策統括官（経済社会システム担当）の資料には、「ジェンダーギャップ指数が高い（男女格差が少ない）ほど、出生率は高まる傾向」を示すグラフが掲載されている【図１】。女性が社会進出をすると一旦は少子化になるが、その後回復するかどうかは、ジェンダーギャップをいかに埋めるかにかかっている。

「男女差別がなくなると、少子化も改善するよ」というデータを示すと、なぜ反論(クソリプ含む)が押し寄せるのか？

https://comemo.nikkei.com/n/nd4de034b8a25

ところが、冒頭のツイートの図にあった通り、他の先進国では事情が違います。女性の社会進出と出生率が相関関係にあるのです。なぜかというと、女性の社会進出と子育てが、トレードオフの関係になっていないからです！

子どもが生まれたら、パートナーたる男性も、当事者としてしっかり家事育児にコミットします。これだけでも、女性の負担はケタ違いでしょう。みての通り、男性の家事育児の負担割合が高い国ほど、出生率が高いのがわかります（我が国は定位置の左下）。

しかし、ジェンダー・ギャップ・ランキングの話をすると、クソリプと呼ばれる意見が寄せられたり、

指標のことに異論を挟む声も、少なくない。そこで今回は、改めて白黒はっきりつけ、

ジェンダー・ギャップ・ランキングが少子化を説明できる、卓越した指標であることを示す。

データ

合計特殊出生率は、次の2020年のデータを使う。

Fertility rate, total (births per woman) - World Bank Data

https://data.worldbank.org/indicator/SP.DYN.TFRT.IN

ジェンダー・ギャップ・ランキングは、次の、同じ2020年のデータを使う。

Global Gender Gap Report 2020

https://www.weforum.org/reports/gender-gap-2020-report-100-years-pay-equality/

どちらにも掲載されている、153か国のデータを使って、ジェンダー・ギャップ・ランキングと、

少子化のつながりの強さを確認する。