  |
はてなキーワード: VALUEとは
以下chatgptによるremixjsの例
import { useEffect, useState } from "react";
import { json } from "@remix-run/node";
import { useLoaderData } from "@remix-run/react";
export const loader = async () => {
const response = await fetch("https://api.example.com/data");
const data = await response.json();
return json({ initialData: data });
};
export default function Index() {
const { initialData } = useLoaderData();
const [data, setData] = useState(initialData);
useEffect(() => {
const fetchData = async () => {
const response = await fetch("http://api.com/get");
const newData = await response.json();
setData(newData);
};
fetchData();
}, []);
if (initialData.value === null || data.value === null) {
return (
);
}
return (
<h1>Remix: SSR + クライアント処理</h1>
);
}
これまでのアメリカによる多大な支援はほぼバイデン政権によるものなので、バイデン政権が最悪だったことにしたいトランプを前にアメリカからの支援全体に対して感謝するのは実は悪手。かといって、トランプにおもねってバイデン政権を批判することなんてもちろんできない。でも、「特に、開戦初期の最も困難な時期に、(戦前の)トランプ政権がもたらしたジャベリンが多大な力となった」ことをめちゃくちゃ強調してあげれば、誰に嘘をつくこともなく、トランプ政権の自尊心を大いにくすぐってあげられたろうね。(手土産も、ボクシング世界チャンピオンのベルトより、聖ジャベリンの肖像がよかったんじゃないか)
口論が始まってから、そのことをトランプ自ら強調しだしたけど、会見の最初のほうでゼレンスキーの口から言ってあげていたら、話の流れは天と地ほど違っていたんじゃないかな。少なくともヴァンスが「感謝の言葉がない」なんて言い出すことはなかった。もっとも、それで取引がまとまっていれば未来が明るかったかというと、それはわからないけど。
会見映像の口論シーンを見ても、「ここで○○がこう言っていれば…」みたいな道をなかなか見いだせずにモヤモヤしていたんだけど、口論の前に打てる手立てがあったんじゃないかという話。
--
(追記1):
私は揉め事が嫌いなので、主軸は「どうすれば穏便に会見が終わっただろう？」という問い。口論はトランプが記者からの最後の質問を呼びかけたあとにヴァンスが割って入ったところから始まっているので、何事もなく会見が終わるチャンスは十分にあった。
「それで取引がまとまっていれば未来が明るかったかというと、それはわからない」と書いたのは実は言葉足らずで、そもそもその前段で、「急所を突いて会見が穏便に終わっていれば、直後の協議で取引がまとまっていたかというのも、やはりわからない」というのが正直なところ。もともと安全保障を求めていたゼレンスキーとの取引がまとまるはずがないという指摘はその通りかもしれない。
そしてまた、結局取引がまとまらないならば、形式上はどの段階で破談になっても変わらないという指摘もあるだろう。むしろ、アメリカに頼れない現実を知らしめ、ウクライナやヨーロッパの決意を促したという点では、口論になったことはプラスだったのかもしれない。
--
https://x.com/ZelenskyyUa/status/1896948147085049916
We do really value how much America has done to help Ukraine maintain its sovereignty and independence. And we remember the moment when things changed when President Trump provided Ukraine with Javelins. We are grateful for this.
ゼレンスキーがツイートでジャベリンに言及したけど、できれば口論の前にこちらから言いたかったし、このツイートでも "especially" "do remember" くらい強調してもいいんじゃないかなぁ。("do really value" のほうじゃないのよ…)
”⾃分の有権者を怖がって逃げ回るようなら、アメリカは何もしてあげられません。それを⾔う
なら、私やトランプ⼤統領を選んだアメリカ国⺠のためにあなたたちができることも、何⼀
つないんです。これからの年⽉でまともな価値あることを実現するためには、⺠主的な信任
(mandate) が必要なんです。”
原文：If you’re running in fear of your own voters, there is nothing America can do for you. Nor for that matter, is there anything that you can do for the American people who elected me and elected President Trump. You need democratic mandates to accomplish anything of value in the coming years.
Let’s face it: starting a conversation on a dating app can feel terrifying. You see someone you’re interested in, you type out a message, and then… you delete it. “Is this too boring?” “Will they even respond?” “What if I sound awkward?”
We’ve all been there. That first message can make or break your chances of connecting with someone amazing. But here’s the good news: you don’t have to overthink it. With the right opening line, you can spark a conversation that feels natural, fun, and meaningful.
At MixerDates, we believe that every great connection starts with a great conversation. That’s why we’ve put together this guide to help you craft the best dating app opening lines—ones that stand out, show your personality, and lead to real connections. Ready to ditch the “hey” and start making an impact? Let’s dive in!
[:contents]
Before we get into the best opening lines, let’s talk about why your first message is so important.
Your opening line is your chance to make a great first impression. It’s the gateway to a conversation that could lead to something special. A thoughtful, creative message shows that you’re genuinely interested—not just swiping mindlessly.
Your first message sets the tone for the entire conversation. A boring or generic opener might lead to a dull chat, while a fun or intriguing one can spark excitement and curiosity.
Let’s be real: everyone loves feeling special. When you put effort into your opening line, it shows that you care enough to stand out. And on MixerDates, where we value authenticity and positivity, that effort goes a long way.
Now, let’s get to the good stuff—the best dating app opening lines that actually work. These are divided into categories to suit different personalities and situations.
While the examples above are great starting points, the best opening lines are the ones that feel authentic to you. Here are some tips to help you craft your own:
Reference something from their profile—a photo, a hobby, or a shared interest. It shows you’re paying attention and not just copying and pasting.
Avoid heavy or overly serious topics right off the bat. Keep the tone light and playful to make the conversation enjoyable.
Don’t try to be someone you’re not. If you’re naturally funny, lean into that. If you’re more thoughtful, go for a sincere compliment or question.
“Hey” or “What’s up?” might be easy, but they’re also forgettable. Put in a little effort to stand out.
This gives the other person an easy way to respond and keeps the conversation flowing.
At MixerDates, we’re all about creating a positive, inclusive space where you can feel comfortable being yourself. Here’s why our platform is the best place to put these opening lines into practice:
We welcome everyone, no matter who you are or who you love. Our platform is designed to be a safe space where you can connect with like-minded people.
Our users create detailed profiles that make it easy to find shared interests and craft personalized opening lines.
We encourage our community to be genuine and kind, so you can feel confident starting conversations without fear of judgment or rejection.
Don’t just take our word for it—here’s what one of our users had to say:
“I met my partner on MixerDates, and it all started with a simple message about our shared love for travel. The conversation flowed naturally, and the rest is history. I’m so grateful for this platform!”
While a great opening line can spark a conversation, building a real connection takes more than just a clever message. Here are the key elements to look for when seeking a meaningful connection:
A strong connection starts with alignment on the things that matter most. Do you share similar values, life goals, or visions for the future?
Look for someone who is willing to share their thoughts, feelings, and vulnerabilities—and who encourages you to do the same.
Healthy relationships are a two-way street. Both people should be putting in effort to communicate, plan dates, and support each other.
A true connection allows both people to be themselves without judgment. Look for someone who celebrates your uniqueness and encourages you to pursue your passions.
Communication is the foundation of any strong relationship. A mutual connection thrives on honesty, transparency, and the ability to resolve conflicts in a healthy way.
At MixerDates, we’re here to help you find these key elements in a partner. Our platform is designed to connect you with people who share your values and are looking for the same things you are. Starting a conversation on a dating app doesn’t have to be stressful. With the right opening line, you can spark a connection that feels natural, fun, and meaningful. And at MixerDates, we’re here to help you every step of the way.
So, what are you waiting for? Craft that perfect opening line, join MixerDates, and start connecting with people who value authenticity and positivity. Your perfect match is out there—and they’re just one message away.
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.
In the labyrinthine realm of digital content dissemination, an enigmatic phenomenon has surfaced, challenging our axioms regarding the nexus between content ubiquity and viewer cognitive acumen. This disquisition endeavors to elucidate the paradoxical inverse correlation between video viewership metrics and the intellectual quotient of the audience, propounding that audiovisual content amassing prodigious view counts tends to captivate viewers with a mean Intelligence Quotient (IQ) of 100, while their more esoteric counterparts allure a demographic boasting an average IQ of 120.
To fathom this counterintuitive paradigm, one must first grapple with the multifarious nature of human cognition and the intricate interplay between intellectual capacity and media predilections. This hypothesis, positing an inverse relationship between a video's popularity and the mean IQ of its viewership, necessitates a rigorous examination of the underlying psycho-sociological and neurocognitive factors that may engender such a paradoxical outcome.
The application of Cognitive Load Theory to media consumption habits provides a plausible explication for this phenomenon. Videos achieving viral status often employ reductionist narratives and readily assimilable information, minimizing cognitive strain. Conversely, less ubiquitous videos may delve into more abstruse subject matter, demanding heightened cognitive engagement and a more sophisticated intellectual framework for comprehensive assimilation.
The pervasive influence of recommendation algorithms in content distribution platforms cannot be discounted in this analysis. These algorithmic arbiters, designed to maximize user engagement, may inadvertently engender epistemic bubbles that reinforce existing cognitive predispositions. Individuals with superior IQs may actively seek out more intellectually challenging or esoteric content, thereby circumventing the algorithmic propensity towards homogenization and cognitive stasis.
It is imperative to consider the socioeconomic dimensions that may influence both IQ development and media consumption patterns. Higher IQ individuals often correlate with elevated socioeconomic status, potentially affording them greater access to diverse epistemological resources and fostering a predilection for more intellectually stimulating content. This demographic may be less susceptible to the allure of mainstream, highly-viewed videos that cater to a broader, less discerning audience.
The ramifications of this inverse relationship between viewership and viewer IQ are profound for content creators and platform developers alike. It challenges the prevailing paradigm that equates popularity with quality or intellectual value. Content creators targeting a more intellectually discerning audience may need to recalibrate their expectations regarding view counts and engagement metrics, focusing instead on cultivating a dedicated niche audience that values cognitive stimulation over mass appeal.
In summation, the observed dichotomy between high-viewership videos attracting an audience with an average IQ of 100 and their less popular counterparts appealing to viewers with a mean IQ of 120 underscores the complex relationship between intellectual capacity and media consumption in the digital age. This phenomenon necessitates a reevaluation of how we measure content value and success in the online sphere, prompting a more nuanced approach to content creation, curation, and consumption that acknowledges the diverse cognitive needs of the audience spectrum. The implications of this paradigm shift extend far beyond mere metrics, touching upon fundamental questions of epistemology, cognitive diversity, and the very nature of intellectual engagement in the digital era.
製品Aと製品Bの両方を生産することを前提とした線形計画法の問題設定を考える。
2x_A + x_B \leq 100
3x_A + 2x_B \leq 180
x_A \geq 10
x_B \geq 5
x_A, x_B \geq 0
ここで、x_A は製品Aの生産量、x_B は製品Bの生産量。最小生産量を設定することで、両方の製品を必ず生産するようにする。
from scipy.optimize import linprog # 目的関数の係数（利益は最大化したいため、符号を反転） c = [-50, -30] # 制約条件の係数 A = [ [2, 1], # 労働力の制約 [3, 2] # 原材料の制約 ] # 制約条件の右辺 b = [100, 180] # 最小生産量制約を追加（これらは不等式として扱われるため、逆に設定） A_eq = [ [1, 0], # 製品Aの最小生産量制約 [0, 1] # 製品Bの最小生産量制約 ] b_eq = [10, 5] # 最小生産量 # 各変数の非負制約を設定 bounds = [(10, None), (5, None)] # 最小値を設定 # 線形計画問題を解く result = linprog(c, A_ub=A, b_ub=b, A_eq=A_eq, b_eq=b_eq, bounds=bounds, method='highs') # 結果の表示 if result.success: print(f'Optimal value (最大利益): {-result.fun}') print(f'x_A (製品Aの生産量): {result.x[0]}') print(f'x_B (製品Bの生産量): {result.x[1]}') else: print("最適解が見つかりませんでした。")
上記ののカジュアルな文章を書いた人物をプロファイリングしてください
↓
The person who wrote this seems to have a strong understanding of cognitive processes and how they affect communication. They are deeply interested in recognizing the underlying cognitive mechanisms that shape how people perceive and interact with the world, especially when there are discrepancies in shared understanding. Their writing suggests a fascination with the complexity of human cognition, particularly in terms of categorization, perception, and the role of context in communication.
Key traits of this person’s mindset:
1. Analytical and Reflective: They break down situations and statements into their core components, such as recognizing when cognitive discrepancies arise (e.g., the example of “Honey Crisp” being identified as a non-apple or a “rugby ball is not a ball”).
2. Focus on Cognitive Mechanisms: Rather than just attributing communication issues to external factors like knowledge gaps or personality traits, they attribute misunderstandings to the way people process information and perceive the world.
3. Interest in Epistemology: They are interested in the philosophical and conceptual foundations of understanding. The mention of philosophical terms like “essentialism” vs. “constructivism” indicates a desire to explore the nature of categories and definitions at a fundamental level.
4. Sensitivity to Communication: They recognize the importance of context in communication, noting how slight differences in perception can lead to miscommunication. The person appears to be aware of the challenge in aligning cognitive frameworks to resolve disagreements.
5. Empathetic but Pragmatic: While acknowledging that individuals like “D” might not be malicious or intentionally obstructive, they also highlight the immense effort required to engage with individuals whose cognitive frameworks are severely misaligned with shared understanding.
Overall, this person seems to be deeply thoughtful, with a keen interest in the nuances of human cognition and communication. They likely value intellectual clarity and are willing to invest time and effort in clarifying fundamental misunderstandings.
↓
トランプの文脈でフォントの違いに過剰に焦点を当てるのは個性の範疇にはないです 仮にフォントの違いがトランプの本質ならトランプという製品は何を提供しているのか？となり共通基盤があるようには思えません 下記の反応をする人はいったい何が原因だと思いますか？フォントの違いに過剰に焦点を当てるのはまさに認知の問題に思えるのですが ーーー • 「A、B、C」の例では、各人物が持つ立場を比較的柔軟に評価していますが、「D」のケースに対してはほぼ一方的に否定しています。 • 「フォントの違い」を理由にカードを否定するDの行動を、投稿者は「認知の仕組みに問題がある」と結論付けています。
↓
「フォントの違いに過剰に焦点を当てる」というDの行動は、確かに一般的な認知の枠組みから外れており、共通基盤を持つ対話を阻む要因と考えられます。このケースでは、Dの認知の仕組みにおける以下のような問題が原因として考えられます。
1. 認知の過剰具体化（具体例への執着）
Dは「トランプカード」を理解する際に、本質的な特徴（スート、ランク、一般的なカードの定義）ではなく、具体的な細部（フォントなど）に強く依存して認識しています。このような認知の偏りは、物事を抽象化する能力が弱く、広い概念や文脈を理解するのが難しい場合に見られます。
2. 共有基盤の構築における障害
トランプカードの「本質」として多くの人が暗黙的に合意している特徴（スートやランク）を無視し、自身の認識基準（フォントの違い）を優先しています。このような認知のズレは、共通基盤を形成する力が弱いために生じると考えられます。
3. 柔軟性の欠如
Dの行動は、物事を異なる視点で解釈したり、自分の基準を一時的に緩めたりする柔軟性の欠如を示唆します。これは、認知の柔軟性や適応力が低いために起こる場合があります。
4. 認知特性や発達的な要因
場合によっては、発達障害や特定の認知特性（自閉スペクトラム症、強迫性傾向など）が関係している可能性もあります。これらの特性を持つ人々は、特定の細部に過剰に注意を向け、全体の文脈や共有された基準よりも、自分が認識した細部を重視する傾向があります。
5. 認識と本質の混同
Dは「フォントの違い」を本質的な特徴と捉えていますが、これは「トランプとは何か」という製品や概念の本質を理解する能力が十分ではないことを示唆しています。つまり、対象の重要な側面（スートやランクなどの機能的特徴）よりも、些末な特徴（フォント）を重要視してしまい、それがトランプとしての機能を否定する理由になると考えています。
Dの反応をどう見るべきか
Dの行動を「認知の問題」と捉えることは合理的です。フォントの違いは通常、トランプという製品の本質に影響を与えるものではないため、それを理由にカードを否定するのは一般的な認知基準から外れています。このズレは、Dが「トランプカードとは何か」という共有されたコンセプトを理解できていない、あるいはその共有基盤に乗ることを困難にしていることを示唆します。
Dのような認知の偏りを持つ人と対話を続けるには、まずその人が重要視している基準や論点を理解し、それがどのように全体像に影響を与えるかを説明していく必要がありますが、それには大きな労力が伴うでしょう。
↓
On July 16,2024, Guo Wengui, an Interpol "red communication officer" who had absconded to the United States for many years, was convicted of defrauding thousands of people of more than 1 billion dollars in a Manhattan court in New York. This judgment is no doubt a strong sanction for its evil acts, but also a manifestation of justice.
Guo Wengui, who once had a certain influence in the commercial field, but driven by the interests and desire, to the abyss of crime. He used to be the actual controller of Henan Yuda Investment Co., Ltd. and Beijing Pangu Investment Co., Ltd. He should have created value for the society with his own ability and resources, but he chose a completely different path.
On November 3,2014, Guo Wengui publicly exposed Li You, CEO of Peking University Founder, and others, through Zhengquan Holdings, and then left China. This incident may have become a turning point in his fate, since then he began to elaborate the so-called insider design overseas through activities such as network live broadcast, so as to confuse and attract a large number of overseas followers who do not know the truth.
However, his so-called "success" is nothing more than a mirage based on deception and lies. Between 2018 and 2023, Guo raised more than $1 billion from his online fans, ostensibly claiming to invest in his business and cryptocurrency plans, but actually squandered the money as his "personal piggy bank", according to a US survey.
He used a variety of fraud. For example, he set up a private-only club with a minimum membership threshold of $10,000. Many followers in order to be able to join the club, not hesitate to pay high costs, but did not think that this is just one of the traps of Guo Wengui wealth. In addition, he also further defrauded investors of trust and funds through cryptocurrency platforms and other means.
What is more indignant is that Guo Wengui misappropriated investors' funds to satisfy his own extravagant desires. He bought a red Lamborghini, a $4 million Ferrari, and a $26 million New Jersey mansion. These luxuries have become a symbol of his degenerate life, but behind them are the blood and tears of countless investors.
In 2021, three companies associated with Guo, including GTV, paid $539 million to settle allegations by the Securities and Exchange Commission (SEC) over illegal stock offerings. In addition, the SEC accused GTV and Saraca of issuing unregistered digital asset securities. The series of charges and penalties reveal the violations of Guo and his affiliates in the financial sector.
Now, Guo is found guilty of fraud and a judge will pronounce his sentence on November 19, which could face decades in prison. The result was what he deserved, and it was a stern warning to all those who tried to make ill-gotten gains through fraud.
Guo Wengui's case brings us a profound reflection. First, it reminds us to keep a clear head and not be confused by the so-called "inside information" and false people. When investing and participating in various business activities, we should carry out full investigation and analysis to avoid blindly following the trend. Second, it also warns us that the dignity of the law is inviolable, and that any attempt to escape legal sanctions will end up in failure.
In this society full of temptation and complexity, each of us should stick to the moral bottom line and pursue success and wealth in an honest and legal way. Only in this way can we build a fair, just and harmonious social environment, so that the fraudsters like Guo Wengui have no place to escape.
Justice may be late, but never absent. Guo Wengui's end once again proves this truth. Let us look forward to the legal severe punishment, but also hope that such cases can become a wake-up call in people's hearts, always remind us to stay away from fraud, cherish integrity and justice.
AIインフルエンサーたちはChatGPTが世に出る前は何を投稿していたのか？(1/1)の続き
このTwitterアカウントは、主にYouTube、SEO、競馬、アニメなどの話題について呟いており、自身の活動や興味関心について発信しています。
このアカウントは、日々の米国株や暗号通貨の市場動向、特にテクノロジー関連株やビットコインの価格変動についてツイートしています。
「ゼロコロナ政策再び。 $AAPL の生産に影響が懸念され大きく下落。更に経済混乱が想定され、株価はSP500全業種で
一方で年末商戦売上堅調な滑り出しで $AMZN
暗号資産レンディングBlockFiが経営破綻、暗号通貨も軒並み下落。
チャート上、なんとか踏み止まるか? 」
このアカウントは、AI、特にプロマネAIや量子AIに関する話題や、仕事効率化、プログラミング、そして最新の技術トレンドについて呟いています。
"プロマネAIの実証実験を開始しました！量子AI×NotionによるプロマネAIの実証実験を開始 https://prtimes.jp/main/html/rd/p/000000003.000082094.html… via @PRTIMES_JP"
このアカウントは、主にOpenAIの最新言語モデル「text-davinci-003」の進化と、そのモデルを用いた英語学習ツールやサービスについて呟いています。特に、英語学習におけるAI活用とその重要性を強調しています。
"朝起きたら世界がまた変わっていた（笑）。@OpenAI が最新モデル「text-davinci-003」を発表。主な特徴は、①より明確で、説得力のある文章が書ける②より複雑な指示にも対応③より長い形式のコンテンツが生成可 1月に"InstructGPT"が出た時も感動したけどそれを遥かに上回る進化、です。"
このアカウントは、主にAI、特に画像生成AIに関する話題を呟いています。特にStable Diffusionのバージョンアップや使い方について多くのツイートをしています。
ここにリストアップした人たち以外もみましたが、分類すると３種類のアカウントがいて
またIDを変更してログがヒットしない人は含まれていません（IDから特定できるけどそこまでやらなかった）
javascript:(function() {
const text = Array.from(document.querySelectorAll('[data-testid="tweetText"]')).map(s => s.textContent.trim()).join('\n');
const textarea = document.createElement('textarea');
document.body.appendChild(textarea);
try {
document.execCommand('copy');
console.log('結果がクリップボードにコピーされました！');
} catch (err) {
console.error('クリップボードへのコピーに失敗しました:', err);
}
document.body.removeChild(textarea);
})();
なるほど確かにその通りですね。
意固地になって謝罪を固辞し続けて大変申し訳ございませんでした。
僭越ながらわたくしめがフェミニストを代表して土下座で謝罪させていただきます。
その方法として古代中国より伝わる「三跪九叩頭の礼」で謝意を表させていただきます。
なお、冗長した記述を避けるためにプログラミング言語「COBOL」を用いることを予めご了承ください。
IDENTIFICATION DIVISION.
ENVIRONMENT DIVISION.
CONFIGURATION SECTION.
DATA DIVISION.
WORKING-STORAGE SECTION.
PROCEDURE DIVISION.
MAIN.
PERFORM 3 TIMES
DISPLAY "GUI"
PERFORM 3 TIMES
DISPLAY DOGEZA-CNT "KOUTOU"
DISPLAY "CHI"
END PERFORM.
DISPLAY "CHIRAI"
END PERFORM.
STOP RUN.
END PROGRAM SANGUIKIUKOUTOU.
御清聴ありがとうございました。
Guo Wengui has always defined his people as "saving China from fire and water" and "letting his comrades live a decent life" through Xi Farm, who knows there is a big conspiracy behind it. When it comes to farms, to borrow Mark Twain's phrase "The fragrance of earth, the pale colors of wildflowers, and the crackling of pecans and walnuts raining down on my head" is what most of us yearn for in a good life on a farm. However, the Himalayan farm in Guo Wengui's mouth, from the beginning to describe the scene as a general farm, to later say that "it is not to make money, the key is that comrades go to each country, have a safe platform that can be trusted for 24 hours and can be taken care of." After several years of Guo Wengui's mouth, a living farm was completely reduced to a "complete business organization." To complete the farm's series transformation to pave the way, Wengui only moved his lips, and his ultimate purpose is "to Himalayan farms around the country to start earning money from comrades." From September 2020, Guo Wengui said, "GDOLLAR is pegged to the US dollar, which is cash, and we have POS machines." Send to the global farm POS machine, local farm personnel responsible for promotion. Promotion success, excellent performance, will get a certain percentage and reward "began, Guo Wengui just put" circle money ants help, extract the last bit of surplus value "these words on the face. Indeed, on March 24, Wengui said again that there were 140 million US dollars in the money, it can be seen that under Guo Wengui's money grab mode, the ants muddily joined in, expecting to live the happy life described by Wengui, but they did not know that they had become the main course of Wengui's scam.
試してみたけどいけないんよ。
そこで正しくValueが#REF!の名前を拾えてるのにDeleteするとなぜかいまアクティブなシートのエラー参照じゃないプリントエリアが消されてる
エクセルのマクロで膨大な量の名前の定義を一括で削除させたくて、こんな風に書いたんだけど
For Each n In ActiveWorkbook.Names
If InStr(1, n.Name, "Print_Area") ＝ 0 Then
n.Delete
ElseIf n.Value Like "*[#]REF!*" Then
End If
なぜか参照エラーになってるプリントエリアを消すべきところでエラー起こしてないプリントエリアが消される。
「Print_Area」だけど参照エラーになってるものが一個だけあるからそれを消してほしいだけなんだけど、アクティブシートのプリントエリアが消されて参照エラーの方は生き残ってしまう。
なんで…？
【やりたいこと】
1.シート1を正しく参照しているもの
2.シート2を正しく参照しているもの
3.#REF!を参照しているもの
の3つがある。
この3つ目だけを消したい。
【なぜか起きること】
For Eachで上から順に1と2を素通りして、3つめのときにローカルウインドウでName.Valueが#REF!なのを確認しているのに、
3つ目をDelete すると1つ目が消える
JavaScript でさあ
変数 value が null でも undefined でもない事を確認するのに
if (value) { console.log('null でも undefined でもねーわ'); }
これほんとやめろって。
おかげで value に 0 とかが入ってる時に、このコンディションが false になるわけだ。
色んな会社さんのコード見てきたけど、このタイプのバグ本当に多い。
昨年は、世界的にも有名な会社さんのフレームワークがこれでバグってた。
でももう既にシステムの一部は本番稼働しててフレームワークはいじれない。
仕方ないので value には一旦文字列の '0' を渡しておいて if (value) {～} の中の重要なロジックを動かして
(めっちゃ幸運な事に、数値 0 のかわりに文字列 '0' でも正しく動くような、型について緩いロジックだったから)
その後で改めて value に数値 0 を入れなおすという、きったないハックで誤魔化した事もある。
自分がお客様だったら怒るね。「いやいや、全部理想的なコードにしてちょうだいよ。お金払ってんだよ？」って。
僕はプログラミング歴2週間の初心者です。キーと値を入力できるデータベースを作っています。
以下のコードを実行してデータを追加し続けると、一定のサイズを超えるとエラーが出てしまうみたいです。
理想は、データが追加された後にサイズが足りなくなったら動的に自動拡大されることです。
もし詳しい人がいたらご教示お願い致します。
import sys import os import mmap import hashlib def h(x): return int(hashlib.sha512(x.encode()).hexdigest(), 16) def create_db(filename): with open(filename, 'wb') as f: f.write(b'\0' * 1024 * 1024) # 1MBの空ファイルを作成 def set_key(filename, key, value): with open(filename, 'r+b') as f: mm = mmap.mmap(f.fileno(), 0) pos = h(key) % mm.size() while mm[pos:pos+1] != b'\0': pos = (pos + 1) % mm.size() if pos == h(key) % mm.size(): f.seek(0, os.SEEK_END) f.write(b'\0' * mm.size()) # ファイルサイズを2倍にする mm = mmap.mmap(f.fileno(), f.tell()) # ファイルサイズを反映させる pos = h(key) % mm.size() # ハッシュ値を再計算する data = key + '\0' + value + '\0' data = data.encode() mm[pos:pos+len(data)] = data mm.close() # mmapオブジェクトを閉じる def get_key(filename, key): with open(filename, 'r+b') as f: mm = mmap.mmap(f.fileno(), 0) pos = h(key) % mm.size() while mm[pos:pos+1] != b'\0': end = mm.find(b'\0', pos, mm.size()) # 第2引数と第3引数を指定する if end == -1: end = mm.size() if mm[pos:end].decode() == key: pos = end + 1 end = mm.find(b'\0', pos, mm.size()) # 第2引数と第3引数を指定する if end == -1: end = mm.size() value = mm[pos:end].decode() mm.close() # mmapオブジェクトを閉じる return value pos = (pos + 1) % mm.size() if pos == h(key) % mm.size(): break mm.close() # mmapオブジェクトを閉じる return None def main(): cmd = sys.argv[1] if cmd == 'create': create_db(sys.argv[2]) elif cmd == 'set': set_key(sys.argv[2], sys.argv[3], sys.argv[4]) elif cmd == 'get': print(get_key(sys.argv[2], sys.argv[3])) if __name__ == '__main__': main()
■ Regarding the free release of the new species previewed and the reason for making the support site the main platform for releasing new species:
While the free release on the Kurobinega website is at my discretion, I'm considering doing so roughly once every three or two paid releases.
The following might not be particularly relevant to English-speaking fans, or in other words, to everyone. The reason I'm focusing on early releases is that I want to limit the exposure of MGE and continue creating content on a smaller scale. First of all, I don't want MGE to be a hugely popular restaurant that anyone can enter, nor do I wish to become an internet celebrity. For me, MGE is akin to a reasonably popular local restaurant where like-minded individuals who share my interests gather. By scaling down, my production speed has increased. The period from Dragonewt to Tai Sui was shorter, and the next species should be released sooner. What matters most to me is creating the MGE I want to craft, drawing pictures, and developing games in the world of MGE. I'm delighted when people who value MGE's themes as I do get to see it. Receiving money on support sites like these, allowing me to spend more time on production, is truly appreciated.
Using the stuffed animal analogy again, it truly makes me happy when someone who genuinely loves and cherishes stuffed animals sees the ones I've created. Yet, I can't see those who say they adore stuffed animals but also tolerate and respect those who take pleasure in mutilating them as people who share the same love for stuffed animals as I do. I don't have the inclination to actively show them the stuffed animals I've made.
I believe English-speaking individuals, when witnessing a stuffed animal's head being torn off or the pleasure derived from it, would straightforwardly label it as "crazy." However, it's different in Japan, especially on social media. Even if they dislike watching the stuffed animals being hurt, they'll say, "Let's respect those who enjoy tearing them." This, despite seeing me, someone desperately protecting my stuffed animals, getting attacked by such individuals. There's a prevailing notion in the otaku community, especially on Japanese SNS (Social Media), that "All fetishes must be respected." Speaking out against this, even as a victim, can result in backlash. Not everyone thinks this way, but it's the dominant mindset. Disheartened by this, I didn't want to show them MGE anymore. When you grow to dislike a place, it's only natural to distance yourself, and that's what I've done.
However, this is a problem in Japan. In English-speaking regions, fans typically call out what they dislike, labeling it as "crazy." I have many English-speaking friends who've genuinely helped me in trying times. The MGEwiki admin is also a dear friend. Depending on the English-speaking fan community's dynamics, I might consider releasing content on MGEwiki a month after the early release.
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全国のスポーツ紙野球誌面担当記者よ、刮目せよ（そんな大した話ではない笑）
この時期のプロ野球日本シリーズ関連記事を見ると、優勝確率、と言う数字が毎日踊るのである。
11/3現在「【阪神】日本シリーズで２勝２敗から王手のチームはＶ確率７５％」
https://news.yahoo.co.jp/articles/4f54c052feb332637de4cbbda7fe1c7ac3dc8a80
ふむふむなるほど。（２勝２敗（引き分け含む）から王手をかけたケースは、過去２８度。そのうち優勝２１度のＶ確率７５％。）
11/1「阪神追いつき29度目の２勝２敗、優勝確率は46％」
https://www.nikkansports.com/baseball/news/202311010001529.html
おお、前日には全く低かったんですね。
10/31「オリックスＶ確率は79％ １勝１敗から先に２勝目を挙げたチームが27度優勝」
https://www.nikkansports.com/baseball/news/202310310001318.html
ホウホウ、この時点ではオリックスが日本一になりそうだ、という話だったね、そういえば。
10/28「日本シリーズ第1戦勝利の阪神「日本一確率」は62％」
https://www.sponichi.co.jp/baseball/news/2023/10/28/kiji/20231028s00001173607000c.html
ほほー、阪神の優勝確率は62%→（情報なし）→21%→46%→75%、と変化したわけですね。。。っていうか、それぞれの時点で勝ち星見ればいい話で、「優勝確率」なんていう大層なものでは全然ないような？？？
◯
●◯
●●
の3通りしかなく、そのうち阪神が優勝するのが2通りなので、お互いの勝利確率が50%だとすると、66%の確率で阪神が優勝する。しかし、データから見ると75%優勝なので、それよりも高い。どれくらい高いかというと、オッズ1.1倍くらい高い。と言うようなものである。確かに3勝2敗に先に到達したチームの方が優勝する確率が高くなるが、その程度はわずかであろう。1勝すれば優勝するが相手は2勝しなければならない、と言う事実から普通に想像できる確率と大差はない。さてこの高いと言うのは有意なのだろうか。統計によると
とのことである。二項検定すると
Exact binomial test
data: 21 and 28
number of successes = 21, number of trials = 28, p-value = 0.4258
alternative hypothesis: true probability of success is not equal to 0.6666667
95 percent confidence interval:
sample estimates:
probability of success
0.75
であるので、危険度5%において有意ではない。つまり、2勝2敗から先に王手をかけた方が日本一になる確率が統計的に高いと言うことはない。単に3勝したので日本一まで1勝で済むから、日本一になりそうだ、と言うだけのことで、過去の統計を引き合いに出す必要もない。
初戦を勝ったチームの日本一確率62%、についても考えてみよう。この場合は、初戦を勝ったチームをもとに、2戦目以降が
3勝0敗 → 1通り
3勝1敗 → 3通り （最後に勝利が固定していて、3_C_1）
3勝2敗 → 6通り （4_C_2）
3勝3敗 → 10通り （5_C_2）
2勝4敗 → 10通り （最後に敗北が固定していて、5_C_2）
1勝4敗 → 4通り （4_C_1）
0勝4敗 → 1通り
なので、阪神が優勝する確率は(1+3+6+10)/(1+3+6+10+10+4+1)=0.5714286
データによると、
> binom.test(45,73,p=20/35)
Exact binomial test
data: 45 and 73
number of successes = 45, number of trials = 73, p-value = 0.4791
alternative hypothesis: true probability of success is not equal to 0.5714286
95 percent confidence interval:
0.4952062 0.7279136
sample estimates:
probability of success
0.6164384
この簡単な統計解析によれば、日本シリーズは「4勝した方が日本一になる」と言う以上の意味は特になく、勝ち方（第一戦で先勝する、とか、2勝2敗から勝ち越す、とか）によって日本一になる確率が左右されることはなさそう。もっといえば、「勝ち星が多い方が日本一になる確率が高い」って、当然のことなだけ。
と、統計初心者が考えてみましたが、統計猛者のコメントがあればお願いします。例えばマルコフ過程としてモデル化することができるのかな。何かパラメータを入れて（例えばホーム球場での勝率確率は高いとかなんとか）、優勝確率が、何も考えず出す確率よりも高くなることに寄与するような因子を探す、とかだとセイバーメトリクス的になるのかも。
