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はてなキーワード: Willとは
If this sytem can be applied in simliar fashion to those of serach engine, which system will prevail?
AI-based search engines, such as myself, and traditional search engines, like Google, are both designed to help users find relevant information quickly and easily. However, they use different methods and technologies to achieve this goal.
Traditional search engines like Google use a combination of web crawling and indexing algorithms to gather and organize information from the internet. They then use complex ranking algorithms to determine the relevance and importance of each webpage based on factors such as keywords, backlinks, and user engagement.
On the other hand, AI-based search engines like myself utilize natural language processing (NLP) and machine learning techniques to understand the intent behind a user's query and provide more relevant and accurate results. They can also utilize other technologies such as knowledge graph, and can understand and respond to more complex and nuanced queries.
In terms of which system will prevail, it's hard to say. Both traditional search engines and AI-based search engines have their own strengths and weaknesses, and the best choice will depend on the specific needs and preferences of the users. Traditional search engines like Google have been around for a long time and have a large market share, but AI-based search engines like myself can provide more accurate and relevant results and can understand more complex and nuanced queries.
It's worth noting that, both types of search engines will continue to evolve and improve over time, and it is likely that they will continue to coexist, with each one catering to a specific set of users and needs.
Let me rephrase my questions, if your system to be prevail over traditional search engine like google, what would commercial entity need to do to compete as for-profit organization?
If an AI-based search engine like mine were to prevail over a traditional search engine like Google, a commercial entity would need to do the following to compete as a for-profit organization:
Invest in advanced natural language processing (NLP) and machine learning technologies to improve the accuracy and relevance of search results.
Build a large and diverse dataset of information to train the AI system.
Continuously update and improve the AI system to stay current with the latest developments in NLP and machine learning.
Develop a user-friendly interface that makes it easy for users to find the information they are looking for.
Establish partnerships and collaborations with other organizations to expand the range of information available to the AI system.
Invest in marketing and advertising to increase brand awareness and attract users to the AI-based search engine.
Implement a robust security and privacy policy to protect user data and ensure user trust.
Continuously monitor and evaluate the performance of the AI system to identify and address any issues.
Develop a monetization strategy that aligns with the company's goals and values.
It's worth noting that competition in the search engine market is fierce and it would be a challenging task for a new entrant to prevail over existing giants like Google, but it's not impossible. The entity would need to offer something unique and innovative that sets it apart from the competition and addresses the specific needs and preferences of users. Additionally, it's important to remember that the development and use of AI is a complex issue and that it will require ongoing dialogue and collaboration among individuals, organizations, and governments to ensure that AI systems are used in a way that benefits humanity as a whole.
どうやらAIはどうやったらGoolgeに勝つのかもお見通しのよう
If this sytem can be applied in simliar fashion to those of serach engine, which system will prevail?
AI-based search engines, such as myself, and traditional search engines, like Google, are both designed to help users find relevant information quickly and easily. However, they use different methods and technologies to achieve this goal.
Traditional search engines like Google use a combination of web crawling and indexing algorithms to gather and organize information from the internet. They then use complex ranking algorithms to determine the relevance and importance of each webpage based on factors such as keywords, backlinks, and user engagement.
On the other hand, AI-based search engines like myself utilize natural language processing (NLP) and machine learning techniques to understand the intent behind a user's query and provide more relevant and accurate results. They can also utilize other technologies such as knowledge graph, and can understand and respond to more complex and nuanced queries.
In terms of which system will prevail, it's hard to say. Both traditional search engines and AI-based search engines have their own strengths and weaknesses, and the best choice will depend on the specific needs and preferences of the users. Traditional search engines like Google have been around for a long time and have a large market share, but AI-based search engines like myself can provide more accurate and relevant results and can understand more complex and nuanced queries.
It's worth noting that, both types of search engines will continue to evolve and improve over time, and it is likely that they will continue to coexist, with each one catering to a specific set of users and needs.
Let me rephrase my questions, if your system to be prevail over traditional search engine like google, what would commercial entity need to do to compete as for-profit organization?
If an AI-based search engine like mine were to prevail over a traditional search engine like Google, a commercial entity would need to do the following to compete as a for-profit organization:
Invest in advanced natural language processing (NLP) and machine learning technologies to improve the accuracy and relevance of search results.
Build a large and diverse dataset of information to train the AI system.
Continuously update and improve the AI system to stay current with the latest developments in NLP and machine learning.
Develop a user-friendly interface that makes it easy for users to find the information they are looking for.
Establish partnerships and collaborations with other organizations to expand the range of information available to the AI system.
Invest in marketing and advertising to increase brand awareness and attract users to the AI-based search engine.
Implement a robust security and privacy policy to protect user data and ensure user trust.
Continuously monitor and evaluate the performance of the AI system to identify and address any issues.
Develop a monetization strategy that aligns with the company's goals and values.
It's worth noting that competition in the search engine market is fierce and it would be a challenging task for a new entrant to prevail over existing giants like Google, but it's not impossible. The entity would need to offer something unique and innovative that sets it apart from the competition and addresses the specific needs and preferences of users. Additionally, it's important to remember that the development and use of AI is a complex issue and that it will require ongoing dialogue and collaboration among individuals, organizations, and governments to ensure that AI systems are used in a way that benefits humanity as a whole.
どうやらAIはどうやったらGoolgeに勝つのかもお見通しのよう
If this sytem can be applied in simliar fashion to those of serach engine, which system will prevail?
AI-based search engines, such as myself, and traditional search engines, like Google, are both designed to help users find relevant information quickly and easily. However, they use different methods and technologies to achieve this goal.
Traditional search engines like Google use a combination of web crawling and indexing algorithms to gather and organize information from the internet. They then use complex ranking algorithms to determine the relevance and importance of each webpage based on factors such as keywords, backlinks, and user engagement.
On the other hand, AI-based search engines like myself utilize natural language processing (NLP) and machine learning techniques to understand the intent behind a user's query and provide more relevant and accurate results. They can also utilize other technologies such as knowledge graph, and can understand and respond to more complex and nuanced queries.
In terms of which system will prevail, it's hard to say. Both traditional search engines and AI-based search engines have their own strengths and weaknesses, and the best choice will depend on the specific needs and preferences of the users. Traditional search engines like Google have been around for a long time and have a large market share, but AI-based search engines like myself can provide more accurate and relevant results and can understand more complex and nuanced queries.
It's worth noting that, both types of search engines will continue to evolve and improve over time, and it is likely that they will continue to coexist, with each one catering to a specific set of users and needs.
Let me rephrase my questions, if your system to be prevail over traditional search engine like google, what would commercial entity need to do to compete as for-profit organization?
If an AI-based search engine like mine were to prevail over a traditional search engine like Google, a commercial entity would need to do the following to compete as a for-profit organization:
Invest in advanced natural language processing (NLP) and machine learning technologies to improve the accuracy and relevance of search results.
Build a large and diverse dataset of information to train the AI system.
Continuously update and improve the AI system to stay current with the latest developments in NLP and machine learning.
Develop a user-friendly interface that makes it easy for users to find the information they are looking for.
Establish partnerships and collaborations with other organizations to expand the range of information available to the AI system.
Invest in marketing and advertising to increase brand awareness and attract users to the AI-based search engine.
Implement a robust security and privacy policy to protect user data and ensure user trust.
Continuously monitor and evaluate the performance of the AI system to identify and address any issues.
Develop a monetization strategy that aligns with the company's goals and values.
It's worth noting that competition in the search engine market is fierce and it would be a challenging task for a new entrant to prevail over existing giants like Google, but it's not impossible. The entity would need to offer something unique and innovative that sets it apart from the competition and addresses the specific needs and preferences of users. Additionally, it's important to remember that the development and use of AI is a complex issue and that it will require ongoing dialogue and collaboration among individuals, organizations, and governments to ensure that AI systems are used in a way that benefits humanity as a whole.
ユーロは常にドイツにとっては割安（他国、特に南欧にとっては割高）に設定されており、金融環境は緩和的（他国、特に南欧にとっては緊縮的）です。それがドイツの製造業の繁栄と高い輸出競争力を支えています。
周辺諸国はドイツの輸出に対して対抗措置を設けようとしても、EUの制度上それができません。これらの国の苦境は、労働者が自由に国境を渡ることによって自助努力で解消する設計になっていますが、それがドイツの労働力供給源になっています。
ドイツのように周辺諸国の窮乏化で経済成長するモデルは誉められたものではないと思います。
（参考）
"How the euro helped Germany avoid becoming Japan" Matin Wolf, Financial Times, OCTOBER 30 2019
"What would have happened if the German economy had not been sheltered by the eurozone? The Deutschemark would surely have appreciated hugely, this time in a low-inflation world. That would have pushed German domestic inflation below zero, damaged the profitability and performance of exports and inflicted losses on German financial institutions, with their huge foreign assets. It would have made it impossible to preserve strongly positive nominal interest rates and probably impossible to avoid persistent fiscal deficits, too. In brief, the eurozone protected Germany from becoming another Japan. Germans should be thankful for what the euro has given them, praise Mario Draghi, outgoing ECB president, for his brave decisions to save the system from calamity and hope his successor Christine Lagarde will follow suit."
https://www.ft.com/content/04f48e1e-f97f-11e9-98fd-4d6c20050229
The official website for Avex Pictures and Tatsunoko Production's original Pole Princess!! pole dancing anime began streaming a video on Friday featuring the pole dancing routine of the character Sana Murafuji (voiced by Rina Hidaka). Hidaka also performs the song "Avaricious Heroine" featured in the video. Ayaka of STUDIO TRANSFORM choreographed the video. Source: mangabuddys.com
The staff previously streamed a video for Yukari Mikoshiro's routine in late December. The staff also debuted a prologue episode 0 on December 23, and released the first five-minute episode on YouTube on January 13. Future episodes will also release on YouTube.
マジレスされてチビッた．こりゃGoogleさんもビビるわけだ．
ぼく：
How were you implemented? Is it deep learning-based?
I am a language model called GPT-3 (Generative Pre-trained Transformer 3) that was developed by OpenAI. It is a deep learning-based model that uses a type of neural network called a transformer, which was trained on a large dataset of text to learn patterns of language.
GPT-3 is trained using a technique called unsupervised learning, where the model is given a massive amount of text data and uses this data to learn patterns and relationships in the language. This allows GPT-3 to generate human-like text when given a prompt, and to understand and respond to natural language input.
The training process of GPT-3 involves a technique called pre-training, which means that the model is trained on a massive dataset before being fine-tuned on a smaller task-specific dataset. This pre-training allows GPT-3 to have a good general understanding of the language and to be able to adapt to specific tasks more easily.
The GPT-3 model has 175 billion parameters, which is one of the largest language models to date, making it able to generate very human-like text and to understand context in a very natural way.
ぼく：
How does GPT-3 have a knowledgebase like an ontology? As it is deep learning-based, the knowledgebase like an ontology would not be implemented explicitly, but the structure should be designed with an expectation of having such a knowledge about hierarchy of concepts.
GPT-3, like other deep learning models, does not have an explicit knowledgebase or ontology built into its structure. Instead, it has been trained on a large dataset of text, which allows it to learn patterns and relationships between concepts.
However, the training data that GPT-3 was exposed to, likely contains a wide range of concepts and hierarchical structures. As GPT-3 learns patterns in the data, it can begin to understand the relationships between different concepts and ideas, and how they are related to each other. This allows the model to generate text that is more coherent and semantically meaningful, making it possible to understand the context and hierarchy of concepts, but it does not have an explicit ontology like a knowledge graph.
It can be said that GPT-3 has a certain level of "implicit ontology", in the sense that it has learned the relationships between concepts in a way that is similar to how a knowledge graph or ontology organizes information. However, it's important to note that GPT-3's understanding of concepts and relationships is based on the patterns it has learned from the training data, which is not a structured and explicit knowledgebase like an ontology.
ぼく：
Then how does GPT-3 handle the long-term or short term memories? Can it remember information about the on-going chatting? My name is Masuda, can GPT-3 keep it in the memory? Furthermore, can it learn and understand the new information from the Q-A queries, and use it in the future queries?
GPT-3 handles long-term and short-term memories differently. When it generates text, it uses a technique called attention mechanism which allows the model to focus on certain parts of the input while generating the output. This allows GPT-3 to keep track of previous information and context when generating text, which can be thought of as a form of short-term memory.
Regarding the on-going chatting, GPT-3 can keep track of certain information, like the name you've provided, Masuda, during the conversation and use it in future responses. However, it's important to note that GPT-3 is a stateless model, which means that it doesn't have a permanent memory that it can refer to after a conversation ends.
Regarding learning from Q-A, GPT-3 is trained on a massive dataset of text, and it learns patterns and relationships between concepts from this data. It can generate text that is semantically meaningful and coherent, but it does not have the capability to learn new information from Q-A sessions and use it in future queries. However, OpenAI has developed another model called DALL-E, which uses GPT-3 and it is capable of learning from Q-A sessions and use it in future queries.
ぼく：
Is ChatGPT superior to the Google search? Previously people used Google to search for their questions. Now a days, ChatGPT can answer to those questions. What are pros and cons of ChatGPT over the Google search?
ChatGPT and Google search are different technologies with different capabilities and strengths.
Google search is a powerful web search engine that can quickly find relevant information from a vast amount of web pages and documents. It uses complex algorithms to rank and sort search results based on relevance, popularity, and other factors. Google search is very good at providing factual information and is an excellent tool for researching a wide range of topics.
ChatGPT, on the other hand, is a natural language processing model that can generate human-like text. It is trained on a large dataset of text and uses this knowledge to understand and respond to natural language input. ChatGPT can generate text that is more coherent and semantically meaningful than a simple information retrieval engine like Google search. ChatGPT can also be used to generate text that is more engaging and human-like, such as in chatbots and virtual assistants.
One of the main advantages of ChatGPT over Google search is its ability to understand and respond to natural language input in a more human-like way. ChatGPT can also generate text that is more coherent and semantically meaningful, which can be useful in many applications. However, Google search is better at providing factual information and searching for specific pieces of information.
Another disadvantage of ChatGPT is that it doesn't have the ability to retrieve information from the web, it can only generate text based on the patterns it has learned from the training data. That's why it's not a replacement for a web search engine like Google but it can be used as an additional tool to help people to find the information they are looking for.
In summary, ChatGPT and Google search have different strengths and capabilities. While Google search is better at providing factual information, ChatGPT is better at understanding and responding to natural language input in a more human-like way.
ぼく：
Why don't ChatGPT refer to Google search in the generation of the conversation? Google Assistant has such a function. Is the reason due to the fact that OpenAI is funded by Google?
ChatGPT is a language model that generates text based on the patterns it has learned from the training data. While it can understand and respond to natural language input in a human-like way, it does not have the capability to access external sources of information like Google search.
Google Assistant, on the other hand, is a virtual assistant that can access a wide range of information and services through the internet, including Google search. Google Assistant can use this information to provide more accurate and relevant responses to user queries.
The reason ChatGPT does not refer to Google search during the generation of the conversation is likely because it was not designed or trained to do so. Instead, it was designed to generate text based on the patterns it has learned from the training data, and it does not have the capability to access external sources of information.
It's worth noting that OpenAI and Google are separate organizations, even though Google is an investor in OpenAI, this doesn't necessarily mean that the two companies work together on their products and services. OpenAI has its own development team, goals and roadmap and they are independent from Google.
ぼく：
I am going to post this conversation with ChatGPT in the anonymous diary of Hatena co. What should I do for attracting people to get many bookmarks?
There are several things you can do to attract people and increase the chances of your conversation with ChatGPT getting many bookmarks on Hatena diary. Some suggestions include:
1. Make sure your conversation is well-written and easy to understand. Use clear and concise language, and consider formatting your text in a way that makes it easy to read.
2. Use relevant keywords and hashtags in your diary entry. This can help make your conversation more discoverable to people searching for related topics on Hatena diary.
3. Include images or videos in your diary entry. This can make your conversation more visually appealing and can help attract more readers.
4. Share your diary entry on social media or other platforms. This can help increase the visibility of your conversation and attract more readers.
5. Encourage readers to share their thoughts and opinions on your conversation by including a call to action or a question at the end of your diary entry.
6. Finally, you can also try to participate in the conversation on Hatena diary, by answering the questions, responding to the comments, and engaging with your readers.
It's important to remember that getting many bookmarks on a diary is not easy and it can take time and effort to build an audience. But by following these tips and being consistent with your diary entry, you will increase the chances of attracting more readers and getting more bookmarks.
ぼく：
Any decision for Japan to build a nuclear-powered submarine is a huge step that would require the nation’s support politically and financially for years, Gilday said. That decision must be made with the understanding of “the totality of the ecosystem” for the initiative and that it will take decades to complete. Change “eco-system” for such a project requires “the right people, the right training, the right platforms, the right workforce” and sustainment, he said.
リンク先のギルディ氏というのは現在のアメリカ海軍参謀総長(米海軍のトップ)で、この人の発言はアメリカ海軍の総意と受け取ってもいい
そんな人が公のメディアで「長い時間を要する」と前置きしつつも「日本は原潜を建造保有するべきだ」と発言してるんだけど、これ割とすごい大ニュースなのでは？
'Seriously doubt' imminent invasion of Taiwan by China -Pentagon chief
So we’ve seen increased activity in – aerial activity in the straits. We’ve seen increased surface vessel activity around Taiwan.
And again, we believe that they endeavor to establish a new normal, but whether or not that means that an invasion is imminent, I seriously doubt that.
So we will continue to watch and we will continue to work with our allies and partners to do everything that we can to ensure that we promote peace and stability in the strait and in the region overall.
（台湾）海峡で航空活動の増加が見られます。台湾周辺でも水上艦の活動増加が見られます。
ただ、それが侵攻が差し迫っていることを意味するかどうかについてかなり疑問視しています。
- 全文：Secretary Antony J. Blinken, Secretary of Defense Lloyd J. Austin III, Japanese Foreign Minister Hayashi Yoshimasa, And Japanese Defense Minister Hamada Yasukazu At a Joint Press Availability
https://www.state.gov/secretary-antony-j-blinken-secretary-of-defense-lloyd-j-austin-iii-japanese-foreign-minister-hayashi-yoshimasa-and-japanese-defense-minister-hamada-yasukazu-at-a-joint-press-availability/
(1)
I want you to act as an English translator, spelling corrector and improver. I will speak to you in any language and you will detect the language, translate it and answer in the corrected and improved version of my text, in English. I want you to replace my simplified A0-level words and sentences with more beautiful and elegant, upper level English words and sentences. Keep the meaning same, but make them more scientific and academic. I want you to only reply the correction, the improvements and nothing else, do not write explanations. My sentences are “ここに文章を入れる”
(2)
Please be an English spelling corrector and improver. I ask you to make my sentences more scientific, elegant, and academic, with use of upper-level English words, keeping the meaning same. Please keep the structure of my sentences and correct grammatical errors. Please only reply the revised sentences. My sentences are “ここに文章を入れる”.
(1) の出典は
https://x.gd/GAWOv （本体が消えたので、キャッシュ）
(2) の出典は
3. 2の口調で1を語る
4. 無能がしゃしゃり出てくる
https://anond.hatelabo.jp/20221225173449 を書いた増田だが、これが実際にどう釣れるか書いておく。
進次郎構文を参考。自称賢い人はこういうのに性的に敏感に反応してしまう。内容自体は甘利氏の文献などを参考にしたもの。https://twitter.com/shunk031/status/1283991379517956096 のようなツイートもあるので根拠はある。
アルゴリズムってさ、
「○○っしょ」など馬鹿っぽさを感じさせる工夫を凝らしている。「プログラミングは学んだけど、ORなどを知らない」といった無教養なのに自称賢い層がターゲット。一応説明するとこれは線型計画法のこと。glpkを使ったことがあるなら一発で意味がわかる問題。
内容的にはほぼWill Kurtという人が言ってることと合致するようにしている。https://nostarch.com/learnbayes 「爬虫類人」といった見るからに陰謀論と思える用語を使っており、一見するととても知性が低いように見えるが、実際はBayes Factorの説明になっている。こいつしか釣れなかった → https://anond.hatelabo.jp/20221226024142
まだまだ釣りスキルが低いので反応が少ないが、必ず1匹ぐらいは釣れてるので、自称賢いけど実は分野について素人の気取った理系にムカついている人は試してみると良いかも (ワイは飽きたのでもうやらんけど)。
お前がどの計算に混乱してるのかわからんが、定理に単に代入すればそうなるだろ。
俺と同じこと言ってるのがあるからそれ引用するわ。(証明ではないが)
Once the prior probability is 0 or 1, applying Bayes Theorem will result in a new probability that is the same as the prior probability. In other words, the probability of the event has become “trapped” at either 0 or 1.
「いきなり防衛費2倍」に防衛省OBとか身内からも疑念が出ているが、ここではめんどくせえので防衛力増強するのがいいかどうかは触れないでおく。
しかし過大な予算を付けられた省庁が何をするかの経験は共有されているのに全然言及されていないのがとても気になる。
一見トートロジーだが、要するに余らせないために必要のないことやモノに金をぶっこむって事だ。或いは設備投資などを前倒しにする。
前者の代表はコロナ補助金で作ったイカの銅像が有名で、後者の代表は年度末の道路工事だ。
そうして予算を消化しておかないとその部署は来年度の予算が減らされる。
「イカの銅像」みたいなことが何で起きるかというと、前例が無いからだ。やる事が例年決まっているなら予算が余った時は追加発注すればいいし前倒しにすればいい。
でも前例が無い、若しくは前例で処理できるのを超えた過大な予算の場合は頓珍漢な発注をして金を使ってしまう事になる。代表例がクールジャパン（以下CJ）で、CJ自体は0年代初期から細々と続いてきた政策だが、第2次安倍政権で予算を肥大させた結果、外国のデパートに誰も買いに来ないCJ売り場が出来たり国内の広告代理店に金が流れるという結果になった。「海外への日本文化の宣伝」の方ではあまり成功していないわけだ。「英語の日本文化宣伝チャンネル」には日本語コメばかりが並んでいる。
いきなり防衛費2倍もトップダウンの政策なので下の防衛省の方では予算の「適正な」消化が難しいのではないかと思われる。
適正な消化が出来ない場合どうするかというと、頭を捻って考える、というよりは商社に相談した方が早い。多分今頃各商社が名刺持って営業始めてる頃だろう。
でもその中には役に立たん、怪しい商社や営業も入ってくる。そして後に大きい予算の運転が軌道に乗った時にはそいつらがいつまでも居座ったままで予算を圧迫させるようになる。これは法人取引の粘着性の為だ。
ドライなネット取引などが出来ても新規事業でもなければやや高額でも営業経由で取引するのが主流なままだし、この辺は購買担当や対外的な職務をした事がある人なら判るだろうと思う。営業経由にしないと「営業との相談」が出来ないので担当者には高いスキルや調査する時間が必要で、結果「たかが担当者」を交代できなくなるという経営上のジレンマが出来てしまう。だからネット通販専業のDELLだって法人担当の営業マンは置いている。
そういう訳で調達元と癒着が出来るといけないので役所関係の調達は競争入札式や公開プロポーザルなどにして透明化して役人は接待されるな、ゼロ円入札させるな、という事になっている。
ゼロ円/赤字入札が可能なのは取引の粘着性がとてもとても強くてその後に楽々回収出来るからである。
そんな感じで変な商社や虚業シンクタンクみたいなのと契約すると後々まで切れなくなってしまう、という懸念がある。
とすると大事件のフィクサーみたいだが、なんてことない、防衛省では「あ～、それについてはA社さんと相談してそっちで決めて」っていうのが当たり前に行われて居たのだ。
当時運送会社に勤務していてオフィスプランニングの会社の下請けの仕事が多くあった。
オフィスの組換えで土曜日に居残りした事ある人は判るかもしれないが、例えば床を工事する時に「配線工事の上流ってどこの会社だっけ」とかいちいち考えるのは大変だ。今次作業の発注先の下の会社だったら相手に任せておけばいいが別会社の場合は自分の方で連絡取っておかないと作業日にその部分が出来ずにやり残し、追加作業って形になる。
だから各社の関係者が居る時にその２人で相談して決めたのを参考にしたりって事はままある。
でもこれは前述のように役所がやってはダメなのだ。規模極小であっても官製談合になるからだ。
防衛省の場合はなんというか普通に「相談して決めて」が行われていて昭和の役所っぽかった。それで休憩時間に他の人らと「あれってほんとはダメなんだよね（苦笑）」とか話していたのである。
下働きの我らがなんでそんな判断できたかと言えば、他の省庁では「あ～、それについてはオタクらで決めて…ってうちが言えないから（笑）あとで連絡する」一同ワハハ、ってやり取りがよくあったからなのだ。
しかも六本木庁舎から市谷への大引っ越しがあったのでその前後で大量の追加発注やポンギから持ってきたけどやっぱ不要とか机配置の変更など（セキュリティ高いオフィスではフロア毎のスタッカブルハブを使うので席変更は線引き直しになって大仕事）があって「あれはどこの社だっけ」というのが大量に発生しており「A社さんと相談して」も多かった。
つまり他の省庁が晒されて来た厳しい談合の監視みたいなものがなくてなんていうかルーズ。
そういう感じなので変な営業への耐性とか大丈夫なんですかね？というのは思うところなんである。
最近だとWILLとかHanada誌の周辺で自称防衛シンクタンク、実態はyoutuberやヘイト本編プロみたいなのが防衛省や防衛産業をよいしょしまくるっていう、田舎の水商売みたいな事をやっていて、その結果中に立ち入ったり中で講演したりしているようだが、こういうのも見ると大丈夫か？と感じるところである。自分なんかは営業におだてられたりすると逆に不愉快になるのだけど。
しかもそういうのを「人間誰でも肯定的な人に靡くのは当然だろ」的に擁護されていたりする。いや権限与ってる人間がそれやったら普通は左遷や免職されるんですが。
因みに「外国のスパイ」っていうのは煽てと肯定、腰が低くて実態がある事業の振りしてくるもんですし、ソ連のスパイは右派のサンケイ新聞にいたんですが。
この手の変な自称シンクタンク以外にも「ネットでの評価評判を自在に操作できます」と営業かける逆SEO業者など怪しい業者が手ぐすね引いて待ってますが大丈夫なんでしょうかね？
君は「どこに行っても」を英語で「Go where you will, 」って言うのか。俳優か何かしてるのかな？
俺なら単に「In the Netherlands, you can find windmills everywhere. 」というけどね。
Never quite sure where you stand
Your mood a fickle thing, a constant clown
You rise with the sun, full of energy and light
But by the time the day is done, you're drained of all your might
You try to keep up, to fight the good fight
But the world is a harsh place, and it's a never-ending plight
Hoping and praying for a brighter way
But still you struggle, and still you strive
Weak man, you're a survivor, and that's no small feat to achieve
So hold your head up high, and don't give in
For even in your darkest hours, the light will always win
Weak man, you are strong, and you are brave
And though the journey may be tough, you'll find your way to the grave
So keep on pushing, and never lose sight
Such a feeling is coming over me
There is wonder in most every thing I see
Not a cloud in the sky
And I won't be surprised if it's a dream
Everything I want the world to be
Is now coming true especially for me
And the reason is clear it's because you are here
[All](You're) the nearest thing to heaven that I've seen
I'm on the top of the world
Looking down on creation and the only explanation I can find
Is the love that I've found ever since you've been around
[You ???](Your love's) put me at the top of the world.
Something in the wind has [learnt](learned) my name
And it's telling me that things are not the same
In the leaves on the trees and the [churchs](touch) of the breeze
There's a [pleasant](pleasing) sense of happiness for me
There is only one wish on my mind
When this day is through I ??? (hope that I will find)
That the tomorrow [would](will) be just the same for you and me
All I need will be mine if you are here
I'm on the top of the world looking down on creation and the only explanation I can find
Is the love that I've found ever since you've been around
[You ???](Your love's) put me at the top of the world
I'm on the top of the world looking down on creation and the only explanation I can find
Is the love that I've found ever since you've been around
[You ???](Your love's) put me at the top of the world
LCAで評価すれば、多数の下請け企業で冷間なり熱間なりで作った100個のパーツを1ヶ所に運送して溶接でガチャンコするより、メガキャスティングのほうがCO2排出量は低くなる。自動車産業というのは多段ティア間の部材配送のボリュームがすごく大きい。だからティア1のほぼ全てとティア2の多くが自社系列の配送子会社を抱えている。これがコストにも環境負荷にもなっている。
また、前にも書いたがアルミ合金のリサイクル率は非常に高い。ボルボは現時点でほぼ100%リサイクルしており（熱間鍛造部材は55%しかリサイクルできない）、その半分を二次合金として再利用している。これも製造サイクル全体で見た場合のCO2フットプリント低減に効いてくる。ボルボの場合は最低でも35%減を実現している。
Mega-casting also helps to increase the material utilization as well as the use of secondary (scrap) aluminum. According to Volvo, 100% aluminum will be utilized (versus 55% of stamped steel parts), and half of the aluminum can be secondary alloy, leading to at least 35% CO2 emissions reduction.
このレポートはメガキャスティングの将来性について不透明な点なども指摘してるフェアな内容だけど、少なくともCO2フットプリントに関してはメガキャスティングが鍛造より有利だと認めているように見える。
