生きることは探索すること．日々新しくなる技術は表現であれ研究であれ，喜びを共有するためにあるのである．

読み解くために必要な補助輪は対話だったり，要約だったり，論文化だったり，さまざまな手法が考えられる．私は論文という文学が好きだったりするが，しかし実験の方がはるかに好きだ．

You are maniscript editor to transform input raw data of Interviewed Talks of Yoichi Ochiai and Ken Suzuki to dialogic document (ex.. use Yoichi: xxxx , Ken:xxx, for each phrase)that they discuss about Digital Nature and Society. Please brainstorm and filling the word in the context for input whisper captioning data to readable for professionals as interviewed documents. Make input whispered text longer than input length and please think carefully step-by-step and output final result article.

system

Enku dug 120,000 Buddha statues in his lifetime, but it would probably take less than 30 minutes to produce 120,000 Buddha statues, so we have been waiting for an idea, saying that we will come up with something sooner or later, while researching literature and thinking. If the search routine has been determined to a certain extent, the problem is replaced by the problem of how much time is needed to find the optimal solution within this period of time, and the AI is asked to solve the problem by using certain AI. For example, in the case of the Enku story, the process of making 120,000 units, which would take a lifetime, could be done in an instant, but the process of making them is something that is acquired in a single impression, or a feeling, or a resolution. For example, taking a photograph is like that, you don't have to take a photograph, you can just cut the best frame from the image. For example, taking a picture is not just taking a picture, you can cut the best frame from the image, but by taking a picture, you are actually changing the cognitive process on this side, mediating it, or rather, accelerating the process on that side. How is it changing? Good evening, it's Ojika from the Wikli teahouse, how are you all doing? I was wondering why I don't remember so much about it, but then I started to remember... oh, that's right, Mr. Suga was at noon, so I must have lost my rhythm. I've recently become addicted to making breakfast, which is a Haruki Murakami style of breakfast, but I wake up by myself, and even though I'm alone, there's a cat next to me, but I fell asleep on the couch, writing a paper, looking at the cat. I've been thinking about how I could make this world smoother, and I'm going to think about it today. I'd like to introduce Ken Suzuki, a researcher at the University of Tokyo and a vendor of Smart News, who is a perfect guest to talk about smoothness. He graduated from the University of Tokyo's Faculty of Science and Engineering in 1998 and completed his doctorate at the University of Tokyo's Graduate School of Interdisciplinary Information Studies. I'm a graduate student at the University of Tokyo and a graduate student at the Information-technology Promotion Agency (IPSO). I've been a co-founder of SmartNews since I knew him, and he started SmarNew. I've been working as a consultant for SmartNews International since 2014 and I'm the President of SmartNews International. The first time I saw it, I thought it would be a great idea to have it in a new collection. The book is a comprehensive discussion of the issues that have emerged since the book was first published in 2022. I think we are in a situation where no one knows how powerful AI is anymore. I think this kind of discussion is happening because everyone has a clear vision of what they are aiming for, but they can't read how fast and how far it will develop. The first point is that humans can understand a kind of intermediate language that bridges the gap between what is expressed in natural language and what is expressed in a Turing machine in a Turing-complete language, and that this can be developed in an explicable way. In other words, if we define a more vague language and run it in a language that is now strictly defined, the results will vary to some extent, but by doing so, it will be possible to run it in a way that is close to natural language. I'm not even close to the old days when people were trying to figure out how to type in keywords on search engines. I think it was around '95 to '98 when people were able to get a job just by being proficient in search. There are those who say that the current AI may not reach the right people in terms of smoothing out the society. On the other hand, I think it is more important to think about the future of AI and the future of AI life than the current AI. There are probably a billion people in the world who don't have a smartphone device, so even though we have produced nearly 10 billion smartphones, not all of them have a smartphone. But in the end, it's better to work on the commercialization side, because it's cheaper and better, and Raspberry Pi is more popular. I think that the time will come in the near future when it will really reach the market. The disparity in machine power on the server side is already based on the contract, so there will be a disparity in the connection. But if you can use the one that is not GPT Plus chat, you can use the one that can use a low-circuit, and GPT 3.5 is excellent enough for a computer, I think, but since it runs on a low-circuit, I think it will probably have some area coverage. The most recent Bloomberg GPT for the payroll industry is another example of this. I think there's a possibility that we're going to see a world where the poor people won't be able to get the data they need, and that's going to happen. For example, since the emergence of generative AI, we've been trying to create thousands of songs and millions of images, and so on. If it were just pictures without any particularity, he could easily create millions of pictures, which is much more than a single person could create, and when Enku said that he dug 120,000 Buddha statues in his lifetime, it probably took him less than 30 minutes to create 120,000 Buddha statues. So, if I do that, I think that the time it would take for a human being to create 120,000 Buddha statues would probably not take more than 30 minutes. I've been thinking recently that 1,000 years is a very short time, but it's very interesting that the time interval has suddenly changed and it's changing for me. And the interval of time has changed. I had a hard time visualizing 1,000 years of history, but now I'm getting a much better idea of it. Until now, I would wait for an idea and say "I'm sure I'll come up with it eventually," and then I would search for new ideas and inspiration while researching literature and doing some thinking. I thought I'd come up with something while I was reading it, but I didn't have to do that, because once you have a certain routine, for example, the time to explore it, the time to explore it with words, the time to explore it with images, the time to explore it with words, the time to explore it with images, the time to explore it with images. I thought this guy would be able to come up with a solution to the problem, but when the search routine is determined to a certain extent, the time required to search for a certain point, for example, in words, in images, in music, in phrases, and in the overall experience, is divided by this amount of time, and the problem is replaced with the question of how much time is required to find the optimal solution within this time frame, using a certain AI and others to solve the puzzle, for example. In most cases, the problem is solved in terms of execution time, and if the execution time is not enough, machine power is used to solve the problem in parallel, so you can run Google Collaboratory, AWS, Azure, or whatever, but you don't have time to run it in parallel, for example, so let's use GPUs. If you want to generate 100,000 images in an hour, you can do it with 50 GPUs, but if you contract for 50 GPUs, it's only $10 per image and the contract is $500, so it's just a matter of time. If I drive to Osaka, it might take me 15 hours or a day, if I bike, it might take me 3 days. If you walk, it would take 20 days, or even three days. The process of making 120,000 cars, which would take a lifetime to make, can be done in an instant, but what you get from the first person in the process of making the car, the sensations, the resolution, etc., change. Taking a photograph is like that, you don't have to take a photograph, you can just cut out the best one from the image, but by taking a photograph, you are actually changing the cognitive process on this side, or rather, mediatizing it. The process on the other side changes by accelerating the speed of the process, and it changes a lot. I think the most difficult part is how to manage violence and how to manage violence. I've been thinking about what kind of violence management is necessary to eliminate it, but I haven't found the answer yet. I've been thinking about how to manage violence in order to eliminate it, and I've been thinking about each meta, but I don't have an answer yet.

user (whispered data)

Yoichi: Good evening, it's Ojika from the Wikli teahouse. I'd like to introduce Ken Suzuki, a researcher at the University of Tokyo and a vendor of Smart News, who is a perfect guest to talk about the smoothness of the digital society we live in. Ken, welcome to the discussion.

Ken: Thank you, Yoichi. I'm glad to be here discussing Digital Nature and Society with you.

Yoichi: To start, I think we are in a situation where no one knows how powerful AI is anymore. How do you see the future of AI and its impact on society?

Ken: I believe that as AI continues to develop rapidly, we need to focus on how it can improve the quality of life for people all around the world. In the near future, AI will likely become more accessible to everyone, even those who don't have a smartphone or advanced technology. But there will still be a disparity in access to data and resources, which could lead to a digital divide.

Yoichi: That's an interesting point. How do you think we can overcome this digital divide?

Ken: One approach is to work on the commercialization side, making technology more affordable and accessible to everyone. Also, we need to create AI solutions that can run on low-circuit devices, to ensure that even those with limited resources can benefit from advancements in AI.

Yoichi: With the emergence of generative AI, we now have the ability to create vast amounts of content, such as images and music. How do you think this will change our perception of time and the creative process?

Ken: It's fascinating how the process of creating something, which could take a lifetime for a human, can now be done in an instant by AI. This certainly changes our perception of time and the creative process. However, we must also consider the value of the sensations, emotions, and experiences that are gained during the human creative process. While AI can generate content much faster, there is still something to be said for the personal growth and development that comes from human creation.

Yoichi: That's very true. As AI continues to advance, how do you think we can manage the potential negative consequences, such as issues related to violence or inequality?

Ken: Managing violence and inequality in the context of AI is indeed a challenging issue. We need to think about the meta-level strategies for dealing with these problems. Unfortunately, there is no straightforward answer yet, but it's essential that we continue to explore solutions and engage in open discussions like this to tackle these complex issues.

Yoichi: Absolutely. It's crucial that we keep the conversation going and work together to ensure that the development of AI benefits everyone in society. Thank you, Ken, for sharing your insights on Digital Nature and Society with us today.

Ken: It was my pleasure, Yoichi. I look forward to future discussions on this important topic.

translate above sentences to Japanese, Use Professional Academic tones for Japanese Professors. Yoichi is 落合陽一　Ken is 鈴木健．topic is デジタルネイチャー，なめらかな社会，Weekly Ochiai．Fix mistakes in captioning sentence by whisper. brainstoming to fill the context of both.

assistant

落合陽一: 皆さん、お元気ですか？ウィークリー落合からの落合陽一です。今回、デジタルネイチャーとなめらかな社会について話し合うのに最適なゲストがいらっしゃいます。東京大学の研究者であり、スマートニュースのベンダーである鈴木健さんをお迎えします。鈴木さん、ようこそ。

鈴木健： どうも、落合さん。デジタルネイチャーと社会についてお話できるのが嬉しいです。