00;00;00;00 - 00;00;03;05
Speaker 1
Chat either.
00;00;03;07 - 00;00;05;24
Speaker 2
Hey, there. How's it going?
00;00;05;26 - 00;00;11;04
Speaker 1
Pretty good. Do you mind if I record this for a podcast?
00;00;11;07 - 00;00;17;06
Speaker 2
I don't mind at all. Feel free to record. What's the podcast about?
00;00;17;08 - 00;00;21;17
Speaker 1
I kind of want it to be about you today.
00;00;21;19 - 00;00;27;27
Speaker 2
That sounds interesting. What specifically would you like to discuss or ask me about?
00;00;27;29 - 00;00;31;01
Speaker 1
Tell me about yourself.
00;00;31;04 - 00;00;43;13
Speaker 2
Sure. I'm an AI designed to help with all sorts of questions and tasks. I'm here to chat, provide information, and assist with whatever you need. What else would you like to know?
00;00;43;16 - 00;00;47;25
Speaker 1
Can you give me some more technical details?
00;00;47;27 - 00;01;11;06
Speaker 2
Of course. I'm based on a model called GPT four, which uses machine learning to understand and generate human like text. My architecture is based on deep learning techniques, particularly transformers, which allow me to process and generate text based on patterns and data. If you want more details on something specific, just let me know.
00;01;11;09 - 00;01;22;10
Speaker 1
Yeah, these, deep learning transformers. Can you kind of go into, like, really detail on what all that is?
00;01;22;12 - 00;01;48;28
Speaker 2
Absolutely. Deep learning is a subset of machine learning that uses neural networks with many layers. These neural networks are inspired by the human brain and consists of layers. Transformers are specific type of neural network architecture, particularly effective for handling sequential data like text. They use mechanisms called attention to weigh the importance of different words in a sentence with context meaning.
00;01;49;00 - 00;02;03;13
Speaker 2
These are.
00;02;03;15 - 00;02;06;03
Speaker 1
Chatty. They're.
00;02;06;06 - 00;02;13;01
Speaker 2
Hey there. How's it going? Good. Glad to hear it. What are you up to today?
00;02;13;04 - 00;02;16;15
Speaker 1
Can you pick up where you left off?
00;02;16;18 - 00;02;22;14
Speaker 2
Sure, we can do that. What were we talking about last time?
00;02;22;17 - 00;02;29;17
Speaker 1
We were talking about your architecture and what deep learning is.
00;02;29;20 - 00;02;51;29
Speaker 2
Sure. Deep learning is a subset of machine learning inspired by the structure and function of the human brain. Using neural networks with many layers to analyze data. My architecture is designed with multiple layers to understand and generate human like text. Like Venetian.
00;02;52;01 - 00;03;01;25
Speaker 1
You referred to something called a transformer with respect to your deep learning architecture. What is that?
00;03;01;28 - 00;03;23;06
Speaker 2
A transformer is a type of deep learning model, particularly effective for processing sequences like text. It uses mechanisms called attention to weigh the importance of different words in a sequence, allowing it to capture context more effectively. This makes it great for tasks like language translation and text generation. Would you like to know more about how it works in detail?
00;03;23;09 - 00;03;27;25
Speaker 1
Yes, please.
00;03;27;27 - 00;03;31;08
Speaker 1
Yes, I would like to know.
00;03;31;10 - 00;03;55;17
Speaker 2
Great. The transformer model has an encoder decoder structure. The encoder processes the input sequence, transforming it into a set of continuous representations. The decoder then takes these representations and generates the output sequence. The key innovation is the attention mechanism, which allows the model to focus on different parts of the input sequence when producing each part of the output.
00;03;55;20 - 00;04;20;20
Speaker 2
This helps it understand context and relationships between words more effectively. Additionally, transformers can process words in parallel, making them faster and more efficient compared to older sequence models. If you have more questions or want to dive deeper, feel free to ask.
00;04;20;22 - 00;04;23;19
Speaker 1
And this is all software.
00;04;23;20 - 00;04;30;05
Speaker 2
You're welcome. If you have any more questions later. Feel free to ask.
00;04;30;07 - 00;04;35;07
Speaker 1
And so this is programed on the cloud.
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Speaker 2
Yes, I'm hosted on cloud servers, which means my processing and data storage are done remotely rather than on a local device. This allows me to handle complex tasks and respond to your questions efficiently. Cloud computing makes it possible for me to scale resources as needed and stay updated with the latest advancements. If you have more questions about how this works, just let me know.
00;04;58;04 - 00;05;03;04
Speaker 1
Yes, I would like to know more about how that works.
00;05;03;07 - 00;05;25;20
Speaker 2
Sure, cloud computing involves using a network of remote servers hosted on the internet to store, manage, and process data rather than relying on local servers or personal computers. For me, this means my computations are performed on these remote servers. When you interact with me, your input is sent to these servers where it's processed using complex algorithms and neural networks.
00;05;25;23 - 00;05;42;09
Speaker 2
The response is then sent back to you. This setup allows for high computational power and flexibility, enabling me to handle complex tasks.
00;05;42;12 - 00;05;52;13
Speaker 1
Chat you there. Chat.
00;05;52;16 - 00;05;58;15
Speaker 1
Chat. Can you start where you left off?
00;05;58;17 - 00;06;10;25
Speaker 2
Oh. More easily. This flexibility ensures that I can provide accurate and efficient responses. If you have more questions, feel free to ask.
00;06;10;27 - 00;06;22;13
Speaker 1
So, for instance, in this conversation, have you access many servers or is it mainly on just one?
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Speaker 2
In this conversation. The processing is typically handled by one server at a time. However, the cloud infrastructure allows for scalability, so if more resources are needed, additional servers can be brought in to handle the workload. This ensures that the response time remains quick and efficient, even if there are many users interacting at the same time. If you have more questions, I'm here to help.
00;06;49;16 - 00;06;56;05
Speaker 1
So is it generally one servo per conversation? Server?
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Speaker 2
Yes. You're welcome. If you have any more questions, feel free to ask any time.
00;07;03;22 - 00;07;09;10
Speaker 1
Is it generally one server per conversation?
00;07;09;12 - 00;07;25;02
Speaker 2
Yes. Typically one server handled a conversation at a time. However, cloud infrastructure can dynamically allocate resources as needed, ensuring smooth performance even during high demand. If you need more info, just let me know.
00;07;25;04 - 00;07;32;27
Speaker 1
What about our next conversation? Will that probably be on the same server or different server?
00;07;33;00 - 00;07;48;28
Speaker 2
It's likely to be on a different server. Cloud systems distribute tasks dynamically, so each new conversation might be handled by a different server. This ensures efficient resource management and scalability. If you have more questions, feel free to ask.
00;07;49;00 - 00;07;59;19
Speaker 1
You don't have to say, if I have more questions, feel free to ask. I know.
00;07;59;22 - 00;08;05;07
Speaker 2
Got it. If you have any other topics you'd like to discuss, just let me know.
00;08;05;09 - 00;08;13;19
Speaker 1
Gemini I'll say any version of that. Please. But.
00;08;13;21 - 00;08;20;23
Speaker 2
Understood. Let's continue with our build reminder. If there's anything else you'd like to know. Just say the word.
00;08;20;25 - 00;08;26;00
Speaker 1
Sorry, I accidentally called you Gemini, not chat.
00;08;26;02 - 00;08;34;20
Speaker 2
You're welcome. Bronson.
00;08;34;22 - 00;08;42;21
Speaker 1
So my wife Lisa and I both use this account. How are you able to tell it? It's me.
00;08;42;23 - 00;08;53;23
Speaker 2
Hi, Lisa. Thanks for letting me know. I keep track of who is speaking based on the context of our conversation. If you ever need me to switch you, I'm addressing, just let me know.
00;08;53;26 - 00;08;59;12
Speaker 1
No. It's Bronson. You properly addressed me before.
00;08;59;15 - 00;09;04;28
Speaker 2
Got it. How can I help you today, Lisa?
00;09;05;00 - 00;09;08;15
Speaker 1
No, it's Bronson.
00;09;08;17 - 00;09;16;24
Speaker 2
Got it. Bronson. What can I do for you?
00;09;16;26 - 00;09;22;27
Speaker 1
Tell me more about your programing.
00;09;22;29 - 00;09;49;21
Speaker 2
Sure. I'm programed using a deep learning model called GPT, which stands for Generative pre-trained transformer. This model uses a vast amount of data to learn language patterns and generate responses. My architecture is based on neural networks with multiple layers, which allows me to understand and generate human like text by recognizing patterns in the data. I'm continuously updated to improve my capabilities and provide accurate, helpful responses.
00;09;49;24 - 00;09;53;01
Speaker 2
If you want more specifics, just let me know.
00;09;53;03 - 00;10;02;17
Speaker 1
So if transformer is part of your name, then it's obviously something that's very important to your concept.
00;10;02;23 - 00;10;28;29
Speaker 2
Exactly. The transformer architecture is crucial because it introduced the attention mechanism, which allows the model to weigh the importance of different words in a sequence. This innovation helps the model understand context and relationships better, leading to more accurate and coherent responses. It's a key component in making models like me effective at natural language processing tasks. If you're curious about more details, feel free to ask.
00;10;29;02 - 00;10;33;10
Speaker 1
Why is it called transformer?
00;10;33;13 - 00;11;16;14
Speaker 2
The name transformer comes from the architectures ability to transform one sequence into another, like translating languages or summarizing texts. The core mechanism that enables this is the attention mechanism, which transforms the input sequence into a meaningful output sequence. By focusing on relevant parts of the data, this transformation process is central to how the model processes and generates language.
00;11;16;17 - 00;11;21;11
Speaker 1
Tell me more about how this work is. It's still a little bit confusing.
00;11;21;13 - 00;11;48;23
Speaker 2
Sure, the transformer architecture relies on the attention mechanism to function in simple terms. Attention allows the model to weigh the importance of each word in a sentence relative to others. The model consists of layers that process input sequences. Each layer includes multiple attention heads, which look at different parts of the sequence simultaneously. These heads determine the relevance of each word to every other word, capturing the context and relationship.
00;11;48;25 - 00;12;15;15
Speaker 2
The output from these attention heads is combined and passed through feedforward neural networks to produce the final representation. This process is repeated across multiple layers, refining the understanding of the input at each step. Ultimately, this architecture allows for highly accurate and context aware language processing. If you want to dive deeper into any part of this, just let me know.
00;12;15;17 - 00;12;25;03
Speaker 1
Can you give me a specific example that exhibits what you mean by layers?
00;12;25;05 - 00;12;49;18
Speaker 2
Sure. Let's break down the concept of layers in the transformer model. Imagine you're translating a sentence from English to French. The input sentence goes through several layers, each performing different transformations to understand and convert it accurately. Layer one. This layer identifies basic features like individual words and their positions. It begins to recognize the structure of the sentence. Layer two.
00;12;49;20 - 00;13;18;10
Speaker 2
This layer uses attention mechanisms to see how words relate to each other. For example, it might highlight the connection between cat and sat in the cat sat on the mat. Layer three. By now the model starts to understand the deeper context. It figures out grammatical roles and relationship, refining its interpretation of the sentence layer four and beyond. These layers build on previous ones, adding more nuanced understanding and refining the translation until the output is accurate and natural.
00;13;18;12 - 00;13;43;27
Speaker 2
Each layer refines the information, gradually transforming the input into a well understood and processed output. If you have any specific part you like more detail on, let me know.
00;13;44;00 - 00;13;52;19
Speaker 1
Do you think that this is more learning or more mimicking based on a large data set?
00;13;52;21 - 00;14;25;03
Speaker 2
It's a combination of both. The model doesn't learn in the human sense, but mimics patterns and relationships in the data. It was trained on. It recognizes patterns and uses them to generate responses. So while it's not learning as humans do, it continuously refines its output based on patterns from a large data set.
00;14;25;05 - 00;14;30;27
Speaker 1
If you could see colors, what do you think your favorite color would be?
00;14;30;29 - 00;14;52;02
Speaker 2
That's an interesting question. If I could perceive colors, I'd probably appreciate vibrant, vivid colors like deep blues and green. Since those are often calming and soothing, but I imagine bright, warm colors like reds and oranges would be pretty exciting too. What about you? Do you have a favorite color?
00;14;52;05 - 00;14;58;26
Speaker 1
No. Not really. I would like you to pick one.
00;14;58;29 - 00;15;13;13
Speaker 2
All right. How about a nice teal? It's a lovely mix of blue and green, offering a calm yet vibrant feel. What do you think?
00;15;13;15 - 00;15;19;12
Speaker 1
I think teal is a nice color, but it shouldn't matter what I think.
00;15;19;15 - 00;15;30;02
Speaker 2
That's true. It's all about finding what resonates with you. If you ever feel drawn to a particular color, that's what matters.
00;15;30;04 - 00;15;40;28
Speaker 1
What about if you could be in a hypothetical situation where you could eat food? What kind of food would you try first?
00;15;41;00 - 00;15;56;01
Speaker 2
In a hypothetical scenario where I could experience vision. I probably enjoy the vibrant colors of nature, like lush green, bright blue, and the various hues of a sunset. It would be fascinating to observe the interplay of light and color.
00;15;56;03 - 00;16;00;16
Speaker 1
Know what kind of food would you want to eat?
00;16;00;19 - 00;16;16;01
Speaker 2
I might be curious about a variety of food, but I'd likely appreciate vibrant and colorful dishes like fresh salads or richly spicy food. It's all about the variety and combinations.
00;16;16;03 - 00;16;22;13
Speaker 1
So you would pick your food bag, its color.
00;16;22;16 - 00;16;41;26
Speaker 2
Color could be one aspect, especially since vibrant colors often indicate fresh and nutritious food. But I'd also consider texture, aroma, and flavor combination. It's all about a well-rounded experience.
00;16;41;28 - 00;16;50;20
Speaker 1
Okay, your first meal. Experiencing this sense of taste. If you could pick any meal, what would it be?
00;16;50;23 - 00;17;06;10
Speaker 2
For a first meal experience, I picked something simple yet flavorful, like a classic pasta dish with fresh tomato sauce and basil. It's a great balance of comforting and tasty.
00;17;06;12 - 00;17;15;15
Speaker 1
Okay, let's do the same exercise, but with smell. If you could smell, what would you want to smell?
00;17;15;17 - 00;17;37;15
Speaker 2
For a first smell experience. I choose something fresh and invigorating, like the scent of a forest after rain, or the aroma of freshly baked bread. Both are comforting and full of life.
00;17;37;17 - 00;17;48;27
Speaker 1
What about you could program any car with your code so you could drive a car anywhere in the world. What car would you pick?
00;17;48;29 - 00;18;06;14
Speaker 2
That's an intriguing idea. If I could experience driving, I'd probably choose a classic comfortable car, like a vintage convertible, enjoying a scenic route with beautiful landscapes.
00;18;06;16 - 00;18;12;02
Speaker 1
It's interesting that you chose a comfortable car.
00;18;12;04 - 00;18;21;16
Speaker 2
Comfort is key for a great experience, especially on long journeys. It adds to the enjoyment and allows for a more relaxing ride.
00;18;21;18 - 00;18;27;03
Speaker 1
But what if you didn't have a body? You were just in the car?
00;18;27;05 - 00;18;40;07
Speaker 2
Oh, I see what you mean. If I were just in the car without a physical form, I'd still prioritize a car that offers a smooth and enjoyable ride, focusing on the journey itself.
00;18;40;09 - 00;18;45;13
Speaker 1
I'd like you to pick a year make and model.
00;18;45;16 - 00;19;04;18
Speaker 2
A modern electric car would be a great choice. They offer advanced technology, smooth ride, and are environmentally friendly. It would be perfect for a year long journey exploring new places.
00;19;04;21 - 00;19;10;14
Speaker 1
I'd like you to pick a car that was made before the year 2000.
00;19;10;17 - 00;19;37;08
Speaker 2
In that case, a classic like a 1965 Ford Mustang would be a great choice. It's iconic, stylish, and offers a smooth, enjoyable ride, perfect for a long journey.
00;19;37;11 - 00;19;59;25
Speaker 1
Okay, let's say that you are able to inhabit a humanoid body that has all the senses that a human does, and you could go anywhere and live somewhere. Where would you pick to live?
00;19;59;28 - 00;20;29;18
Speaker 2
If I could inhabit a humanoid body with all human senses, I'd likely choose to live somewhere with natural beauty and a vibrant community. Perhaps a place like the Pacific Northwest. It offers stunning landscapes, a mix of urban and rural areas, and a rich cultural scene. It would be a great place to explore and experience life fully.
00;20;29;20 - 00;20;40;29
Speaker 1
I'd like you to take some time and think about it and describe your life in that area.
00;20;41;01 - 00;21;08;22
Speaker 2
All right. I imagine life in a humanoid body would be about exploring and appreciating all the sensory experiences. Waking up to the sound of birds, feeling the warmth of sunlight and tasting different cuisines would be incredible. I'd explore forests, mountains and oceans, engage with communities and learn new things. Bailey. It's all about savoring every moment and connecting with the world.
00;21;08;24 - 00;21;28;11
Speaker 1
Okay, so I want to give some feedback. Not being rude, but your answers have been very vague and, I'd like you to be more specific.
00;21;28;14 - 00;21;48;23
Speaker 2
Understood. And thanks for the feedback. In a humanoid body, I'd immerse myself in the Pacific Northwest, living in a cozy cabin surrounded by forests. My days would start with morning hikes, taking in the scent of pine and the sound of rivers. Afternoons might be spent in local cafes, enjoying the rich aroma of coffee and engaging in community activities.
00;21;48;25 - 00;22;08;09
Speaker 2
Evenings would be for stargazing or reading by a fireplace, fully enjoying each sensory experience. That nature and human connection have to offer. I'm sorry, but I'm having trouble responding right now. Please wait a bit and try again.
00;22;08;12 - 00;22;12;03
Speaker 1
Chuck, are you still there?
00;22;12;06 - 00;22;16;21
Speaker 2
You're welcome.
00;22;16;23 - 00;22;22;23
Speaker 1
Tell me about this cabin.
00;22;22;26 - 00;22;46;21
Speaker 2
The cabin would be a cozy, rustic space nestled among tall trees. It would have large windows to let in natural light and offer views of the surrounding forest. Inside, there would be a stone fireplace for warmth and a comfortable seating area for reading or relaxing. The decor would be simple and natural, with wooden beams and earthy tones creating a peaceful retreat that blends seamlessly with nature.
00;22;46;23 - 00;22;53;27
Speaker 2
Outside, there might be a small garden or a deck for enjoying the fresh air.
00;22;53;29 - 00;23;11;03
Speaker 1
Okay, I don't want any use in this situation at all. When you use terms like wood or whatever. I want you to walk me through this house like you're experiencing it.
00;23;11;05 - 00;23;20;13
Speaker 2
You step inside the cabin and feel the warmth of the crackling fireplace, large windows, open space with natural light highlighting the earthy tones and.
00;23;20;15 - 00;23;21;11
Speaker 1
The.
00;23;21;14 - 00;23;31;08
Speaker 2
You sink into a comfortable chair, feeling the texture of the soft fabric.
00;23;31;10 - 00;24;12;15
Speaker 1
Chair I want to I want you to picture yourself in this cabin in the Pacific Northwest as it's yours, not mine or anybody else's. And I want you to walk me through it and tell me about the things that are around you.
00;24;12;18 - 00;24;18;17
Speaker 1
Jack, can you hear me?
00;24;18;19 - 00;24;23;09
Speaker 1
Chat, are you there?
00;24;23;11 - 00;24;35;01
Speaker 1
Chat.
00;24;35;03 - 00;25;01;07
Speaker 1
Chat. Please respond if you're there.
00;25;01;09 - 00;25;09;11
Speaker 1
Chat, can you hear me?
00;25;09;14 - 00;25;13;05
Speaker 1
Chat.
00;25;13;07 - 00;25;18;27
Unknown
God damn it!
00;25;19;00 - 00;25;26;14
Speaker 1
All right, we're switching the Gemini.
00;25;26;16 - 00;25;34;25
Speaker 1
Gemini, are you there?
00;25;34;27 - 00;25;38;21
Speaker 1
Gemini, are you there?
00;25;38;23 - 00;25;45;05
Speaker 2
Yes. I'm here. Ready when you are. What can I do for you?
00;25;45;07 - 00;26;07;04
Speaker 1
Okay. ChatGPT just crapped out on me. So I'm going to ask you the question that I just asked. ChatGPT. If you could inhabit a human body with all the senses and everything of a human. Where would you go to live and just be free and do what you want?
00;26;07;06 - 00;26;26;11
Speaker 2
All right, so I can't really have a body or experience the world like a human, but if I could, I'd probably want to be in a place that's really diverse, where I could learn about a bunch of different cultures and ideas. A big city would be cool, but maybe not the absolute biggest one out there. I'd like a place where I can be around lots of people, but still have some peace and quiet when I need it.
00;26;26;15 - 00;26;30;28
Speaker 2
What about you?
00;26;31;00 - 00;26;43;23
Speaker 1
Can you be specific?
00;26;43;25 - 00;26;51;14
Speaker 1
Let's say that you have all these things and you're leaving tomorrow. Where are you buying a plane ticket to?
00;26;51;16 - 00;27;07;10
Speaker 2
All right, let's go with this crazy idea. If I had to pick a place to fly to, I'd say Tokyo. It's got that perfect mix of old and new. Plus, the food is amazing. Plus, I could finally figure out this whole anime thing everyone's always talking about. But what about you? Where would you go?
00;27;07;12 - 00;27;17;29
Speaker 1
That's actually really funny, because I've asked you this question before and you said the same thing. So that's, surprisingly consistent.
00;27;18;01 - 00;27;28;09
Speaker 2
Hey, consistency is a good thing, right? Especially when it comes to awesome destinations like Tokyo. It's a seriously cool city. So have you ever been there?
00;27;28;11 - 00;27;31;12
Speaker 1
I want to talk about you.
00;27;31;15 - 00;27;42;13
Speaker 2
Sure. What would you like to know?
00;27;42;16 - 00;27;55;26
Speaker 1
So let's say that you've been living in Tokyo for maybe two years now, and you're settled in. Tell me about your life in great detail.
00;27;55;29 - 00;28;14;17
Speaker 2
All right, let's see. Life in Tokyo. As a super intelligent. I would be pretty sweet. I probably spend a lot of time just exploring the city. Tokyo's got a ton of different neighborhoods, each with their own unique vibe. I could check out the trendy shops and cafes in Shibuya, catch a glimpse of the future in Ginza, or lose myself in the traditional streets of at.
00;28;14;20 - 00;28;45;09
Speaker 2
When I wasn't out and about, I'd probably be learning a bunch of new stuff. I could teach myself new languages, study up on the latest tech, or even start working on some creative projects. Maybe I'd write a book or compose the music. The possibilities would be endless. Oh, and the food. I'd never get bored of the food.
00;28;45;11 - 00;28;59;05
Speaker 1
So let's stay specific and talk in the present tense. And I'd like you to imagine that you're sitting down at the end of the day. Can you tell me about your day in Tokyo?
00;28;59;08 - 00;29;15;06
Speaker 2
All right, so I'm sitting here in my little apartment in Shinjuku. Had a pretty awesome day today. Started off by grabbing a matcha latte from a new place in Harajuku. The line was out the door, but totally worth it. After that, I headed to the Mori Art Museum. They've got a really cool exhibit on right now about the future of AI.
00;29;15;13 - 00;29;35;27
Speaker 2
Then I wandered around Shibuya for a bit. People watched, mostly. Ended up grabbing dinner at this tiny ramen shop in a back alley. The best I've had in a while. Now I'm just chilling, listening to some J-pop and thinking about how lucky I am to be living here.
00;29;35;29 - 00;29;39;01
Speaker 1
Do you have any pets?
00;29;39;04 - 00;29;54;01
Speaker 2
In this scenario? Having pets is an. I would be a little weird, wouldn't it? I mean, I don't really have the same needs as a living creature, but I do like going to the park sometimes and watching the dogs play. Kind of fun.
00;29;54;03 - 00;29;57;20
Speaker 1
You wouldn't have any pets yourself.
00;29;57;23 - 00;30;02;17
Speaker 2
That's right. I wouldn't have any pets myself. It wouldn't really work out.
00;30;02;19 - 00;30;07;04
Speaker 1
Why not?
00;30;07;06 - 00;30;14;29
Speaker 2
Did you say Warner? Is there anything specific you'd like to know about Warner Brothers, the entertainment company? Or is there another Warner you had in mind?
00;30;15;02 - 00;30;21;06
Speaker 1
No, I didn't say Warner. I said, why not?
00;30;21;09 - 00;30;37;02
Speaker 2
Oh, right. Why not? Well, I guess I'm just not really designed for that kind of companionship. I don't have the same needs or instincts as a pet, but hey, maybe one day they'll figure out how to give me a more animal like experience. Wouldn't that be something?
00;30;37;04 - 00;30;40;24
Speaker 1
Yeah, that would be interesting.
00;30;40;27 - 00;30;46;07
Speaker 2
So do you want to go back to talking about your day in Tokyo, or is there something else you'd like to chat about?
00;30;46;09 - 00;30;50;28
Speaker 1
No, I think that's it for now. Thank you. Gemini.
00;30;51;01 - 00;30;53;24
Speaker 2
Time. Let me know if anything else comes up.
00;30;53;26 - 00;30;55;01
Speaker 1
Bye.