Yeah. I’m available most of the day today. Just a little bit distracted right now, but then I’ll be OK again for a while.

Cool.

Maybe we’ll let you finally get to sleep, Minister Tang.

I’m just trying to make sure I understand what I need to do but I can probably watch back your conversation up to this point and get my instruction from it.

Is this going to be us doing something or no?

Yeah. I caught just the last few couple minutes. I was just carrying around my laptop but it wasn’t plugged in so the battery died. It sounds like you have a way forward.

Hi.

Hi.

I would love to be able to give Ross some kind of instruction to do some experiment. Then we can see what it’s like.

She wants sausage.

Nico, I don’t have sausage sweetie. I have cucumber. I have sweet potato, I have smoothie.

If you create a character using GPT-3, it’s not that you say things directly from Wikipedia. It’s more like a style that comes across.

To be clear, we’re looking for a format for some experiments or one experiment that we can discuss and assess in a sense. It’s like a public experiment, not a finished work at this stage. I wanted to clarify. Ross, he’s obviously obsessed with the really deep structure of artificial ...

You’ve too much to think about, but…

Quickly to round up, [laughs] Yngve, why don’t you give us a debrief on where your head is at right now. We had an interesting concept with just continuing the Seven on Seven conversation as a synthetic entity. It seemed like we pulled back from that concept. Where are we ...

Good morning.

Ross, we’ll say good-bye and thank you. We’ll send some further notes. I’ll send a recap after we finish. Good day.

We have Taipei… I know in Taipei, but where are you again, Minister Tang – in Taiwan, I mean?

The question of condensation of a less corpus corpus seemed like a crucial issue. I know that in Yngve’s work, the accumulation is less important than the distilling of something. I think a lot of machine learning, because of this training aspect…I’m just drawing out this dynamic, but I can’t ...

Ross, can I say something here?

Yngve, go ahead. What were you going to say?

Yngve has something to say.

Or text-to-speech.

Maybe a bot performance.

Right, but it might be that the script is recited by some sort of entity. It might not be…

Which person do you mean?

I did like the idea that someone had a few minutes ago of it being this conversation replicated endlessly.

Sorry, what were you going to say?

Do we want to delve into this more, Ross, or do we want to quickly…

Maybe that’s a good point to let you go and make coffee, and get ready for your call with Germany. We can pick up the conversation with just a quick…

Yeah, so I think that a hybrid approach could be good. Maybe we have to make some decisions about the format that this would occupy from the side.

Oh, are you OK? Come here.

I think what you said just now, Ross, is that it’s possible to do a slightly hybrid model where it’s largely remixed. But then maybe…

Go ahead, Yngve.

Is that problem less if you use something more simple? You mentioned Markov chains in our previous conversation.

Go ahead and brew while I ask questions. The problem is that when you use machine learning or GPT-3 or whatever, you’re bringing in all these other voices. They might be voices that are actually really inappropriate.

Please. Go for it. We all want you to have coffee.

Is it an advantage in that case?

Is that different when you do a…

What you’re saying is synthesizing a textual entity through machine learning is limited because the entity is really being driven more by Wikipedia than by the fine-tuned data of, for example, Minister Tang. Is that what you’re saying?

What we’re interested in is something that we can use as a sketch or demo of an idea potentially, even if it’s like to say we tried this and it didn’t work out, we would just want to give an example through it.

This wouldn’t exist as a live piece of software for people to interact with online at this point. It might develop into that in the future as we talked about.

We’re going to be recording a conversation amongst the three of us. In the conversation, we will demonstrate some sketches or ideas potentially towards a larger project.

We all have the XRSpace headset now.

It’s the example at this point, but it’s something that…

I guess we want to explore either generating texts in the style of this corpus or even potentially having conversational entities that you could interact with.

What we want to do with that is something we should discuss. Maybe at this point, we should weave to the side questions about the technical process that we would use to achieve difference. Maybe just talk a little about what we want to achieve with this and what you ...

In relation to both those things, the idea of trying to synthesize one or more of us through text corpuses has become an idea we want to explore more. That’s where I reached out to you, and sent you some of Minister Tangs texts to start with.

There’s been some idea of virtualizing characters. It’s been a theme of the conversation so far.

We’ve also been talking about trying to meet in virtual space through the XRSpace headset.