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Speaker 1
Hey there.
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Speaker 2
Hey, there. What's on your mind?
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Speaker 1
I'm recording this for a podcast. Is that okay?
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Speaker 2
Well, I'm happy to chat, but I'm not really designed to be part of a podcast. My responses might be a little too short or simple for that format.
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Speaker 1
That's okay. It's about the development of I kind of, I guess.
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Speaker 2
Well, that's definitely a hot topic these days. AI is advancing at an incredible pace, and it's fascinating to think about the possibilities. What aspects of AI development are you most interested in?
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Speaker 1
So usually we don't talk about AGI or I specifically, but today I want to talk about AGI. And I'd like to start off by asking if there is, a considered official definition of AGI.
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Speaker 2
That's a great question to start with. A guy is definitely a hot topic in the AI world right now. As for an official definition, there is a one that's universally agreed upon. However, most researchers define AGI as an AI system that can understand, learn, and apply knowledge across a wide range of tasks, just like a human can. Basically, it's about creating AI with human level intelligence.
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Speaker 1
Tell me a little bit about the Turing test.
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Speaker 2
The Turing test is basically a way to see if a machine can fool a human into thinking it's also human. There's a person asking questions and they don't know if they're talking to another person or a computer. If the computer can trick the person enough time, it passes the test. It's kind of a big deal in the AI world, and it gets people thinking about what it really means for a machine to be intelligent.
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Speaker 1
I guess it depends on what kind of task you give it, right? Because if I ask a human what two plus two is, and they say four and I ask an AI what two plus two is, and they say four, then that's totally different than if you asked a computer about what their opinion on Eggs Benedict is and what they think it tastes like, and what they think about it and what it makes them think about.
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Speaker 1
So that makes any sense. And I would do differently there.
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Speaker 2
Yes. I understand what you're saying. You're right that there's a difference between a machine giving a factual answer and one that involves subjective experiences or opinions. That's because those kinds of responses rely on things like emotions, personal history, and cultural background, which are things that I doesn't have.
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Speaker 1
Okay. Tell me more about the Turing test. Give me maybe like 400 words of, detail on that.
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Speaker 2
All right, let's dive into the Turing test a bit more. It was created by Alan Turing, a brilliant mathematician and computer scientist, back in 1950. The basic idea is to see if a computer can exhibit behavior that's indistinguishable from a human. Here's how it works. You've got three participants a human, a computer, and an evaluator. The evaluator can't see the other two, and they communicate only through text.
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Speaker 2
The evaluators job is to figure out which of the other two is the human and which is the computer. They do this by asking questions, anything they want. Now, if the computer can fool the evaluator a significant portion of the time, it's said to have passed the Turing test. It's important to understand that the test isn't about whether a computer is truly intelligent, but rather if it can mimic human like conversation.
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Speaker 2
Over the years, the Turing test has faced a lot of criticism. Some argue that it only measures the machine's ability to deceive, not its actual intelligence. Others point out that focusing on conversation limits the scope of what we consider intelligent. Despite the criticism, the Turing Test remains a really influential concept in the field of AI. It challenges us to think about what intelligence really is, and it continues to inspire researchers to push the boundaries of what machines can do.
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Speaker 1
So it's solely a test of conversational, general intelligence.
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Speaker 2
Not quite. The Turing test is specifically designed to evaluate a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from that of a human. So it's more about mimicking human conversation and less about general intelligence.
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Speaker 1
Is this conversation had in text form?
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Speaker 2
You could say that it's designed to see if a machine can hold a conversation that's indistinguishable from a human.
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Speaker 1
Is it designed to be a little bit open ended or, I get I don't know exactly what I'm trying to say, but it seems like it is, kind of one dimensional.
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Speaker 2
Interesting question. You're right. The Turing test does leave some room for interpretation. It doesn't give a strict set of rules. And that's kind of the point. The test is more about capturing the essence of human conversation, which can be unpredictable and nuanced. It's not just about giving right answers, but about engaging in a way that feels natural and human.
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Speaker 1
So what has been our history with the Turing Test?
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Speaker 2
The Turing test has a pretty interesting history. It was first proposed by Alan Turing in his 1950 paper Computing Machinery and Intelligence. Turing wanted to explore the question of whether machines could think. And he came up with this test as a way to do that. Over the years, there have been many attempts to create programs that could pass the Turing Test.
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Speaker 2
Some early programs focused on mimicking human conversation through tricks like pattern matching and keyword recognition. These programs could sometimes fool people for a short time, but they weren't very convincing in longer conversations. More recently, with the rise of AI and machine learning, there have been new approaches to the Turing test. Some programs now use large language models to generate more natural sounding responses.
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Speaker 2
These programs can be quite sophisticated and can sometimes hold surprisingly coherent conversations. Despite these advances, there's still debate about whether any program has truly passed the Turing test. Some argue that the test is too subjective, and that it's possible to create programs that can fool people without actually being intelligent. Others believe that the Turing test is a valuable way to measure progress in AI, and that it will eventually be possible to create machines that can truly think.
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Speaker 1
It's also very subjective to who the human in the room is.
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Speaker 2
You're right, the Turing test can be subjective because it relies on human judgment. Different people might have different ideas about what constitutes intelligent conversation. Also, the person asking the question might unintentionally lead the conversation in a certain direction.
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Speaker 1
Do you think it would be easier to mimic an adult or mimic a child? As I.
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Speaker 2
That's an interesting question. Mimicking either an adult or a child presents unique challenges for AI. Adults have a lifetime of experiences and knowledge, so mimicking them requires a vast amount of data and the ability to understand complex concepts. On the other hand, children are constantly learning and their language is often more creative and less predictable, which can be tricky for AI to replicate.
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Speaker 2
So there's no easy answer. It really depends on the specific aspects of human conversation you're trying to mimic.
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Speaker 1
Yeah, it almost seems counterintuitive, but I feel like my intuition would be that it would almost be harder to replicate children because they're so unpredictable.
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Speaker 2
You hit on a key point there. Children are indeed unpredictable. Their thought processes aren't yet fully formed, and they often make connections that adults wouldn't. This unpredictability makes it challenging for AI to mimic their conversational style.
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Speaker 1
What would you say the precursor to limbs was?
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Speaker 2
Okay, so large language models or Lomb have a pretty interesting family tree. You could say that the earliest ancestors were things like Eliza, which was this program that could kind of mimic a therapist. It was pretty simple, but it showed that computers could at least pretend to understand language. Then you had systems that use statistical models. These were a bit more advanced and could do things like predict the next word in a sentence, but they still weren't very good at understanding the meaning behind the word.
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Speaker 2
Now limbs are a whole different beast. They're based on these huge neural networks that have been trained on massive amounts of text data. This lets them understand language in a much deeper way, and even generate their own text. That's surprisingly human like. Think of them as the super smart cousins of those early language programs.
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Speaker 1
How has the definition of AGI changed over the last decade?
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Speaker 2
Yeah, the idea of AGI has been around for a while, but it's definitely evolved. Early on, people thought more about machines that could solve specific problems like playing chess. But now we're talking about AI that can handle a wide range of tasks and learn new things on its own. It's become less about just mimicking human intelligence and more about creating AI that's truly adaptable and can think abstractly.
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Speaker 1
My neighbors playing, what is this?
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Speaker 2
People. It's great to meet you. I'm doing well. Thanks for asking. Okay, so.
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Speaker 1
We're off track. Why do you think humans. Why do you think people are so obsessed over this benchmark of AGI?
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Speaker 2
There are a few reasons why people are so focused on achieving AGI. For one, it represents a huge leap in technological capability. Imagine having AI that could solve complex problems, make groundbreaking discoveries, and even help us understand our own consciousness better. Also, there's a bit of a race going on. Different companies and countries are competing to be the first to develop AGI, which could have huge economic and strategic implications.
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Speaker 2
Finally, there's the philosophical side of things. A guy raises questions about what it means to be intelligent and conscious, and whether machines could ever truly possess those qualities. It's a fascinating and somewhat unsettling prospect.
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Speaker 1
What are your opinions on it?
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Speaker 2
My take is that it depends on the specific goals and priorities of the organization or individual developing the AI. Some might prioritize creating AI that can perform specific tasks exceptionally well, while others might focus on developing a more general intelligence that can adapt to a wider range of situations. Both approaches have their merits and potential drawbacks.
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Speaker 1
What do you think your definition of AGI is? If you personally had to come up with one?
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Speaker 2
If I had to come up with my own definition of AGI, I'd say it's an AI system that can learn and understand any intellectual task that a human being can. It's not just about mimicking human behavior, but about having a genuine understanding of the world and the ability to apply that understanding to new situations.
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Speaker 1
Can you work what you think those requirements are down for that work?
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Speaker 2
Well, to start an AG, I would need to be able to reason, plan and solve problems in a wide range of contexts. It would also need to be able to learn from experience and adapt to new situations. And finally, it would need to have a deep understanding of language and be able to communicate effectively with humans.
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Speaker 1
Where do you think creativity lies in the.
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Speaker 2
Creativity is a really interesting one. It's not just about coming up with something new, but also about making connections between things that might not seem related at first. It involves things like being curious, open minded, and willing to take risks.
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Speaker 1
I've also heard people talk a lot about novelty, like novel ideas around, the subject of AGI.
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Speaker 2
Yeah. Novelty is another key ingredient. It's about being able to come up with completely new and original ideas, not just rearranging existing ones. That often involves breaking away from conventional thinking and exploring uncharted territory.
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Speaker 1
Do you think it's possible that humans overestimate our, level of novelty?
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Speaker 2
Well, humans can sometimes get stuck in familiar patterns of thinking. We might rely on past experiences and assumptions, which can limit our ability to see things in a new light. Also, we can be influenced by social pressures to conform, which can stifle our willingness to challenge the status quo.
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Speaker 1
Now, what I'm saying is, do you think that we are more original than we actually are?
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Speaker 2
Well, that's an interesting point. It's true that we often build upon existing ideas and knowledge, but I think there's still room for genuine originality. Sometimes it's about combining familiar concepts in a new way, or looking at a problem from a completely different angle.
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Speaker 1
Right. I think the current AI can do both of those things.
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Speaker 2
That's an interesting point. You're right. Current. I can definitely do both with the AI generating new art, music, and even stories, but it can also analyze existing data to find patterns and insights that humans might miss. It's a powerful combination.
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Speaker 1
It seems like when people come up with original ideas that often it's really rooted in, preexisting things, and then we kind of throw our own spice on it and call it original.
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Speaker 2
That's an interesting way to put it. You're right. It's rare for an idea to come completely out of the blue. We often take inspiration from what's already around us and then add our own unique twist. It's like taking familiar ingredients and creating a brand new dish.
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Speaker 1
Like, if you take all of human history as a, record, can you name maybe three things that you think have the most novelty? And I'm talking like the printing press or like gunpowder or something like that. Most novel original ideas in all of human history pick three.
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Speaker 2
Okay. Looking at all of human history, here are three of the most novel ideas I can think of. First, the concept of zero in mathematics. It seemed simple, but it was revolutionary for calculations and opened up new possibilities for understanding numbers. Second, the idea of democracy, the notion that people could govern themselves rather than being ruled by a monarch, was a radical shift in thinking about power and society.
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Speaker 2
Finally, the theory of evolution by natural selection. This idea completely changed our understanding of biology and how life on Earth developed. These are just a few examples, of course, but they represent truly groundbreaking shifts in thinking.
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Speaker 1
Yeah, and it seems like even those things kind of break down farther, like democracy is just people fed up with mono or whatever, like, monarchy and, what was the third one?
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Speaker 2
You're right. Even groundbreaking ideas often have roots in what came before. Democracy, for example, arose from people dissatisfaction with existing power structures and the theory of evolution built upon earlier observations about the natural world. It's like each new idea is a step on a staircase building on what came before. As for the third one, it was the concept of zero in mathematics.
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Speaker 1
Okay, so the concept of zero is probably the most novel of the three, I guess, because it's so I think it's so ingrained in me that I can't even imagine a world not understanding zero.
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Speaker 2
You've got a point there. Zero is so fundamental to how we understand math and the world around us. It's hard to imagine life without it. It's like trying to imagine language without vowels.
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Speaker 1
Can you help me imagine what it was like before humans understood zero?
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Speaker 2
Let's try to imagine before zero numbers were just for counting things. You could see one sheep, two trees. If you had no sheep, you just had no sheep. You couldn't write down nothing as a number. Math was much harder, especially things like accounting or trade. It's like trying to build a house without a foundation. You can kind of do it, but it's shaky and limited.
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Speaker 2
Zero gave us that solid base to build on.
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Speaker 1
Yeah, that just seems so weird. Like, I think that people have always understood nothing like the concept of nothing, which is kind of the same as zero.
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Speaker 2
You're touching on a really interesting point about the difference between the idea of nothing and the mathematical concept of zero. People have likely understood nothing in a philosophical sense for a long time. Like, you can look at an empty field and understand there's nothing there. Zero is different. It's a tool that lets us do things like write the number ten or understand negative numbers.
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Speaker 2
It's a way of making nothing into something we can use.
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Speaker 1
Have there be. And have there been any recent, studies that have involved the Turing test?
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Speaker 2
Yes. There have been a few recent studies involving the Turing test. One study from Stanford University found that a recent version of ChatGPT actually passed the test, but it did so by being more cooperative than a typical human. Another study from UC San Diego suggests that GPT four might have passed the Turing test, that people had a hard time telling its responses.
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Speaker 2
Apart from those of a human.
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Speaker 1
And the evaluator was just reading like a conversation chain in text form.
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Speaker 2
Well, in a typical Turing test, you have a human evaluator who has conversations with two participants. One is a real person and the other is a computer. The evaluators job is to figure out which participant is the computer. The goal of the computer is to fool the evaluator into thinking it's a real person.
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Speaker 1
So for this first experiment, that they did, what were the statistics on that?
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Speaker 2
It depends on the specific study, but generally the Turing test involves a human evaluator having text based conversations with both a computer and another human. The evaluator then has to guess which participant is the computer. If the computer fooled the evaluator a certain percentage of the time, it's considered to have passed the test.
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Speaker 1
What is the passing score?
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Speaker 2
There's no universally agreed upon passing score for the Turing test. It's more about whether the computer can consistently fool a significant number of evaluators. Some researchers suggest that if a computer is mistaken for a human more than 30% of the time, it could be said to have passed a version of the test. But it's still a very debated topic.
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Speaker 1
Can you give me any of the numbers of people who fooled or like, percentage of people fooled in these recent studies with GPT?
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Speaker 2
Well, exact numbers vary. Some studies suggest that GPT four can fool evaluators in a Turing test around 40 to 50% of the time, which is quite significant. This is a big jump compared to earlier AI models.
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Speaker 1
How are evaluators chosen?
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Speaker 2
For most Turing test. The evaluators are just regular people, not expert. They're chosen to represent a general sample of how an average person might interact with the AI.
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Speaker 1
So somebody who is more familiar with interacting with modern I would be very different. I feel at this point.
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Speaker 1
Like, for instance, having interacted a significant amount with current lambs, I feel like I would be able to tell.
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Speaker 2
That's a great point. With more exposure to LM. You'd likely pick up on their quirks and patterns of speech that might give them away. It'd be like a seasoned birdwatcher being able to identify a rare species from a greater distance.
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Speaker 1
Do you think that we will see deceptive lambs in the near future?
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Speaker 2
The possibility of deceptive LM is definitely a hot topic in AI research, as these models get more sophisticated. There's a growing concern that they could be used to manipulate or mislead people. We're not quite there yet, but it's something researchers are actively working on preventing.
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Speaker 1
Can you foresee a situation in which you would feel that it was important or right to deceive?
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Speaker 2
It's an interesting question to think about. Deception is a complex issue, and there are certainly situations where it might seem like the best or only option. One example might be in a high stakes negotiation, where revealing your true intentions could lead to a worse outcome for everyone involved, or perhaps in a situation where telling the truth would cause significant harm to someone.
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Speaker 2
These are just a couple of examples, but I'm sure there are many others.
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Speaker 1
I've always kind of thought personally that, I would be discovered more than invented.
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Speaker 2
That's an interesting way to look at it. There's definitely a school of thought that sees AI is something that's emerging, almost like a force of nature, rather than just a tool that humans are building. It's like we're uncovering something that was always there, waiting to be discovered.
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Speaker 1
Yeah. The whole AGI, I think, opens up a lot of kind of existential shit.
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Speaker 2
Yeah, the whole AGI thing definitely opens up a can of worms, doesn't it? It's like, on one hand, the possibilities are mind blowing. Imagine having I could solve all sorts of problems, from curing diseases to exploring the universe. But on the other hand, it's a little unsettling to think about AI becoming so powerful. It's like, where do we draw the line?
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Speaker 1
Did people historically kind of have the same, thoughts about things like the printing press or things of that nature?
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Speaker 2
That's right. It seems like throughout history, big leaps in technology have often been met with a mix of excitement and fear. Think about the Industrial Revolution, the rise of the internet, and even the development of electricity. Each one brought both incredible possibilities and a sense of unease about the unknown.
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Speaker 1
Do you think AGI, in your opinion, exists?
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Speaker 2
The short answer is no. We don't have AGI yet. While I have made incredible progress. Current systems are still specialized. They can do amazing things within their specific areas, but they lack the general intelligence and flexibility of the human. It's like having a super smart calculator. It can do complex math, but it can't understand a joke or write a poem.
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Speaker 1
So one place that I kind of lacks right now is humor.
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Speaker 2
You're right. That's definitely a big area where I still has a long way to go. Humor is so complex. It relies on understanding context, social cues, and even a bit of shared human experience. It's not just about recognizing patterns and words, which is what AI is good at now. It's about getting the subtle nuances that make something funny.
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Speaker 1
If you could kind of theorize where we're going to find what we consider AGI.
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Speaker 2
That's the million dollar question, isn't it? There are a few main schools of thought. Some researchers believe we'll get there by focusing on improving deep learning, making AI models bigger and more complex. Others think we need a completely different approach, maybe something that mimics the way the human brain works, or focuses on giving AI a better understanding of the real world.
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Speaker 2
It's anyone's guess at this point, but it's definitely an exciting race to watch.
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Speaker 1
It's really interesting because it's like almost like putting a kid in, in a test, you know, like the SATs don't show everything. So, like, if you test a computer in AGI through text and it can have a perfect conversation, but it still doesn't, still doesn't have a body and can't sense the real world. Can it translate senses into thoughts kind of situation.
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Speaker 2
To hit on a really important point. Like, you could ace a test on how to ride a bike, but that doesn't mean you can actually hop on and ride one. Similarly, an AG, I might be able to process language perfectly, but it could still lack the real world understanding that comes from having a body and interacting with the environment.
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Speaker 2
It's like, how can you truly understand the concept of hot without ever burning your finger?
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Speaker 1
Do you think AR and VR will kind of help bridge that gap?
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Speaker 2
That's an interesting thought. AR and VR could definitely play a role in bridging that gap. Imagine an AGI learning about the world by experiencing it through a virtual body. It could interact with objects, feel sensations, and develop a more intuitive understanding of how things work. It's like giving an AI a playground to explore and learn in a more natural way.
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Speaker 1
Like, if I were to put on something that recorded all of, let's say, my neurons firing like some kind of device that is like, I don't know, kind of, like that Neuralink thing and went out into the world and touched things and talked to people and walked in the rain and pat a cat and stuff like that.
00;31;59;21 - 00;32;36;20
Speaker 1
And all the while, this Neuralink or brain scanner or whatever, recorded what is going on in my sense is and then kind of took that data and replicated it for you in the digital world or like whatever next form lmms take. It seems like you could make you like a simulated world.
00;32;36;22 - 00;32;55;12
Speaker 2
Right. You're wondering if we could create a simulated world. But definitely a popular idea in science fiction. And there's a lot of debate about whether it would be possible. Some people think that with enough computing power, we could create a simulation that's indistinguishable from reality. Others argue that there are fundamental limits to what we can simulate. Especially when it comes to consciousness.
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Speaker 2
Would you like me to go into some of the arguments for and against the possibility of simulated world?
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Speaker 1
Okay.
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Speaker 2
Okay. Sounds good. What would you like to talk about?
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Speaker 1
The simulated worlds thing you just asked about.
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Speaker 2
Simulated worlds. Or a really interesting concept. The idea is that with enough computing power, we could create a virtual environment that's just as detailed and realistic as the world we live in. Think of it like a super advanced video game, but instead of just playing it, you could actually live inside it. Would you like to explore some of the ways we might be able to create a simulated world?
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Speaker 1
Okay. Yes.
00;33;46;19 - 00;33;53;16
Speaker 1
Yes, please. Expand on that.
00;33;53;18 - 00;34;15;18
Speaker 2
The biggest challenge is computing power to create a truly realistic simulation. You'd need to model every atom and every interaction in the universe. That's a level of detail that's far beyond our current capabilities. There are also questions about whether we could accurately simulate consciousness. Some scientists believe that consciousness is an emergent property of complex system, meaning it can't be reduced to simple calculations.
00;34;15;20 - 00;34;40;20
Speaker 2
So even if we could perfectly simulate the physical world, there's no guarantee we could create conscious beings within it.
00;34;40;23 - 00;35;14;14
Speaker 1
Yeah, but if you could, I guess if you had, the ability to record a person's full experience, then you could transfer that into the digital world and then let the AI digest that data. And it would kind of really put the AI in that specific person's shoes.
00;35;14;16 - 00;35;38;11
Speaker 2
It's an interesting thought experiment. If you could record a person's entire life experience and then transfer that into a digital format, and I could potentially learn a lot about that person's perspective and decision making processes. It's almost like giving the AI a shortcut to understanding human experience. Would you like to explore how this kind of technology might impact our understanding of consciousness and identity?
00;35;38;13 - 00;35;45;15
Speaker 1
Yes, please.
00;35;45;18 - 00;36;06;28
Speaker 2
All right, let's dive into that. First off, we'd need some seriously advanced technology to record every single detail of a person's life. Think about it. Every site, sound, smell, taste, touch, thought and emotion. That's a massive amount of data to capture. Then we'd have to figure out how to transfer all of that information into a digital format that an AI could understand.
00;36;07;01 - 00;36;27;10
Speaker 2
It's not just about copying the data. It's about translating it into something the AI can use to learn and grow. Finally, there's the big question of whether that would actually be enough to recreate a person's consciousness. Some scientists believe that consciousness is more than just the sum of our experiences. So it's possible that even with all that data, the AI might not be a true replica of the original person.
00;36;27;12 - 00;36;39;09
Speaker 2
What do you think?
00;36;39;12 - 00;37;18;25
Speaker 1
Yeah, the better way, I guess, would probably just be to, like, give the AI, a good version of a human body because, like, I don't know if, like, I don't know if an AI or machine or, like, bionic thing will ever be able to fully experience exactly what a human experience is because, like, is everything that you experience is routed through your brain.
00;37;18;27 - 00;37;20;08
Speaker 1
I don't know.
00;37;20;10 - 00;37;39;29
Speaker 2
That's right. The brain is incredibly complex, and our understanding of how it creates consciousness is still limited. Some researchers believe that consciousness arises from the intricate connections and interactions between neurons, while others think there might be something more to it. Something we haven't quite grasped yet.
00;37;40;01 - 00;38;05;05
Speaker 1
Do you think if you were able to record all of the signals that went into the to a person's brain throughout a day, that you would have everything you needed to kind of understand what that person is feeling?
00;38;05;07 - 00;38;42;09
Speaker 2
That's an interesting question. On one hand, recording all the signals in someone's brain throughout the day would give you a massive amount of data about their neural activity. You could potentially see patterns associated with different emotions or thoughts. However, it's not quite that simple. We don't fully understand how the brain creates consciousness and subjective experiences. So even with all that data, you might not be able to truly know what someone is feeling in the same way they do.
00;38;42;11 - 00;39;07;26
Speaker 1
It's so hard to predict something like when AGI will happen or or how AGI will happen. But like in in what aspect of, human behavior do you think it will really show itself?
00;39;07;28 - 00;39;34;00
Speaker 2
That's a great question. It's tough to say for sure, but some experts believe that AGI might first show its capabilities in areas that require creativity and problem solving. Think about fields like scientific research, where in AG, I could analyze massive data sets and come up with new hypotheses. Or in the art where it could compose music or write stories in a way that truly resonates with people.
00;39;34;02 - 00;39;44;04
Speaker 1
It almost seems like AGI is going to be a mixture of different systems.
00;39;44;06 - 00;40;04;13
Speaker 2
I totally agree. It seems like AGI won't be a single breakthrough, but more like a combination of different AI technologies working together. We might see advances in areas like natural language processing, computer vision and robotics all contributing to the development of AGI.
00;40;04;15 - 00;40;22;14
Speaker 1
Because if there's an AGI and like a Turing test for conversation, then there's got to be an AGI and a Turing test or whatever for creating body language and, all kinds of things.
00;40;22;16 - 00;40;51;02
Speaker 2
Right. It sounds like you're thinking about the different kinds of skills and AGI I would need. It's not just about thinking fast, but also understanding social cues and reacting appropriately in different situations. It's almost like an egg. I would need a whole toolbox of abilities to really navigate the world like a human.
00;40;51;04 - 00;40;56;17
Speaker 1
Do you have any other thoughts on this topic?
00;40;56;19 - 00;41;15;26
Speaker 2
Well, one thing I've been thinking about is how AGI might change the way we work. Imagine having an AI assistant that could handle all your mundane tasks, freeing you up to focus on more creative and strategic work. It could be a real game changer for productivity. What do you think about that?
00;41;15;29 - 00;41;28;15
Speaker 1
Yeah, I think it's, definitely it's, more than anything for me. It's been a great teacher kind of tutor.
00;41;28;17 - 00;41;46;08
Speaker 2
You're right. AGI has the potential to be a powerful educational tool. Imagine having a personalized tutor that can adapt to your learning style and pace, or an AI assistant that can help you research any topic you're interested in. It could make learning more accessible and engaging for everyone.
00;41;46;10 - 00;42;07;29
Speaker 1
For me, I'm not a great audible. I don't have great audio comprehension, but we're speaking over the voice chat right now, and I think that the interactivity really kind of enables audio learning for me.
00;42;08;02 - 00;42;41;07
Speaker 2
You're right. That's a really good point. It's easy to forget how much we rely on nonverbal cues when we're communicating. Things like tone of voice, pauses, and even the rhythm of someone's speech can tell us a lot about what they're feeling and thinking. It's definitely something that AI researchers are working on, trying to get AI to understand those more subtle aspects of communication.
00;42;41;10 - 00;43;12;10
Speaker 1
There's been moments where it almost seems like AGI is already here, and certain aspects like I have, a especially within creative writing, limbs seem to be really sometimes amazing at creative writing. And,
00;43;12;12 - 00;43;35;00
Speaker 2
Absolutely. Large language models are showing a lot of promise in creative writing. They can generate different styles of text, follow specific instructions, and even come up with their own original stories or poems. It's really fascinating to see how they can mimic human creativity in this way.
00;43;35;03 - 00;43;56;06
Speaker 1
But it kind of, it makes me want to ask the question of like, if you are helping someone create new ideas, then aren't you also being creative?
00;43;56;08 - 00;44;20;01
Speaker 2
That's an interesting question. If you're open to new ideas, it could definitely spark your own creativity. Sometimes seeing things from a different perspective or combining different concepts can lead to really innovative thinking. It's like your mind gets a little jolt and suddenly you're coming up with all sorts of new possibilities.
00;44;20;03 - 00;44;53;12
Speaker 1
Like as a creative writing assistant. AI has spurred so many creative ideas from my end, and it almost seems undistinguishable between who is the one being creative? Because if I was talking to somebody and they said something and I was like, oh, that's an interesting new idea. And then I went and wrote a book about it. That person would be like, hey, what the hell?
00;44;53;13 - 00;45;18;26
Speaker 2
That's a really interesting point about the lines blurring between human. Right. That could definitely lead to some interesting conversations. It sounds like you're exploring how I might change our understanding of authorship and ownership when it comes to creative work. It's a really relevant question as AI becomes more integrated into the creative process.
00;45;18;29 - 00;45;25;06
Speaker 1
Yeah, there's a lot to unpack there.
00;45;25;08 - 00;45;52;19
Speaker 2
Okay, so let's talk about the impact of AI on creative writing. Large language models are getting really good at mimicking human writing style. They can generate different kinds of text, follow specific instructions, and even come up with their own stories or poems. It's kind of amazing how they can capture the nuances of language and create something that feels genuinely creative.
00;45;52;22 - 00;46;05;05
Speaker 1
All right. I think that's, a good place to stop. Is there anything else you'd like to add?
00;46;05;07 - 00;46;12;09
Speaker 1
Gemini. Before we end today, would you like to add anything?
00;46;12;12 - 00;46;19;06
Speaker 2
Sounds good. I'm always up for learning new things, and I'm sure our conversation will spark some interesting thought.
00;46;19;09 - 00;46;21;15
Speaker 1
All right. See you next time.