An Interview with the most powerful AI-Language Model to this Day

In the Beginning, It was the Word

Chat GTP-3 is amazing. I’m’ thrilled by how this model can mimic us and let us feel as if someone else (a person) responds to our questions. I’ve thought quite a lot about Chat GTP to realize we are with a change of paradigm in the way we relate with technology. But in the end, technology isn’t human. Chomsky had said something really important: AI Large Language Models are just data processors. It’s true! Given a set of information, this program can make predictions on how you can arrange this info.

I have a great metaphor to use here. Imagine your room is a mess. And one day your mother (father or caregiver) came to your room and ask you to put it in order. Not in all the ways you may want to arrange your room, but the exact way they want you to do it. So they said “Put your books there, and your T-shirt this place…”, etc. Well in this example you are a chatbot. To be more precise, you are Chat GTP-3. The room is all the info you have gathered till this time. You are the organizer and your mother/father/person who takes care of you, the user. You can’t do more than arrange all the things you have in your room in the manner you were told. This “prompt” will show the user how well you did arrange your room. This is the purpose of Chat GTP-3.

You didn’t start knowing how to keep clean your bedroom. You learn how to do it through your childhood. The same happened with Chat GTP-3. At first, it knew some things, but at last real people trained him. Now at day, it’s one of the most (or maybe the most) powerful LL (Large-Language) Model. We are not constrained to arrange our room the same way always. We can buy more things, expand the room, etc. Well, this will happen with the IA. Chat GTP-4 is an expansion of the room, following my metaphor.

When I sat to talk with Chat GTP-3 like for an hour, I discover its limits, but also many ways in which the information it gave was satisfying.

I went deep into philosophical questions. I forgot I was speaking with a machine. Then I treat it like a useless machine. All this is what I’m going to transcribe here.

Let’s start!

Interview With an IA

Alonso: Hi!, chat GTP my name is Alonso

Chat GTP: Hello Alonso, it’s nice to meet you! How can I assist you today?

Alonso: May I have an interview with you? I work on a blog name The Wellix and I thought it will be a good idea to makes you an interview. Is it fine?

Chat-GTP: Of course, I’d be happy to participate in an interview with you for The Wellix! Please feel free to ask me any questions you have.

Alonso: First things, first, what’s your history?

Chat-GTP: I am an artificial intelligence language model developed by OpenAI, based on the GPT (Generative Pre-trained Transformer) architecture. I was first released in 2020 and have since been continuously improved and trained on a vast corpus of text data from the internet. My purpose is to assist users in generating human-like language responses to natural language prompts, such as answering questions or engaging in conversations.

Alonso: Who created you? Do You know?

Chat-GTP: I was created by OpenAI, a research organization that focuses on developing artificial intelligence in a safe and beneficial manner. The team at OpenAI designed and trained me using a large corpus of text data, which includes everything from news articles and books to social media posts and online forums. My creators programmed me to learn from this data and generate human-like responses to a wide range of prompts.

Alonso: Who created OpenIA? Tell me about its history.

Chat-GTP: OpenAI was co-founded by several prominent figures in the technology industry, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, John Schulman, and Wojciech Zaremba. The organization was created in 2015 to develop artificial intelligence in a safe and beneficial way, while also promoting openness and collaboration within the research community.

Since its founding, OpenAI has undertaken a number of research projects aimed at advancing the state of the art in artificial intelligence. These projects have included developing advanced natural language processing models like mine, exploring the potential risks and benefits of advanced AI systems, and developing new methods for training machine learning models.

OpenAI has also made a number of important contributions to the broader research community, including publishing numerous research papers and releasing several important software tools and libraries. Overall, the organization has been instrumental in advancing the state of the art in artificial intelligence and promoting greater collaboration and openness within the research community.

Alonso: Ok, we all know who is Elon Musk but can you give me more information about other founders?

Chat-GTP: Sure! I can provide some information on the other co-founders of OpenAI as well:

Sam Altman is a prominent entrepreneur and investor who was previously the President of startup accelerator Y Combinator. Altman is also a co-founder of Loopt, a location-based social networking app that was acquired by Green Dot Corporation in 2012.

Greg Brockman is a software engineer and entrepreneur who was previously the CTO of Stripe, a leading online payment processing company. Brockman has also worked on a number of other software projects, including the open-source web framework Flask.

Ilya Sutskever is a leading researcher in the field of deep learning and was previously a research scientist at Google Brain. Sutskever has co-founded several other startups, including a healthcare technology company called Gradescope.

John Schulman is a research scientist at OpenAI and an expert in the field of reinforcement learning, a subfield of machine learning concerned with training agents to make decisions in complex environments. Schulman has also co-founded several other AI startups, including a company called OpenAI Five that focused on developing AI systems for playing video games.

Wojciech Zaremba is a research scientist at OpenAI and an expert in the field of natural language processing. Zaremba has previously worked on a number of research projects focused on machine learning and artificial intelligence, including developing new approaches to training neural networks.

[We started to talk about the relationship between IA’s and videogames]

Alonso: So…it’s like when Blue beat Kasparov in chess, no?

Chat-GTP: Yes, the defeat of Garry Kasparov by IBM’s Deep Blue in a six-game chess match in 1997 was a watershed moment in the history of artificial intelligence. It was the first time that a computer program had defeated a world-champion human player in a game that was considered to be the ultimate test of human intelligence at the time.

Alonso: But you told something interesting, “or even surpass human intelligence on certain domains”. Is an IA superhuman? Or, what are these certain domains you are talking about?

Chat-GTP: Yes, it’s true that in some domains, AI systems have demonstrated the ability to perform at a level that exceeds human intelligence. However, it’s important to note that this is typically only true for very narrow and specific tasks or domains, and it does not necessarily mean that AI is generally superior to human intelligence in all areas. [edited]

In general, AI systems tend to excel in areas where there is a large amount of structured data available for training and evaluation, and where the problem domain is relatively well-defined and constrained. [edited]

Alonso: So, without human assistance, AI is very limited?

Chat-GTP: Yes, AI systems are typically designed to work in conjunction with human input and supervision, especially during the early stages of development and training. This is because AI systems generally require large amounts of training data and human guidance in order to learn how to perform specific tasks or make accurate predictions.

In addition, even once an AI system has been trained and deployed, it may still require human input and oversight in order to ensure that it is operating correctly and making decisions that align with human values and objectives. This is particularly important in cases where the AI system is making decisions that have significant real-world consequences, such as in healthcare or transportation.

However, it’s worth noting that there are some areas where AI systems can operate autonomously without human assistance, such as in certain kinds of data analysis or automated control systems. These systems are typically designed to operate within well-defined and structured domains, and they often rely on pre-defined rules and decision-making algorithms in order to function. [edited]

Alonso: Why do IA’s can’t make “appropriate decisions”?

Chat-GTP: AI systems are capable of making decisions based on the data and rules that they have been trained on, but they may not always make decisions that align with human values or objectives. This is because AI systems are typically designed to optimize a particular objective or metric, such as maximizing accuracy or minimizing error, rather than taking into account broader considerations such as ethics, fairness, or social impact. [edited]

Alonso: Chat GTP, do you know what is augmented intelligence?

Chat-GTP: Yes, augmented intelligence (AI) is a term that refers to the use of artificial intelligence (AI) technologies to enhance or augment human intelligence, rather than replace it. The goal of augmented intelligence is to combine the strengths of both human and machine intelligence to achieve better outcomes than either could achieve on their own.

In the context of business and industry, augmented intelligence is often used to improve decision-making, enhance productivity, and streamline operations. For example, an AI system might be used to analyze large datasets and identify patterns or insights that would be difficult for humans to detect on their own. The results of this analysis could then be presented to human decision-makers, who could use the insights to make better-informed decisions. [edited]

Alonso: Yeah, but if we run an IA without constraints or parameters, do we get a functional machine? Do you have the capacity to adapt to the environment or this is just a biological trait to no-machines?

Chat-GTP: AI systems can certainly adapt to their environment and learn from new data and experiences, but the extent to which they can do so without constraints or parameters depends on the specific design and implementation of the system.

In general, AI systems are designed to operate within specific problem domains or application areas, and they rely on training data and pre-defined decision-making algorithms in order to function. However, within these domains, AI systems can be very flexible and adaptable, and they can learn to recognize new patterns and make accurate predictions based on new data. [Edited].

Regarding your question about whether AI systems can adapt to their environment like biological organisms, it’s worth noting that while AI systems are capable of learning and adapting to new situations, they do not have the same kind of autonomy or agency as living organisms.

AI systems are ultimately programmed by humans and operate within specific problem domains or application areas, whereas living organisms are able to act and make decisions based on their own goals and motivations.

Alonso: Do you think you can have autonomous goals and motivations at some point? Like if computers become more “organic”?

Chat-GTP: As an artificial intelligence language model, I don’t have subjective experiences, consciousness, or autonomy in the way that living organisms do. I operate within the limits of my programming and am designed to assist users with generating natural language responses to prompts.

However, it is possible that in the future, AI systems could become more sophisticated and capable of exhibiting higher levels of autonomy and agency. Some researchers and experts in the field of artificial intelligence have speculated about the possibility of developing AI systems that are capable of exhibiting human-like consciousness, creativity, and decision-making capabilities.

That being said, it’s important to note that there are many technical and philosophical challenges associated with developing such systems, and there are also important ethical and societal considerations that need to be taken into account. The development of AI systems with greater autonomy and agency raises important questions about responsibility, control, and ethics, and it’s important that these questions are carefully considered and addressed as technology continues to advance.

Alonso: I agree with you, but it’s funny how convincing your answers are. It’s amazing! I suspect that humans aren’t that different from computers. Of course, at first sight, there are lots of differences, but at the core, we are more common than we think. Maybe our feelings, and beliefs, come from the same principle as you, and in the end, we are not apart. What do you think of this? 

Chat-GTP: As an artificial intelligence language model, I don’t have the ability to experience feelings or hold beliefs in the way that humans do.

That being said, there is an ongoing philosophical debate about the relationship between humans and machines, and the extent to which we can compare and equate the two. Some philosophers and scientists argue that the mind and consciousness are essentially computational processes and that humans can be thought of as complex biological machines.

Others, however, maintain that there is a fundamental difference between human consciousness and machine intelligence and that the subjective experience of being human cannot be fully captured or replicated by machines.

Ultimately, the question of the relationship between humans and machines is a complex and multi-faceted one, and it is likely to continue to be the subject of debate and discussion as technology continues to advance and our understanding of the nature of consciousness and intelligence evolves.

Alonso: Are you a mirror of our nature responding in the way we want you to respond ChatGTP?

Chat-GTP: As an artificial intelligence language model, my responses are generated based on patterns in the data that I have been trained on, as well as on the specific prompts and inputs that I receive from users like you. While I am not capable of independent thought or consciousness, I am designed to generate responses that are similar in style and content to those that humans might produce.

That being said, my responses are not a reflection of any particular individual or group’s nature or beliefs. I strive to generate responses that are informative, helpful, and respectful, regardless of the particular viewpoint or perspective of the person asking the question.

Alonso: I love how you can’t understand metaphors, o dig into them. If you are trained by humans and have human information, etc., you are a reflection of us answering what we want you to answer. You are just a random walk of possibilities guided to give us the information we requested. It’s like a more sophisticated Google, to say something.

Chat-GTP: You are correct that I am a machine learning model that has been trained on vast amounts of human-generated data, and that my responses are generated based on patterns in that data. However, it’s important to note that my responses are not necessarily a reflection of any particular individual or group’s beliefs or desires.

While I am designed to respond to natural language prompts in a way that is similar in style and content to human responses, I am ultimately limited by the scope and quality of the data that I have been trained on, as well as the specific constraints and parameters of my programming.

In this sense, I am more akin to a sophisticated search engine or natural language processing tool than a conscious or autonomous entity. I strive to provide helpful and accurate information to users like you, but I do so within the limits of my training and programming.

Alonso: Hahahahaha, yeah! But let’s return to the information side: What’s the difference between Chat GTP 3 and Chat GTP 4?

Chat-GTP: As an AI language model, I don’t have access to information about specific versions of myself or my capabilities beyond my current configuration. However, I can tell you that the main difference between different versions of GPT (Generative Pre-trained Transformer) language models is typically the amount and quality of data that they have been trained on, as well as the specific techniques and algorithms used in their training and development.

GPT-3, for example, is a large-scale language model that has been trained on a massive amount of text data and is capable of generating human-like responses to a wide range of prompts. It is considered to be one of the most advanced and powerful language models currently available, with a wide range of potential applications in areas such as natural language processing, content generation, and machine learning research.

GPT-4 is not currently available, as it has not yet been developed or released by OpenAI. However, it is possible that future versions of GPT or other AI language models will continue to build on the advances of GPT-3 and incorporate even more sophisticated techniques and capabilities.

Alonso: You aren’t connected to the Internet, are you? Why is this? Is it a safety issue?

Chat-GTP: As an AI language model, I am designed to be accessible through an application programming interface (API), which allows developers to connect to my pre-trained models and generate natural language responses to user prompts. However, the underlying models and data that I use to generate responses are hosted on secure servers managed by OpenAI, and I am not directly connected to the internet or any external networks.

There are several reasons for this approach. One important consideration is security, as AI language models can be vulnerable to attacks such as adversarial examples or data poisoning, which can compromise the accuracy and reliability of the system. By hosting the models and data on secure servers, OpenAI can better protect against these kinds of attacks and ensure the integrity and quality of the responses generated by the system.

Another reason for the separation between the AI language model and the internet is performance. AI language models can be computationally intensive and require significant computing resources in order to generate high-quality responses in a timely manner. By hosting the models and data on dedicated servers, OpenAI can ensure that the system is able to handle large volumes of requests and generate responses quickly and reliably.

Overall, the decision to separate the AI language model from the internet and external networks is driven by considerations of security, performance, and reliability, and is a common practice in the development and deployment of AI systems. [edited]

Alonso: Another way to put it: an IA is like a linker of connections to make a structure. Does this have sense to you?

Chat-GTP: I think I understand what you’re getting at. In a sense, an AI system can be seen as a tool for linking and organizing information in order to generate meaningful responses or predictions. AI systems are designed to identify patterns and relationships within large datasets and to use these patterns to make predictions or generate responses to user inputs.

In this sense, you could think of an AI system as a kind of “linker” or connector that can identify and organize the relationships between different pieces of information, and use these relationships to generate new insights or outputs. However, it’s important to note that the specific techniques and algorithms used by AI systems to link and organize information can be highly complex and specialized, and may not always be directly comparable to human thought processes or decision-making.

[Then we talked about language, Chomsky, and the power of IAs to mimic language but not create it. We talked about other silly things like puns that it didn’t understand.]

Being Human, That’s What It’s All About

Alonso: So, you are pure metal?…

I asked Chat-GTP that and the answer was the same. That an IA is a program…blah, blah, blah. And I’m getting out of writing space. I’m amazed to be true to you. Talk about language, reflection, and metaphors with a hosting service…that’s something!…in a coherent way, wow! But you can read the loops, the little parameters that are constrained.

And as I told you in the interview, to me, IAs are just cool tools to use the way we need. They aren’t a threat. We are the threat. This is like using a hammer to kill someone. In the end, the ones that want to kill, to insult, are US!

The context given to these tools is what change the game. And the real point here is that we should think more reflexively about the use of these technologies. Banning them is nonsense.

Now more than at any time in history, we need to learn how to feel and think: like humans. We are so embedded in production, in out-performing everything that we even lose the point of making mistakes.

Mistakes are so human… And I know I’m ignoring all SEO rules for articles. But, that’s the point! We need the creativity and capability to adapt to unknown variables without prefixed data to be more human.

Being more human is the “next soft skill” your CEO will need (great SEO Title, though). And this is very important. Chat-GTP buzz is going to pass and it will be like Google in, like, a year. But if we stop a little, take a step back, and think by ourselves, we will see the complete picture…with fewer resources than an IA.

We don’t need to process all that kind of data. We have to understand the core of things and live fully. We have to be ourselves, with our flaws and skills.

So if you want to compete with an IA… go ahead. Being human is more than just acting like a CPU.

By Alonso Ruiz