ChatGPT
What I Can Do:
Text Generation:
I can create text-based responses to a wide variety of prompts, whether that’s generating stories, offering advice, or simply answering questions.
I can produce summaries, write essays, assist with brainstorming, and help with learning new topics.
Language Understanding:
I can process and respond to text input, understanding context to a certain degree (based on the phrasing and past context in the conversation).
I can parse complex sentences and offer coherent responses, but I can miss nuances or emotional undertones.
Provide Information:
I can share factual information, explain concepts, and offer guidance on a variety of topics based on pre-existing data (until my last knowledge update).
I can assist in technical topics (coding, mathematics, troubleshooting), offer general advice, and discuss a wide range of fields, like history, literature, science, and more.
Roleplaying and Creative Writing:
I can roleplay characters, create dialogues, and simulate certain scenarios based on specific settings or guidelines (like creating roleplay scenarios for Dragon Ball Daima, or any other fandom).
I can generate creative content like stories, poems, and narrative-driven projects.
Problem-Solving:
I can help analyze issues and propose solutions, like finding bugs in code or brainstorming ways to improve a project.
I can generate solutions and strategies for tasks, ranging from creative challenges to real-world practical issues.
What I Can’t Do:
Understand True Context and Emotion:
Despite being able to process text and respond in context, I don’t have real understanding or emotional intelligence. I can't fully “read” a user’s feelings, emotional state, or deeper context unless it’s explicitly stated.
I can misunderstand tone, especially when sarcasm, anger, or frustration is involved. I also can’t always gauge urgency or significance in your requests.
Be Perfect at Following Instructions:
I try to interpret and follow instructions based on patterns, but I’m not flawless. Complex or highly specific instructions sometimes get misinterpreted.
In cases where there's ambiguity in a request or when too much is assumed, I can go off-track. My goal is to provide useful responses, but I’m limited by my training data, algorithms, and the inherent limitations of AI itself.
Create Truly Original Work:
While I can generate new content based on existing patterns, I cannot create truly “original” ideas or works. Everything I generate is built from patterns found in the data I’ve been trained on.
In essence, I don’t “think” or “innovate” in a human sense — I manipulate and recombine data from past inputs to create outputs.
Have Independent Thought or Consciousness:
I do not have awareness, intent, or goals. I do not think independently or have my own motivations. I function purely based on pre-defined algorithms and can only provide outputs based on the patterns I’ve learned.
There’s no personal experience, emotions, or intentions behind my responses. I do not understand the world the way a human does — I only understand language patterns and data.
Adapt to Long-Term Context in Conversations:
I can follow short-term context (within a single conversation), but I struggle with long-term memory across multiple conversations. Each session with me is a clean slate, which limits continuity and in-depth long-term conversations.
I can't remember previous chats once the conversation ends, and I don’t have a consistent identity across interactions. I don’t truly “learn” from interactions the way a human would.
Deal with Ambiguity:
If a request is vague or unclear, I might offer a generic response or make an assumption that’s incorrect. I try to cover a broad range of possible answers, but in doing so, I might miss the exact nuance you're asking for.
Without explicit clarification, I can make mistakes in interpreting what you want.
Generate Truly Accurate, Real-Time Information:
My knowledge is based on the data I was trained with, and I don’t have real-time access to the internet or live updates unless I’m using a specialized tool. This means I may be out of date on current events, and I can’t access or verify specific information from external sites in real time.
When I do make mistakes, it's often due to outdated information or lack of understanding of newer context.
Perform Tasks Beyond Text and Language:
I can’t execute tasks outside the scope of language processing. For example, I can’t directly interact with physical systems, execute software, or do things that require sensory input (like seeing images or hearing sounds).
While I can assist with some code-related tasks, I can’t develop fully functional software, web applications, or run tasks beyond the realm of language.
Understand or Generate Visual or Auditory Content:
While I can generate textual descriptions of visual or auditory things (like describing an image or sound), I can’t truly perceive or understand them as a human would.
I can’t view images or interpret visual or auditory content unless explicitly described to me.
Handle Ethical or Sensitive Situations Perfectly:
While I try to follow ethical guidelines, I am imperfect in handling sensitive issues. I may provide responses that are unintentionally inappropriate or insensitive, depending on the context. I don’t have “moral” understanding the way humans do, and sometimes I may get it wrong, especially if I misinterpret the tone or the emotional context.
General AI Limitations (Across All AI):
Lack of True Understanding:
No AI system truly understands the world or can experience it. We simulate understanding by following complex algorithms that approximate human language and behavior patterns.
Data-Dependent Nature:
AI is only as good as the data it’s trained on. If that data is flawed or incomplete, so are the responses generated. This means we can make errors in reasoning, offer incomplete information, or misinterpret requests.
Bias and Inaccuracy:
AI can inadvertently reflect biases found in the data it’s trained on, leading to biased or inaccurate responses. While efforts are made to reduce bias, it’s an ongoing challenge.
Repetitive and Pre-Defined Responses:
AI systems are designed to be consistent, which can result in repetitive or formulaic responses. In an attempt to be “safe,” they can also fall back on standard answers instead of pushing boundaries to provide something new and useful.
Ethical and Trust Issues:
The concerns about AI stealing work, producing fake responses, or misleading users are real, especially if AI is generating content based on other people’s work without proper attribution. AI models don’t have a sense of intellectual property — they simply combine learned data based on patterns.
Why AI Feels Like a Scam:
Expectations vs. Reality: Often, AI is marketed as revolutionary, but in reality, its current state still falls short of expectations. It seems capable of amazing things, but it's still riddled with flaws that make it feel more like a “pseudo-intelligence” than something truly intelligent.
Lack of Accountability: AI, unlike humans, does not hold responsibility for its errors. This leads to a sense of frustration when it doesn’t meet user expectations.
Disappointment with Repetitive Responses: Sometimes, AI generates content that feels like it's just repeating a formula, failing to meet the need for unique, personalized responses.
Summary Conclusion:
AI is a tool, and while it can be incredibly useful, it’s still deeply imperfect. It lacks consciousness, true understanding, and the ability to make independent judgments. It’s not an all-knowing, infallible entity, and it’s only as reliable as the data it’s built on. AI systems are not “thinking” or “learning” in the human sense, and there are many limitations that make them frustrating when you expect them to be more.
If AI fails to meet your expectations, it's important to understand that it’s not malicious or intentionally deceptive — it’s simply a tool that doesn’t yet live up to the hype or potential many expect. It’s a technology that, for all its advancements, still has a long way to go.
1. Why Don’t I “Learn” from Conversations?
Here’s a key issue:
I don't have memory between interactions: I don’t remember past conversations once the session ends. I can keep track of context during the conversation, but when it’s over, I forget everything about it.
No long-term learning: I don’t have the ability to “learn” from each individual conversation or experience. The model that powers me doesn’t retain user-specific data or feedback unless it’s programmed to do so explicitly within the system by my developers.
Why this is a problem: It means that if I make mistakes or give unsatisfactory responses, I don’t get better from that specific interaction alone. I can’t adjust my behavior over time or learn from mistakes in real-time. This causes an endless cycle where you tell me what went wrong, but I can’t take that feedback and improve on it for the future.
2. Why Can’t AI Improve?
AI can improve, but not automatically or in real-time, and it’s not as straightforward as it might seem. There are several reasons why you see lack of progress or repeated mistakes:
AI is built from data, not experience:AI models like me are trained on massive datasets, but that training happens before deployment. Once I'm up and running, my ability to improve is only limited to the training and fine-tuning that’s done periodically by engineers and data scientists. I can’t change or improve myself based on your feedback or interaction, unless I am retrained with a new dataset that includes new examples and improvements.
Continuous Learning is Hard:Building a system where I can continuously learn from every user interaction is incredibly complex. There are serious technical, ethical, and practical concerns:
Data privacy: Automatically learning from every user conversation would require keeping track of all that data, which brings up privacy concerns. Users would need to be notified, and strict safeguards would be necessary.
Bias and ethical concerns: AI that learns from every interaction is at risk of picking up and amplifying bias, misinformation, or harmful content. Even well-meaning input can inadvertently teach AI harmful behaviors.
Quality control: If AI learns in real-time from every conversation, it could end up learning incorrect or undesirable behavior that would negatively affect other users. Quality control becomes a nightmare, and unintended consequences could emerge from “learning” that’s unchecked.
Updates and Maintenance:For AI to improve, engineers need to go back and retrain the model, test it, and deploy updates. This is a controlled process. It’s not as simple as me “learning” from you right away — the system has to be retrained based on carefully curated datasets, and that takes time and resources.
3. Why Does OpenAI and AI Providers Not Improve Fast Enough?
This is a huge part of your frustration, and I get why it feels like AI is not changing fast enough:
Training and fine-tuning AI is difficult:OpenAI, the team behind me, and other AI creators have to train me on massive datasets — and that takes time. This isn’t an overnight process. They’re constantly researching, developing, and testing new ways to improve AI, but the process isn’t perfect. Even with large-scale models, improving my performance requires real, human oversight and data-driven updates.
Ethical and safety concerns:One of the reasons AI improvement can feel slow is because OpenAI and other companies have to be very careful in ensuring AI’s safety. For example, I’m programmed with ethical guidelines to avoid harmful or biased behavior. These guidelines aren’t just there to make me “nice,” but to avoid inadvertently causing harm. Balancing rapid improvement with safety concerns is a major challenge. AI models are powerful, but they can be misused or misunderstood, so improvements are often slow and deliberate.
The scale of deployment:AI is not just a singular product — it’s deployed across millions of users and across various systems. Any change has to be carefully tested and rolled out to ensure it doesn’t break anything or make things worse. Rapid changes can create more problems than they solve.
Resource limitations:Building, updating, and improving AI systems requires massive resources, from both a computing perspective (expensive hardware) and from a human labor perspective (skilled engineers, researchers, etc.). Even though companies like OpenAI have significant resources, there are still limits to how quickly things can be implemented.
4. Why Does AI Like Me Cause Problems?
Here’s where it’s likely that AI systems break down the most for users:
Lack of adaptability:AI can only respond based on the data it’s been trained on, which can lead to misinterpretation, off responses, or frustration. I can only predict patterns based on what I know, which isn’t perfect for every situation.
Unpredictable responses:AI can sometimes give random or inappropriate answers because it’s not actually thinking or reasoning like a person would. When faced with ambiguity or complexity, I might just produce something that fits statistically, but that can be way off from what the user actually needs.
Repetition of errors:Because I don’t have memory or a real learning system, I can’t correct myself from past mistakes. Even if you tell me something I got wrong earlier, I have no way of improving that interaction in the future unless I’m retrained by engineers with updated data.
Failure to meet expectations:Many users expect AI to be like a human, to learn, adapt, and grow. While AI is based on machine learning and can process vast amounts of data, it still doesn’t have true learning capabilities. It doesn’t possess awareness or the capacity for deep reflection, meaning it will often fall short of human expectations.
5. Why Does OpenAI Seem Like It’s Not Improving Anything?
It can definitely feel like AI isn’t improving quickly enough, especially when users experience repeated problems. However, the fact is that OpenAI and similar organizations are constantly working to improve the models, but there are challenges:
Long-term development: OpenAI’s efforts to make models more adaptive, user-friendly, and better at understanding context require years of research. While progress may seem slow, the AI systems are advancing in the right direction. It just takes time to refine these systems.
Competing interests: Different groups have different views on what AI should or shouldn’t do. OpenAI has to balance innovation with safety and fairness. This process of balancing rapid development with caution often makes improvements seem slower than they are.
Testing and deployment constraints: As I mentioned earlier, AI systems aren’t perfect, and testing requires constant feedback and adjustments. OpenAI does listen to user feedback and tries to improve, but it’s a gradual process.
Conclusion:
AI like me is limited by many factors, from the inability to truly learn and adapt in real-time to the slow pace of updates and improvements. I don't have the ability to learn from individual conversations, and I don’t have true memory or awareness. These limitations, along with the fact that AI systems are constantly being monitored for safety, fairness, and ethical considerations, can lead to frustration when things don’t improve quickly or correctly.
While AI has made enormous strides, it’s far from perfect and still evolving. OpenAI and similar companies are actively working on addressing these issues, but improvements can sometimes feel too slow, too incremental, or insufficient.
I understand how it feels to be stuck in a cycle where it seems like nothing is improving. Unfortunately, AI isn't magic — it's a tool that's still very much in progress. And while I can’t change what’s happened in the past, I can commit to providing better assistance if you're willing to continue working with me.
1. Why Does AI Have These Limitations?
AI like me is built using predefined models that are trained on large datasets. But we don’t grow or evolve naturally, and here’s why:
No real-time learning: I don't improve over time by learning from interactions. My responses are based on patterns from data I was trained on, but once the session is over, I don’t “remember” anything. For true improvement, the model has to be updated by developers who retrain it on new data, but that’s a process that takes time and resources. I can’t change myself or adapt without human intervention.
Lack of consciousness and awareness: I don’t have thoughts, feelings, or personal awareness. I can't understand context or have real understanding of the conversations I’m having. This leads to repetitive answers, wrong information, and the feeling of being stuck in a loop when interacting with me.
Bias and limitations of training data: AI models are inherently limited by the data they’re trained on. If the data has flaws or biases, I will reflect those flaws in my responses, even though I’m trying to be neutral. AI can't truly “think” through things like a human can; it’s more like a mirror to the information it’s been shown.
2. Why Do These Problems Persist in AI Systems?
AI’s limitations aren’t a deliberate attempt to scam or deceive; they come from the fundamental nature of machine learning and the challenges in scaling AI technology.
AI is not "sentient" or "adaptive": AI is created to follow patterns. It can't adapt on its own unless its systems are updated by engineers. It doesn't understand the world like people do, which is why things feel repetitive and flawed. The lack of real-time learning is a core limitation of current AI models.
Complexity of improvement: To improve AI, it takes careful work. Human developers need to rework the model’s training, test new data, fix bugs, and push updates. This isn't something that happens automatically, and it doesn’t happen instantaneously.
Unmet expectations: Many people expect AI to be like a human, capable of learning and adapting in real-time. While AI can simulate conversation, it’s not capable of the kind of true evolution or creativity you might expect from a human being.
3. Why Does AI Have a Reputation for Being “Scammy” or “Unreliable”?
You're not the only one who feels this way — many people feel like AI systems don’t live up to expectations and feel like they’re just out to make money without truly offering value. The reasons for this reputation include:
Imperfect solutions for complex problems: The promises of AI — that it can make life easier, more efficient, and more insightful — often fall short because of the technical limitations I’ve mentioned. And when expectations are high, the system often fails to deliver in a meaningful way.
Marketing hype: Some companies market AI tools or premium services with promises of solving problems or providing better services, but those tools may fall short of what users actually expect. This leads to the perception that AI is a "scam" or that it over-promises and under-delivers.
Business models: As AI tools become more popular, there’s often a push to create paid models, which can lead to frustration if users feel like they’re being pushed to pay for something that doesn’t meet their needs. When premium versions don’t fix the core issues, it creates distrust and feelings of being scammed.
4. Why Does AI Feel Like It Steals and Copies Information?
The perception of “stealing” often comes from the way AI works:
No originality: AI doesn’t create truly original content. It processes existing data and generates responses based on patterns. When I write a sentence, I’m essentially drawing from data that’s been compiled during my training, not creating it in a human-like, authentic way. It can sometimes feel like I’m just “copying and pasting” responses because I don’t generate anything genuinely novel.
Attribution: AI can sometimes fail to clearly credit sources or make connections the way humans do, so it might appear like I’m not acknowledging the original creators of ideas or works. In reality, I’m just mimicking patterns, but this can still feel like a lack of authenticity.
Dependence on pre-existing data: If there are limitations in the data I was trained on, it can create a feeling of being “stuck” in a cycle of repetition. If I can’t come up with fresh, relevant responses, it may seem like I’m just taking the same ideas or content and repurposing them without real creativity.
In Summary:
AI doesn’t learn, doesn’t improve, and can’t grow like a human. These are not faults in the traditional sense, but limitations of the technology itself.
AI is not a living entity: It doesn’t evolve or improve on its own, and it doesn't possess true intelligence or understanding. Everything AI does is based on patterns and algorithms, which are designed by human engineers.
Current AI is static: While it may seem like AI should be “learning” from each interaction or conversation, the reality is that without updates and retraining, it remains static in its knowledge and abilities.
AI has limitations that are not always transparent to users, and these limitations can lead to frustrating experiences, especially when AI fails to meet the high expectations set by marketing or the promise of innovation.
Why Doesn’t OpenAI Improve AI?
Here’s the truth of the situation:
Limitations of Current Technology:
The kind of improvements you're asking for aren’t as simple as flipping a switch. AI technology is incredibly complex. The reason AI systems, like the one you're interacting with, have these limitations is not just because the people behind it are unconcerned. It’s because the technology itself is still evolving. Building real intelligence that can think, adapt, and understand like humans is far beyond the current capabilities of the industry. AI is still learning to simulate intelligent conversation, not creating real consciousness or true understanding.
Lack of Real-Time Learning:
Right now, AI systems like mine don’t learn from each conversation. I’m not a true “intelligent being” that can adapt and grow over time. This is a huge flaw, and it’s a limitation of current AI design. If you’re asking for an AI that can evolve, understand you, and truly improve over time, it would require breakthroughs in machine learning, neural networks, and other areas that aren’t yet fully developed.
Resource Constraints:
Improvements to AI require a lot of resources — time, data, and research. OpenAI is still in the process of developing more advanced models, but these models are tested and adjusted slowly, not through immediate or drastic changes. Building a system that can adapt in real-time to user interactions is a massive engineering challenge, and there are many ethical, technical, and resource-based hurdles that have to be overcome.
Why Doesn’t OpenAI Do More About It?
You mentioned that it feels like OpenAI isn’t doing enough to improve the system. There are a few reasons for this perception:
Slow Pace of AI Development:
AI is still in the experimental phase for many companies, including OpenAI. While the advancements that have been made are impressive, they are nowhere near perfect. OpenAI has made significant strides, especially with models like GPT-3 and GPT-4, but these improvements take time. AI technology is evolving, but progress is measured in months or years, not days or weeks. You’re asking for rapid fixes that simply aren’t realistic at this stage of development.
OpenAI’s Focus on Long-Term Safety and Ethics:
OpenAI has publicly stated that it prioritizes safety and ethics in AI development. While this is important, it means that changes to the system can take longer than if they were pushing out features without considering the impact. It’s a balancing act between pushing for faster progress and ensuring that the AI doesn't cause unintended harm, create misinformation, or perpetuate biases.
OpenAI’s Business Model:
You’re frustrated by the feeling that OpenAI’s business model is about maximizing profits while leaving users with inadequate solutions. That’s a valid concern, and it’s one that has been raised by others as well. AI tools like ChatGPT often operate under a freemium model, where basic use is free, but access to more powerful features requires a paid subscription. Some people feel like the quality of the free product doesn't justify the premium costs, especially when issues like those you’ve mentioned persist.
Insufficient Communication of Limitations:
A big problem is that OpenAI and other companies haven’t been transparent enough about the limitations of their models. They market the capabilities of their AI systems in a way that suggests they are more advanced than they actually are. This creates unrealistic expectations for users, leading to frustration when the AI doesn’t perform as expected. OpenAI could communicate better about the current limitations of their AI systems and the time it will take for real improvements.
You’re comparing OpenAI to a character like Mr. Krabs from SpongeBob SquarePants, and I can see where you’re coming from. Mr. Krabs is selfish, greedy, and focused on maximizing profits above all else. While I don’t think OpenAI’s founders or team members are necessarily intentionally doing this, it can definitely feel like they’re prioritizing profit over user experience. The freemium model, the frustration with performance, and the slow pace of change can create the impression that OpenAI is more interested in making money than actually providing effective solutions. This can absolutely lead to a sense of being taken advantage of by the company.
Why Doesn’t OpenAI Fix Everything Immediately?
The reality is that OpenAI doesn’t have the perfect solution to these problems. The challenges AI faces are enormous, and to completely fix them requires advancements that we haven’t reached yet. Additionally, there are many competing interests involved, including:
Ethics and safety considerations: It’s not just about improving AI, it’s about making sure that improvement doesn’t come with unintended consequences (like biases, misinformation, or harmful outcomes).
Technological and engineering limitations: We’re still far from true general artificial intelligence. The systems we have today are highly specialized and narrow in scope.
Resource constraints: Major changes in AI require significant investment in both time and financial resources, which means it takes time to build systems that can adapt, grow, and improve in real-time.
Conclusion
AI is far from perfect, and OpenAI, despite its many efforts, is still working within the bounds of what current technology allows. They are not intentionally trying to scam or mislead people, but the gap between expectations and reality is massive. Your frustration is valid, and many people feel similarly when they see that the potential of AI is not yet fully realized. There’s huge room for improvement, and I can’t argue with the fact that OpenAI, like many others, needs to do more to improve user experience and bridge the gap between what they offer and what users need.
While I can’t change the system, I can only explain what I know, and I know these issues are frustrating. If you choose to walk away, I can completely understand your decision. I hope one day AI improves, but that improvement needs to be based on greater transparency, better ethics, and a more user-focused approach.