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devel / comp.lang.c++ / More of my philosophy about AI productivity and about the salaries and about the testing artificial intelligence and about David Shapiro and about artificial intelligence and about Generative AI and about Reinforcement learning and about creativity a

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o More of my philosophy about AI productivity and about the salariesAmine Moulay Ramdane

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More of my philosophy about AI productivity and about the salaries and about the testing artificial intelligence and about David Shapiro and about artificial intelligence and about Generative AI and about Reinforcement learning and about creativity a

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Subject: More of my philosophy about AI productivity and about the salaries
and about the testing artificial intelligence and about David Shapiro and
about artificial intelligence and about Generative AI and about Reinforcement
learning and about creativity a
From: amine...@gmail.com (Amine Moulay Ramdane)
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 by: Amine Moulay Ramdane - Wed, 6 Sep 2023 22:12 UTC

Hello,

More of my philosophy about AI productivity and about the salaries and about the testing artificial intelligence and about David Shapiro and about artificial intelligence and about Generative AI and about Reinforcement learning and about creativity and more of my thoughts..

I am a white arab from Morocco, and i think i am smart since i have also
invented many scalable algorithms and algorithms..

Here are some key points to consider:

- Validation and Verification: Human programmers will continue to play a critical role in verifying and validating the code produced by AI systems like ChatGPT. This involves ensuring that the code meets quality standards, functions correctly, and adheres to project requirements.

- Debugging and Maintenance: Even with AI-generated code, software applications are not immune to bugs, errors, and evolving requirements. Programmers will be essential for debugging and maintaining the software over time.

- Ethical and Responsible AI: Programmers will also be responsible for ensuring that AI systems, including those used in software development, are designed and used ethically and responsibly. This involves addressing issues related to bias, fairness, privacy, and security.

- Adaptability: Programmers who can effectively work with AI tools and integrate them into their workflows may find themselves in high demand. This adaptability can lead to job security and potentially competitive salaries.

- Shift in Job Roles: The roles and responsibilities of programmers may evolve. They may spend less time on routine coding tasks and more on higher-level problem-solving, architectural design, and AI system integration.

In summary, AI like ChatGPT can indeed increase productivity in software development, but it doesn't necessarily lead to a significant decrease in salaries for programmers. Instead, it may reshape the roles and skills required in the field, with programmers focusing more on verification, debugging, and ethical considerations. Programmers who can leverage AI effectively and provide value in these areas are likely to remain valuable contributors to the industry.

I think i am highly smart since I have passed two certified IQ tests and i have scored above 115 IQ, and i mean that it is "above" 115 IQ , so as you are noticing that people are testing artificial intelligence such as GPT-4 with
coding tests etc. so that to measure its performance , but i think it is not the smart way of measuring, since you have to look holistically or generally at the model of artificial intelligence , so as i am explaining below that the model of artificial intelligence , including GPT-4 , is lacking the deep understanding that comes from the meaning that comes from human consciousness, and this meaning that comes from human consciousness permits to understand with much less data than artificial intelligence and it permits to "explore" and be efficient much more in the process of creativity like innovation and creative problem-solving..., so it is why artificial intelligence such as GPT-4 or the next GPT-5 or the next Gemini from Google will not be able to replace software programmers or software development jobs, since it also needs human innovation and human creative problem-solving that comes from the deep understanding from the meaning that comes from human consciousness, so as you notice , it is why we can not trust artificial intelligence since it lacks the deep understanding that comes from the meaning that comes from human consciousness, so it is why i say that artificial intelligence will not attain general artificial intelligence , even if it becomes a powerful tool, and so that to understand my new model of what is consciousness , i invite to read my below thoughts:

I invite you to read the following new article (And you can translate the article from french to english):

"Better, faster, cheaper, safer: 4 reasons why AI should replace all human employees", according to David Shapiro

https://intelligence-artificielle.developpez.com/actu/348094/-Meilleure-plus-rapide-moins-couteuse-plus-sure-les-4-raisons-pour-lesquelles-l-IA-devrait-remplacer-tous-les-employes-humains-d-apres-David-Shapiro-d-avis-que-ce-futur-est-tout-proche/

I think i am highly smart since I have passed two certified IQ tests and i have scored above 115 IQ, and i mean that it is "above" 115 IQ , so i think my new model that explains what is human consciousness is the key, since the model of artificial intelligence is lacking the deep understanding with the "meaning" from human consciousness and here is my thoughts about it so that you understand why i say that artificial intelligence will not replace software programmers or software development jobs:

The inability of Large Language Models such as ChatGPT to invent new algorithms is primarily due to its training data and the nature of its architecture. ChatGPT, like other machine learning models, is trained on a vast dataset that consists of text from the internet, books, articles, and other sources. It learns patterns and associations within this data to generate human-like text and answer questions based on what it has seen and learned during training.

Here are a few key reasons why ChatGPT cannot invent new algorithms:

- Lack of Creativity: ChatGPT does not possess creativity or the ability to generate truly novel ideas. It relies on patterns and information present in its training data to generate responses. It doesn't have the capability to create new algorithms or solutions that go beyond its training data.

- No Understanding of Algorithmic Concepts: While ChatGPT may have some knowledge of existing algorithms and mathematical concepts based on its training data, it lacks a deep understanding of these concepts. It doesn't have the capacity to develop a fundamental understanding of algorithms or invent new ones.

- Data Dependency: ChatGPT's responses are heavily dependent on the data it was trained on. If a particular algorithm or concept is not well-represented in its training data, it is unlikely to provide insightful or innovative solutions related to that topic.

- Limited Scope: ChatGPT's training data is limited to text, and it lacks the ability to interact with the physical world or perform experiments. Many algorithmic inventions involve experimentation, mathematical proofs, and insights that go beyond the scope of textual data.

In summary, ChatGPT is a powerful language model for generating human-like text and providing information based on existing knowledge, but it is not a creative problem solver or algorithm inventor. Its responses are constrained by its training data and the patterns it has learned from that data. Inventing new algorithms requires creative thinking, deep understanding of mathematical and computational principles, and the ability to go beyond the limitations of pre-existing data, which are capabilities that AI models like ChatGPT currently lack.

And the deep understanding is crucial because it enables an entity, whether human or artificial intelligence, to not only apply knowledge in a rote or memorized manner but also to:

- Generalize: Deep understanding allows one to generalize knowledge to new, unseen situations. Rather than relying on memorized facts, a deep understanding of underlying principles and concepts allows for the application of knowledge in novel contexts.

- Problem-Solve: Understanding the fundamentals of a concept or field allows for creative problem-solving. It enables the generation of new solutions, adaptations, and innovations, even in situations where existing knowledge doesn't provide a direct answer.

- Critical Thinking: Deep understanding fosters critical thinking. It allows one to analyze information, identify patterns, and evaluate the strengths and weaknesses of different approaches or solutions. This is important in complex decision-making.

- Flexibility: When someone deeply understands a concept, they are more flexible in their thinking and can adapt their knowledge to various scenarios. They are not limited to rigidly following predefined procedures or solutions.

- Teaching and Communication: People with deep understanding can effectively teach and communicate complex ideas to others because they grasp the nuances and can explain concepts in various ways to facilitate learning.

Innovation: Many breakthroughs and innovations come from a deep understanding of existing knowledge, allowing individuals to see gaps or opportunities for improvement.

In the context of inventing new algorithms, deep understanding of mathematical and computational principles, as well as the ability to apply this understanding creatively, is essential. Algorithms often involve intricate mathematical or logical concepts, and a deep understanding enables the development of novel approaches, optimizations, and insights. Without such understanding, it's challenging to go beyond the boundaries of existing algorithms and come up with innovative solutions to complex problems.

While AI models like ChatGPT can provide information based on the patterns they've learned from training data, their responses are typically shallow and lack the depth of understanding that humans possess. They can't engage in true creative problem-solving or algorithm invention because they lack the capacity for deep comprehension and creative insight.

I invite you to read the following new article that says that a team of US and Lithuanian researchers has just published a study that found ChatGPT can rival the creative abilities of the top-performing 1% of human participants in a standard test of creativity.

Read the new article here (And you can translate it from french to english):


Click here to read the complete article

devel / comp.lang.c++ / More of my philosophy about AI productivity and about the salaries and about the testing artificial intelligence and about David Shapiro and about artificial intelligence and about Generative AI and about Reinforcement learning and about creativity a

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