(This isn’t my opinion, just saying what I think they are)
They are saying it’s not intelligent in any way though. It sees a bunch of words as numbers and spits out some new numbers that the prediction algorithm creates.
What you’re thinking of as AI is actually a narrower version, while true intelligence is termed AGI.
Explanation:
The term ‘AI’ (Artificial Intelligence) refers to computer systems that can perform tasks that would typically require human intelligence, like recognizing patterns or making decisions. However, most AI systems are specialized and focused on specific tasks.
On the other hand, ‘AGI’ (Artificial General Intelligence) refers to a higher level of AI that possesses human-like cognitive abilities. AGI systems would be capable of understanding, learning, and applying knowledge across a wide range of tasks, much like us.
So, the distinction lies in the breadth of capabilities: AI refers to more specialized, task-focused systems, while AGI represents a more versatile and human-like intelligence.
The term ‘AI’ (Artificial Intelligence) refers to computer systems that can perform tasks that would typically require human intelligence,
That’s everything computers do, though, isn’t it? Pocket calculators would have fit this definition of AI in the 1970s. In the '60s, “computer” was a human job title.
Unless your pocket calculator can recognise patterns or make decisions, it doesn’t fit the description.
Fair enough. What evidence have you got that it’s any different than what humans do? Have you looked around? How many people can you point to that are not just regurgitating or iterating or recombining or rearranging or taking the next step?
As far as I can tell, much of what we call intelligent activity can be performed by computer software and the gaps get smaller every year.
That’s not how ChatGPT works.
GPT is an LLM that use RNN. An RNN (Recurrent neural network) is not an algorithm.
Yea, but not really. The algorithms are available for free, but they don’t do anything useful by themselves. The RNN is built by training the neural net, which uses grading/classification of training data to increase or decrease millions of coefficients of a multi-layer filter. It’s the training data, the classification feedback and the processing power that actually creates the AI.
