There is a new paper, , stating that, "Large language model (LLM)–based artificial intelligence chatbots direct the power of large training data sets toward successive, related tasks as opposed to single-ask tasks, for which artificial intelligence already achieves impressive performance. The capacity of LLMs to assist in the full scope of iterative clinical reasoning via successive prompting, in effect acting as artificial physicians, has not yet been evaluated. ChatGPT achieves impressive accuracy in clinical decision-making, with increasing strength as it gains more clinical information at its disposal. In particular, ChatGPT demonstrates the greatest accuracy in tasks of final diagnosis as compared to initial diagnosis. Limitations include possible model hallucinations and the unclear composition of ChatGPT’s training data set." Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study Who is a medical doctor? Or, who is a human in society? A human is an acceptable member of society based on acts according to common agreements, learned by the person. A medical doctor is a professional who is formally trained with established knowledge in medicine. An important capability of the brain, it seems, is its ability to learn widely. Though, the property is prepared in genes, the sprawling connections of the brain that provide a broad learning ability and become expanded, makes humans dominant and exceed other organisms on the planet. Several organisms have similar biological make-ups as humans. They also possess several survival mechanisms. They do not have some of the properties for language, advanced intelligence and so forth. They are also able to learn, but their ability to learn does not match humans. This is obvious by the difficulty for some domesticated animals to recognize certain familiar stuff in another form sometimes, like a known person in a picture or video, or to get the concept of what devices are so forth. Learning is one of the ways the human brain broke from other organisms, even though humans still have to fulfill their biological needs. This learning, though limited, has changed society in places and over eras. There are relays in the brain that alter how what was learned is accessed for many, enabling how things are seen in another way from usual, pivoting towards advances. The learning superiority of the human brain now seems threatened, if not displaced already by LLMs. There are people who play up, and others who downplay, LLMs, they may be right or wrong. What LLMs should be measured against is what the brain does, in terms of the need for people in several purposes. LLMs predict the next word, which is a form of output of their learning of the likelihood of what that word should be. Sometimes they are accurate, other times they are not. They have, however, been able to crossover into key doings in human society, like in medicine, as the paper showed. There are areas where human intelligence is limited, like learning new languages for many adults, or some complex subjects or taking on a fresh field to becoming an expert. In these, LLMs excel, plus they are not given to variations of pleasure or pain, of human consciousness. How does the human brain learn? The two most prominent components in that process are the electrical and chemical impulses of nerve cells. These components, their features and interactions are proposed to be the human mind. Conceptually, as sets of electrical impulses interact with sets of chemical impulses, there are fills that occur in the loop of sets of chemical impulses that ensure that something is learned. There are other features of sets of impulses that may influence the reach of the fills, making learning easy or hard, depending. Since impulses are also involved in other processes, aside learning and only one interaction is prioritized on the mind in a moment, it is generally difficult to do so much, in general. For humans, modeling learning by sets of impulses, in a way towards reshaping education, in adulthood or rearing children could help to counter some of the strengths of AI, to displace lots of people.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

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