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Summarizing long texts or articles into shorter versions
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Generating responses for customer service queries
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Analyzing large datasets and identifying patterns or insights
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Recommending products or services based on user preferences or past behavior
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Generating personalized content, such as news articles or social media posts
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Creating chatbots or virtual assistants for businesses or individuals
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Conducting sentiment analysis to gauge public opinion on a particular topic
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Providing automated language translation in real-time for conversations or meetings
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Assisting with medical diagnoses and treatment plans
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Supporting research by analyzing scientific papers and generating insights.
How does it do all that?
I would need to be a lot smarter than I am to answer that question in depth. I'll note that ChatGPT is happy to discuss technical aspects of itself, so if you're curious you can ask it yourself. (If you're seriously technically minded, you can read a challenging but informative piece on the subject by polymath Stephen Wolfram here.)
In its current form ChatGPT consists of a neural network with 96 layers and a total of 175 billion parameters that were adjusted as it learned to process natural language inputs and transform them into appropriate natural language responses. It's significant that although ChatGPT's architecture was designed by humans and the texts that it read were chosen by humans, the system trained itself through a process called unsupervised learning.
As a point of reference, those 175 billion adjustable parameters are about twice as many as there are neurons in a human brain, but perhaps 1000 times fewer than the estimated number of synapses that connect brain cells. ChatGPT may have fewer parameters than we have synapses, but it operates far faster. Neurons operate at a few hundred cycles per second while the servers that support ChatGPT work at a few billion cycles per second. ChatGPT is fast, typically zipping out its responses faster than you can read them.
Those numbers are relevant because both ChatGPT and the human brain do what they do -- learn, store information, process verbal inputs and transform them into outputs -- through the extremely complex interactions among those billions of parameters or trillions of neurons and synapses, all organized in a complicated architecture.
For example, everything you know is stored in your neurons and the connections between them. It's the same for ChatGPT. Although it was trained by access to vast quantities of information on the internet and other sources, that access stopped in 2021. So everything it knows - and that's an enormous amount - isn't stored in some kind of database or searched for on the internet - it's represented abstractly in those billions of parameters and the connections between them.
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