There is a major misunderstanding in the general public and especially in the news about what ChatGPT really does. This misunderstanding is not really new, there has been confusion about ML techniques for a long time.
Imho a large part of the issue comes from the term "Artificial Intelligence", which covers everything in this area supposed to represent some form of intelligence. Clearly most people would like to believe that there is some real intelligence at play (sci-fi, etc.). The fact that many companies or institutions have an interest in keeping the ambiguity alive (e.g. "smart cars", "smart home", etc.) and that some experts support it greatly contributes to the confusion.
But as far as I know, from the point of view of ML experts, a system like ChatGPT is more like a highly complex calculator than an intelligence.
Its calculations cannot be simulated manually (well technically they can, but it would take a lot of people and a very long time) so it gives the impression of something smart. It's also worth noting that the evolution of ML has been to give less and less direct human supervision to the models, i.e. they have more autonomy in which way and what they learn.
What this kind of system is trained to do is to simulate giving an answer. The more the answer looks real, the better. It is not trained to give a correct answer or give any importance to the truth, because this is not easily measurable. The Chinese Room argument explains why such a system does not comprehend anything of what it says, it just applies a lot of complex rules/calculations based on its training. One could say that the goal of a system like ChatGPT is to create the illusion that there is some intelligence behind it, like the goal of a magician is to make you believe whatever they are showing.
As a consequence, it is well known that ChatGPT answers are meaningless in general: see for instance this article or the ban on StackExchange.
I have been checking organic and inorganic chemistry skills in ChatGPT pro and it is absolutely, laughably bad. But it sounds good, plausible but it comically wrong in so many ways.
Maybe you should think twice about whether the health issues advice it is giving you is legitimate.
Why would you trust ChatGPt about facts in the first place?
And as for product recommendations it's really generic.
what is the best camera?
As an AI language model, I do not have personal preferences, opinions, or biases. However, I can provide you with some information on what makes a good camera.
The "best" camera for you depends on your specific needs and preferences. Different cameras are designed for different purposes, such as professional photography, vlogging, or travel photography. Some factors to consider when choosing a camera include:
Image quality: The camera's sensor size and resolution can affect the quality of the images.
Lens selection: The availability of interchangeable lenses can enhance the versatility of the camera.
Size and weight: Consider the camera's portability if you plan on carrying it around for extended periods.
User-friendly interface: The camera should have an intuitive interface that is easy to use.
Battery life: Consider how long the camera can last on a single charge.
Price: The price of a camera is an important factor to consider.
Some popular camera brands that are known for producing high-quality cameras include Canon, Nikon, Sony, Fujifilm, and Panasonic. It is important to do your research and read reviews to find the camera that best fits your needs and budget.
(author here) yeah and honestly i had them higher when i first made my initial estimate of ChatGPT paying user numbers + enterprise. i think its a monster and probably undervalued at a 29b valuation.
OAI through their API probably does but I do agree that ChatGPT is not really Enterprise product.For the company the API is the platform play, their enterprise customers are going to be the likes of MSFT, salesforce, zendesk or say Apple to power Siri, these are the ones doing the heavy lifting of selling and making an LLM product that provides value to their enterprise customers. A bit like stripe/AWS. Whether OAI can form a durable platform (vs their competitors or inhouse LLM) is the question here or whether they can offer models at a cost that justifies the upsell of AI features their customers offer