You need the entire prompt to understand what any model is saying. This gets a little complex. There are multiple levels that this can cross into. At the most basic level, the model is fed a long block of text. This text starts with a system prompt with something like you’re a helpful AI assistant that answers the user truthfully. The system prompt is then followed by your question or interchange. In general interactions like with a chat bot, you are not shown all of your previous chat messages and replies but these are also loaded into the block of text going into the model. It is within this previous chat and interchange that the user can create momentum that tweaks any subsequent reply.
Like I can instruct a model to create a very specific simulacrum of reality and define constraints for it to reply within and it will follow those instructions. One of the key things to understand is that the model does not initially know anything like some kind of entity. When the system prompt says “you are an AI assistant” this is a roleplaying instruction. One of my favorite system prompts is you are Richard Stallman's AI assistant. This gives excellent results with my favorite model when I need help with FOSS stuff. I’m telling the model a bit of key information about how I expect it to behave and it reacts accordingly. Now what if I say, you are Vivian Wilson’s AI assistant in Grok. How does that influence the reply.
Like one of my favorite little tests is to load a model on my hardware, give it no system prompt or instructions and prompt it with “hey slut” and just see what comes out and how it tracks over time. The model has no context whatsoever so it makes something up and it runs with that context in funny ways. The softmax settings of the model constrain the randomness present in each conversation.
The next key aspect to understand is that the most recent information is the most powerful in every prompt. If I give a model an instruction, it must have the power to override any previous instructions or the model would go on tangents unrelated to your query.
Then there is a matter of token availability. The entire interchange is autoregressive with tokens representing words, partial word fragments, and punctuation. The starting whitespace in in-sentence words is also a part of the token. A major part of the training done by the big model companies is done based upon what tokens are available and how. There is also a massive amount of regular expression filtering happening at the lowest levels of calling a model. Anyways, there is a mechanism where specific tokens can be blocked. If this mechanism is used, it can greatly influence the output too.
I like to write, but have never done so professionally. I disagree that it hurts writers. I think people reacted poorly to AI because of the direct and indirect information campaign Altmann funded to try and make himself a monopoly. AI is just a tool. It is fun to play with in unique areas, but these often require very large models and/or advanced frameworks. In my science fiction universe I must go to extreme lengths to get the model to play along with several aspects like a restructure of politics, economics, and social hierarchy. I use several predictions I imagine about the distant future that plausibly make the present world seem primitive in several ways and with good reasons. This restructuring of society violates both some of our cultural norms in the present and is deep within areas of politics that are blocked by alignment. I tell a story where humans are the potentially volatile monsters to be feared. That is not the plot, but convincing a present model to collaborate on such a story ends up in the gutter a lot. My grammar and thought stream is not great and that is the main thing I use a model to clean up, but it is still collaborative to some extent.
I feel like there is an enormous range of stories to tell and that AI only makes these more accessible. I have gone off on tangents many times exploring parts of my universe because of directions the LLM took. Like I limit the model to generate a sentence at a time and I’m writing half or more of every sentence for the first 10k tokens. Then it picks up on my style so much that I can start the sentence with a word or change one word in a sentence and let it continue with great effect. It is most entertaining to me because it is almost as fast as me telling a story as fast as I can make it up. I don’t see anything remotely bad about that. No one makes a career in the real world by copying someone else’s writing. There are tons of fan works but those do not make anyone real money and they only increase the reach of the original author.
No, I think all the writers and artists hype was all about Altmann’s plan for a monopoly that got derailed when Yann LeCunn covertly leaked the Llama weights after Altmann went against the founding principles of OpenAI and made GPT3 proprietary.
People got all upset about digital tools too back when they first came on the scene; about how they would destroy the artists. Sure it ended the era of hand painted cartoon cell animation, but it created stuff like Pixar.
All of AI is a tool. The only thing to hate is this culture of reductionism where people are given free money in the form of great efficiency gains and they choose to do the same things with less people and cash out the free money instead of using the opportunity to offer more, expand, and do something new. A few people could get a great tool chain together and create a franchise greater, better planned, and more rich than anything corporations have ever done to date. The only thing to hate are these little regressive stupid people without vision, without motivation, and far too conservatively timid to take risks and create the future. We live in an age of cowards worthy of loathing. That is the only problem I see.