Makes me think of that part in Philip K. Dick's Do Androids Dream (..) -- where Deckard reflects on the androids' indifference to their imminent deaths, saying that this was due to them lacking the aversion to death acquired trough evolution.
100%.
Companies are paperclip optimizers, with money as the objective.
For example, Uber used ride data to circumvent investigations by regulators.
There is absolutely no reason to assume that AI companies would not use their data in any way possible to reach their objectives.
The real "nightmare" is the browser that will automatically run all that garbage returned in the response body without any input from the user
It requires an "adblocker" to stop its default behaviour
Alternatively, one needs to disable Javascript, restrict the browser's access to DNS, etc.
When an advertising company releases a "browser" that intentionally allows website operators to cram pages fuil of advertising and tracking is that a coincidence
Is that the only way a browser can be designed
No
How many users realise this
A small number
For example, I'm using a browser that cannot automatically request resources, run Javascript, CSS, etc. where HTTP headers, including cookies, are trivial for the user to create, edit, save and delete. I do not need an "adblocker"
"Don't these sites realise how many users they're losing?"
ChatGPT is the only bot that reliably cites sources (through Web search mode).
The other bots either make up links or simply don't provide any information that is distinguishable from the LLM predictive output.
Ironically Gemini is also very bad at this, while it should have been the best at Web search.
Gemini also does something very patchy, which is to provide "links" which are in fact GET queries into classic Google search. I'm guessing they did it this way because the links generated/hallucinated by the LLM were too unreliable.
I think there's a few things, but its a little subjective and its more about the style the ai uses when doing these than the actual specific behavior:
- Nuggesting improvements to the code after finishing the task you gave it, very irritating when the improvements were obvious and the ai didn't implement them on its own
- Not trying very hard when implementing something, leading to bugs, which leads to more tokens used (this behavior can be incentivized and learned with RL)
Since its a known fact if a user continues a session after the LLM says something, its not hard to train against this. The least efficient way to do this would be to GPRO directly against the user base and try to get as many people talking to the AI, and with OAI having a billion monthly active users the least efficient method would work really well for them.
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