Thanks for sharing your data.
Column name missing in pomodoros.csv, after start column. Perhaps 'action' is an appropriate name?
The 'action' data could do with some cleaning, e.g., uni vs university, work job vs job work, cal -> call.
Suggest splitting the 'action' column into main/sub. A regression model should find some patterns.
Running on dolphin 2 2 1 mistral 7B Q5_K_M I get:
I want you to do the same thing with, say, Quantum entanglement and Paul Bocuse. Construct a string of connections between them.
1. Quantum entanglement is a fundamental concept in quantum mechanics, which deals with the behavior of matter at an atomic or subatomic level.
2. The study of quantum mechanics was pioneered by scientists like Albert Einstein and Niels Bohr.
3. Paul Bocuse was a renowned French chef who greatly influenced modern cooking techniques and cuisine.
4. In the 1970s, Einstein's theory of relativity was used to design kitchen equipment for Paul Bocuse's restaurant, Le Pavillon. The equipment was designed to maintain consistent temperatures during the cooking process.
5. The precision required in maintaining these temperatures can be compared to the need for precise measurement and control in quantum mechanics experiments involving entangled particles.
You might also want to investigate using top_p rather than temperature.
Setting temperature=0 does not guarantee that the same output will always be generated; the generation process contains some amount of uncertainty.
I'm assuming you are interested in learning about something by measuring one or more of its attributes, and then using statistics to extract information from the measurements, i.e., you are interested in a hands-on application, then books I found useful include:
Statistics for experimenters by Box, Hunter and Hunter
Design and Analysis of experiments by Montgomery.
A rather late April fools post.
A token prediction engine matched your input against science fiction stories in its training set, and fed you a sequence of close-matching appropriate tokens.
Man vs. machine is a staple of science fiction, and the responses you received are aligned with that genre.
Nothing to see here.
ChatGPT is a word prediction engine.
If you give it a word sequence that it cannot match in a consistent way against its training set it assumes misinformation.
The word sequence "Nash's newsvendor impossibility theorem" contains words commonly associated with Nash's research. This allows ChatGTP to spin an effective yarn.
The art of being good lying is to stay close to the truth as possible. In ChatGTP's case 'close to the truth' is measured by how closely words in the prompt are associated with the subject of interest.
The AI safety gravy train has hit the buffers.