#conversation #ai #programming
# [[Epistemic status]]
#shower-thought #to-digest
# Changelog
```dataview
TABLE WITHOUT ID file.mtime AS "Last Modified" FROM [[#]]
SORT file.mtime DESC
LIMIT 3
```
# Related
# TODO
> [!TODO] TODO
# Modern programming is all about low entropy conversation starters
%%Robots swimming in the cosmos, a paradox by Escher%%
![[6fab6805-420d-4f90-a456-3204eb7e261f-0-1999251307.png]]
This is a bunch of my code:
```py
# turn the topics column into a list by splitting on commas
tweets_df["Topics"] = tweets_df["Topics"].apply(lambda x: x.split(","))
tweets_df
from sentence_transformers import SentenceTransformer, util
# split dataset into a map of sets of topics per user
topics_per_user = {}
for k, v in tweets_df.iterrows():
user = v["User"]
if user not in topics_per_user:
topics_per_user[user] = set()
for e in v["Topics"]: topics_per_user[user].add(e)
# common topics
common_topics = topics_per_user["louis030195"].intersection(topics_per_user["naval"])
print(f"Common topics: {common_topics}")
# compute the average embedding per user
user_embeddings = {}
for user, topics in topics_per_user.items():
user_embeddings[user] = model.encode([", ".join(topics)])
# compute the cosine similarity between the embeddings
cosine_scores = util.pytorch_cos_sim(
user_embeddings["louis030195"], user_embeddings["naval"]
)
print(f"Similarity score: {cosine_scores}")
```
Basically modern [[Programming|programming]] is all about write simple prompts as comment to be completed.
It's like when you are a [[CTO]], you do the fundamental thinking, the initial prompt, then there is the implementers that create your vision.
![[fcd7b050-cc91-46c9-9ff3-d65be768b7c7-0-2474395583.png]]
This is where the world is heading toward, [[Imaginary programming]] will let us think about prompts that are life goals and [[Artificial intelligence|AI]] will implement our dream.
"I want to be fit" -> [[Artificial intelligence|AI]] will make you do a [[Fasting|fast]]
"I want a Ferrari" -> [[Artificial intelligence|AI]] will make you generate [[Money|money]]
![[6b6f1e47-6824-4dc0-b8b6-a8b58466a9b7-0-1369856361.png]]
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