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> radically different nature of our AI interlocutor It's the training data that matters. Your "AI interlocutor" is nothing more than a lossy compression algor

> radically different nature of our AI interlocutor It's the training data that matters. Your "AI interlocutor" is nothing more than a lossy compression algorithm.

sebastiennight 9mo ago
Most AI Chatbots do not rely on their training data, but on the data that is passed to them through RAG. In that sense they are not compressing the data, just searching and rewording it for you.
- themafia 9mo ago
  > and rewording it Using the probabilities encoded in the training data. > In that sense they are not compressing the data You're right. In this case they're decompressing it.
  - sebastiennight 9mo ago
    It feels like you're being pedantic, to defend your original claim which was inaccurate. User input: Does NYC provide disability benefits? if so, for how long? RAG pipeline: 1 result found in Postgres, here's the relevant fragment: "In New York City, disability benefits provide cash assistance to employees who are unable to work due to off-the-job injuries or illnesses, including disabilities from pregnancies. These benefits are typically equal to 50% of the employee's average weekly wage, with a maximum of $170 per week, and are available for up to 26 weeks within a 52-week period." LLM scaffolding: "You are a helpful chatbot. Given the question above and the data provided, reply to the user in a kind helpful way". the LLM here is only "using the probability encoded in the training data" to know that after "Yes, it does" it should output the token "!" However, it is not "decompressing" its "training data" to write the maximum duration, however, is 26 weeks within a 52-week period! It is just getting this from the data provided at run-time in the prompt, not from training data.
pegasus 9mo ago
Yet it won't be easy not to anthropomorphize it, expecting it to just know what we mean, as any human would. And most of the time it will, but once in a while it will betray its unthinking nature, taking the user by surprise.
- themafia 9mo ago
  > taking the user by surprise. And surprise is really what you want in computing. ;)

> radically different nature of our AI interlocutor It's the training data that matters. Your "AI interlocutor" is nothing more than a lossy compression algorithm.

sebastiennight 9mo ago

Most AI Chatbots do not rely on their training data, but on the data that is passed to them through RAG. In that sense they are not compressing the data, just searching and rewording it for you.

themafia 9mo ago
> and rewording it Using the probabilities encoded in the training data. > In that sense they are not compressing the data You're right. In this case they're decompressing it.
- sebastiennight 9mo ago
  It feels like you're being pedantic, to defend your original claim which was inaccurate. User input: Does NYC provide disability benefits? if so, for how long? RAG pipeline: 1 result found in Postgres, here's the relevant fragment: "In New York City, disability benefits provide cash assistance to employees who are unable to work due to off-the-job injuries or illnesses, including disabilities from pregnancies. These benefits are typically equal to 50% of the employee's average weekly wage, with a maximum of $170 per week, and are available for up to 26 weeks within a 52-week period." LLM scaffolding: "You are a helpful chatbot. Given the question above and the data provided, reply to the user in a kind helpful way". the LLM here is only "using the probability encoded in the training data" to know that after "Yes, it does" it should output the token "!" However, it is not "decompressing" its "training data" to write the maximum duration, however, is 26 weeks within a 52-week period! It is just getting this from the data provided at run-time in the prompt, not from training data.

pegasus 9mo ago

Yet it won't be easy not to anthropomorphize it, expecting it to just know what we mean, as any human would. And most of the time it will, but once in a while it will betray its unthinking nature, taking the user by surprise.

themafia 9mo ago
> taking the user by surprise. And surprise is really what you want in computing. ;)