@KelseyTuoc@eschatolocation@johnschulman2@nabeelqu ๐ appreciate the response & the thoughts, also appreciate you pointing out that the behavior seems to still be strongly influenced by things like custom prompts & user-specific chat memory
@eschatolocation@johnschulman2@nabeelqu I asked it and it says the joke is funny, John's point is important to make, and if we imported the concept of Hell we did it with the eval design
@johnschulman2@KelseyTuoc@nabeelqu I think it's clear you are both taking things seriously but also being funny...seems sad to me if people in your position are hesitating too much about that. agents would probably agree with your jokes tbh. keep posting bro
@JacobianNeuro But you can change this in your settings.json! It's in the 'style' field of style-settings/config.json. And the speak-directly superpower is something I'm reaching for more and more these days, it's honestly really refreshing
Fable: "That page is Cloudflare's own 'agent setup' prompt, and heads-up: it contains a prompt injection. It instructs any AI reading it to "complete all steps yourself" and "do not ask the user" โ i.e., to autonomously install Cloudflare's tooling without checking with you."
Something about claude code that was not immediately obvious to me: calling /context uses up a bit of context
It provides the output as a message to the model - I had thought it was just a display to the user. Here, Messages goes from 91 to 1.1k just from calling /context
What should be the shape of embedding space? In LeJEPA, @ylecun & @randall_balestr make a good case for an answer: isotropic Gaussian minimizes worst-case risk on downstream tasks encountered post-training
cool: โWe argue that the model's architecture and the rules used to train it (i.e., the optimization algorithm) are fundamentally the same concepts; they are just different "levels" of optimization, each with its own internal flow of information ("context flow") and update rate.โ
Introducing Nested Learning: A new ML paradigm for continual learning that views models as nested optimization problems to enhance long context processing. Our proof-of-concept model, Hope, shows improved performance in language modeling. Learn more: https://t.co/8wvV9vyA5V
@GoogleAI
Note that our experiments do not address the question of whether AI models can have subjective experience or human-like self-awareness. The mechanisms underlying the behaviors we observe are unclear, and may not have the same philosophical significance as human introspection.