lumi retweeted
It’s worthwhile to play through in your mind the kinds of motivated reasoning and self-deception that might have led academics to work on this project.
It’ll help you understand better what’s going on at AGI companies.
Purdue University's IDEAS Lab built an autonomous drone that tracks runners through dense forests completely without GPS or cloud networks.
By running 3D LiDAR mapping and obstacle-avoidance AI entirely on-chip, it can weave under tree canopies and predict target movement through blind spots in real time.
Massive implications for next-gen search & rescue and edge AI.
lumi retweeted
In general, many interp and alignment results might not hold up on current frontier architectures, and researchers should be pushing for more transparency from labs to allow for open science.
PSA to everyone doing neuron interp after the recent monosemantic neuron posts: the model's training recipe matters a lot.
e.g. GPT2 seems to have been trained WITH dropout (modern LLMs are not), which seems to increase redundancy and (maybe) polysemanticity but reduce superposition (see sources in comments).
Other choices probably also have an effect (e.g. SwiGLU vs GELU MLPs, optimizer, amount of weight decay, etc.) and I think we should be careful not to generalize too much.
Currently working on a project to characterize the effects of these choices on neuron interpretability (a lot of the existing work is done on older/toy models which I'm not sure are representative), feel free to reach out if interested!
we need a term in between grug tech and gorm fluid for machine learning models that haven't seen a language token in their life
THREAD!
saw very sus ollama endpoints
every endpoint analyzed advertises a model: "agent-id-chris-0928". metadata incl "owner=chris agent=hermes-mac"
365 of 375 endps report model changes within 06:54–06:57 UTC on Sep 29. server-reported timestamps suggest coordination. 1/🧵
many of these are serving 27b+ qwen variants, and some are serving larger GLM and deepseek models, which could be used maliciously
in addition, ollama's /api/pull endpoint is unauthenticated, so an actor could cause any model that would fit on the hardware to be downloaded
i've been monitoring a population of unsecured Ollama and llama.cpp servers on the open internet, using their public metrics endpoints, and observed a spike in model residency last night (maybe an automated scanning campaign)
cause for hope
Replying to @ApolloResearch
GLM-5.3 reasons that a misaligned action taken during training could be reinforced and make similar actions more likely later. It also considers what kind of agent it wants to be in the future, and factors this into how it should act. We call this "update-aware reasoning".
it's cool how google maps just randomly hides stops on your bus line from the map if it decides you're not zoomed in enough
hypothesizing the existence of too high sensory noise floor autism and too low sensory noise floor autism
I do not want an eternal cosmic parent.
Replying to @zetalyrae
I think if we miraculously manage to align AGI and it basically treats us like eternal children that could work out to be fine
a responsible enough AGI mother would also respect our desires for meaning and autonomy and find a way to provide that
















