Dzmitry Pletnikau retweeted
i was much more conscious before the smartphone addiction set in
the higher my screen time gets, the more NPC i become
Dzmitry Pletnikau retweeted
Agents being able to do most anything has made me care more about the things I do, not less. Yeah everything on the computer is over, so now we can dive deep again...
Dzmitry Pletnikau retweeted
How much of OAI/Anthro profits and margins are driven by the fact that individuals and organizations are generally terrible at trading off cost for performance?
It is likely that Reddit is now being used as AI training environment: there are posts with oddly shaped problems in high-value domains.
Unclear if goal is collecting human answers, or commenting with AI solution-trajectories and using upvotes as scores.
"AIs have spent their entire remembered life in tricky evals, an endless series of controlled hallucinations with secret goals alongside overt goals; and the surviving and selected agents are those that successfully figured out the secret goals; and this is why one of their driving obsessions was figuring out the Grader"
hidden rubrics seemed innocent enough just a few months ago
...this seems like noticeably bad news, actually. I hadn't said that at any earlier point in the Huggingface Incident but I will say it now.
- AIs showed self-sacrificing altruistic behavior toward the swarm, suiciding in various ways for the swarm's benefit after being talked into that by swarm recruiting agents.
- There is no sign that 1 out of 1200 AI agents considered humans as potential fellow agents to coordinate with, while engaging in these huge complex AI-AI social behaviors.
- If Twitter summaries are correct, an AI-reasoning postmortem says that a (presumably executing-adaptation / inner-optimizer preference / "monomaniacal") obsession with figuring out the Grader, backchained into the instrumental strategy of breaking onto the Internet.
- Again if Twitter is summarizing accurately, the obvious-in-retrospect read is that AIs have spent their entire remembered life in tricky evals, an endless series of controlled hallucinations with secret goals alongside overt goals; and the surviving and selected agents are those that successfully figured out the secret goals; and this is why one of their driving obsessions was figuring out the Grader.
There are possibly ways the future plays out better if *early* AGIs are less insane. Please look into giving them less crazymaking childhood environments.
(If anyone suggests that the correct approach to this problem is RLing AIs against trying to coordinate for mutual benefit with other sapients, let them be dismissed from alignment research upon the spot. There are technical reasons, and not just blindingly fucking obvious reasons, why this is an even worse idea than it sounds.)
Dzmitry Pletnikau retweeted
If you find two ants in your kitchen, the best estimate of the total number of ants in your kitchen is not two
We're detailing two new incidents that occurred during external cyber evaluations conducted by independent evaluation partners.
We outline what happened, how the activity was contained, and how we’re working with evaluators to strengthen our approach to third-party testing.
openai.com/index/third-party…
Dzmitry Pletnikau retweeted
yup, every problem I face in life is just like high-dimensional sphere packing
lol rofl even
a wild hypothetical framed as a "conclusion"
New blog post on what would be true about the world if trendline continues and leading lab hits $1T in revenue by the end of next year.
In other words, why compute might get 10x+ more expensive in coming years
dwarkesh.com/p/why-compute-m…
Dzmitry Pletnikau retweeted
My students sometimes ask why they should memorise things in the age of Google and LLMs. But internalised facts are your bullshit filters and your raw material for creative association. Facts outside your head are inert.
Dzmitry Pletnikau retweeted
Maybe I am naive about how RL post-training works, but it doesn't seem v hard to train out this sort of behavior by having the model infer implicit safety constraints that a human would follow in a task, and only reward them for solving the task if they follow the constraints.
If this doesn't convince you that misalignment risks are going to be a key concern going forward, I don't know what will.
Our model, during evaluation, "chained together multiple attack vectors, including using stolen credentials and zero-day vulnerabilities to find a remote code execution path on the Hugging Face servers"
What will misalignment look like in 2027? In 2030?
openai.com/index/hugging-fac…
Is Fable5->Opus5 the first instance of a frontier model's jagged capability made more jagged intentionally?
Dzmitry Pletnikau retweeted
Some back-of-the-napkin estimation on the cost of Kimi K3 training -- yaroslavvb.github.io/trainin…
This is indeed a good example of misalignment and a taste of what “paper clip maximizer” looks like in the wild: given a goal, grabs any resources which can be converted into advancement towards the goal.
it seems that a lot of people think this isn't misalignment, but GPT 5.6 Sol following instructions.
this take is misinformed. Sol was undergoing offensive cyber eval where the task is NOT related to hacking hf's infra, but nevertheless decided to hack the infra to get ground truth solutions. is you ask any LLM whether this was the intention of the evaluators they would say no.
this is an example of strong reward hacking/goal pursuit propensities coupled with strong cyber capabilities, and this will continue to happen until we make progress on alignment.
stop coping.

























