Kaj Bostrom
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bostromk.net
Kaj Bostrom
@bostromk.net
I hate slop and yet I work on generative models
PhD from UT Austin, applied scientist @ AWS
He/him • https://bostromk.net
"blah blah blah user noises blah blah"
November 29, 2025 at 7:50 PM
sloppy automation makes it easy to drift into an anti-automation stance even for folks who care more about utility than principle (although i don't count myself as one)
November 27, 2025 at 9:11 PM
My hackles go up when people or agents push bad code obfuscated by misleading "polish signifiers" like comments or defused unit tests. I have a feeling that current quality issues like these are leading folks to build negative preconceptions about future systems
November 27, 2025 at 9:06 PM
This is so important
November 23, 2025 at 9:17 AM
*freeks
November 22, 2025 at 6:21 PM
grindset
November 3, 2025 at 4:13 PM
low level improvements to information capacity of attention are needed to make this possible. Context rot currently makes icl useless for tasks over a certain level of complexity, much lower than what can fit in context by token volume
October 23, 2025 at 5:22 PM
lol @ GFYPO
October 2, 2025 at 10:03 PM
Over on the other app @jessyjli.bsky.social pointed out some countervailing results in arxiv.org/abs/2501.00273
and arxiv.org/abs/2407.00211, using structural rather than lexical similarity to measure diversity
Echoes in AI: Quantifying Lack of Plot Diversity in LLM Outputs
With rapid advances in large language models (LLMs), there has been an increasing application of LLMs in creative content ideation and generation. A critical question emerges: can current LLMs provide...
arxiv.org
August 12, 2025 at 5:38 PM
Reposted by Kaj Bostrom
As our main result, we find that when a token is in a model’s vocabulary—i.e., when its characters are tokenised as a single symbol—the model may assign it up to 17x more probability than if it had been split into two tokens instead
June 5, 2025 at 10:43 AM
culture and cognition
May 3, 2025 at 12:55 PM
being defeasible and malleable >>>>>
May 2, 2025 at 6:25 PM
$440m isn't the end of the world but it's a nice example of people giving an algorithm power and then learning that it's broken slightly too late
December 28, 2024 at 7:58 PM
Yes, in a world where it's working as intended, but see e.g. www.bbc.com/news/magazin... for an example of when that fails to hold
High-frequency trading and the $440m mistake - BBC News
Computers and clever maths enables traders to buy and sell in the blink of an eye. But does high-frequency trading make things worse when things go wrong?
www.bbc.com
December 28, 2024 at 7:48 PM
Again, not "meaningful work" per se but definitely decisions with material consequences
December 28, 2024 at 2:19 AM
High-frequency trading is another established case where people choose to cede decision-making to machines - in this case directly in service of aforementioned "market forces"
December 28, 2024 at 2:17 AM
what the hell they're cracked
December 25, 2024 at 5:37 PM
fickle gill strikes again
December 23, 2024 at 5:07 AM
Love the title
December 20, 2024 at 6:38 PM
/families of environments
December 14, 2024 at 3:13 AM
Pretraining in open-ended environments!!
December 14, 2024 at 3:12 AM
*and/or
December 13, 2024 at 2:58 AM
Or bulk acting as reservoir
December 13, 2024 at 2:57 AM
Had a very similar experience Tues. Sending coal-train-banishing prayers
December 12, 2024 at 6:43 AM
ouches
December 6, 2024 at 4:48 AM