the OCR conjecture: some examples include artifacts such as OCRV ROOT, which indicate the training data may have been reading between the lines: OpenAI is scanning books (for some reason the model loves mentioning how many deaf people live in Malaysia)
@jxmnop
-
Multilingual Reasoning Chains in Neural Language Models
By
–
what you can't see from the map is many of the chains start in English but slowly descend into Neuralese the reasoning chains happily alternate between Arabic, Russian, Thai, Korean, Chinese, and Ukrainian. then usually make their way back to English (but not always)
-
Model Hallucinates Domino Problem Repeatedly in Token Loop
By
–
and it truly is a tortured model. here the model hallucinates a programming problem about dominos and attempts to solve it, spending over 30,000 tokens in the process completely unprompted, the model generated and tried to solve this domino problem over 5,000 separate times
-
Embedded Generations: AI Model Capabilities in Math and Code
By
–
here's a map of the embedded generations the model loves math and code. i prompt with nothing and yet it always reasons. it just talks about math and code, and mostly in English math – probability, ML, PDEs, topology, diffeq
code – agentic software, competitive programming, -
GPT-OSS Training Data Analysis: Bizarre Results Revealed
By
–
curious about the training data of OpenAI's new gpt-oss models? i was too. so i generated 10M examples from gpt-oss-20b, ran some analysis, and the results were… pretty bizarre time for a deep dive
-
GPT-5 Scaling Laws: Diminishing Returns on General Intelligence
By
–
shortest explanation of GPT-5: this is exactly what the scaling laws predicted! the model is better, the returns are diminishing, and sadly absolute general intelligence improvements will only get smaller the good news is there’s so much still to do. personality, reasoning,
-
Four Years Minimum Wage Career Path Challenges
By
–
no, it requires four years of minimum wage and perpetual headache
-
PhD holders unlikely to produce flawed data visualizations
By
–
if they have a phd then there’s no way they would’ve made this graph after two phds
-
PhD-level rigor in data visualization and research standards
By
–
people arent gonna wanna hear this but i truly do not believe this mistake could’ve been made by someone with a phd. after going through brutal peer review several times you just stop doing stuff like this. whoever made this graph clearly has a bachelors degree. maybe a masters