Principal Research Scientist at IBM Research AI in New York. Speech, Formal/Natural Language Processing. Currently LLM post-training, structured SDG and RL. Opinions my own and non stationary.
ramon.astudillo.com
Ramon Astudillo
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well, fuck www.anthropic.com/news/fable-m...
Now there are three levels of alerts in generative code: errors, warnings and errors and warnings that you pass to the LLM agent and don't bother about.
The US government has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States.
There is also this: "I don't care if tokens get wasted, I am not paying for it" meme. It's not a Kombucha fountain, this is a crazy amount of money. You (plural) artificially created a hard decision once they have to think about how to balance that cost.
👆There is clear waste of tokens right now as companies figure out how to incentivize it properly and employees learn to use it better (cache lasts 5min! and planning ahead, less interactions and shorter context still do the job and is far cheaper)
This is the whole trick
Things I am using more lately:
jq for pipes and schema navigation in JSONs. You can do stuff like
head -n 1 tmp.jsonl | jq '.field[3].field2 | keys'
to see keys of deep nodes
Folding text in vim to compact TODO notes
zf zo zc
to create a fold (from visual selection), open and close it
There is this new meme out there that is something like "AI costs more than human employees". Seems like totally the wrong take. It costs much less for the things they can do, but you can't run an org w/o human employees (for now). 👇
What an amazing way to visualize early human migration. Lovely map by @HarvardCGA. A great colour scheme and an appropriate map projection! Source: buff.ly/3lbxonJ
philpax
Ramon Astudillo
Ramon Astudillo
Just FYI on Anthropic's Fable 5 fiasco.
Ramon Astudillo
LAION just released VoiceCLAP-Large-v2, a contrastive voice-text embedding model that's essentially CLIP for voice and emotion.
9B params via a rank-16 LoRA on top of LCO-Embedding-Omni-7B (itself based on Qwen2.5-Omni thinker). Apache 2.0.
🧵
