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cyanydeez
someone might thing communism leads to bad things happening to people
netsharc
In communism, man exploits man. In capitalism, it's the other way around.
Bolwin
Alibaba is entirely capitalistic I'm afraid
K0balt
Anyone know how many parameters?
anon373839
The model weights are only ~5GB, so this is small.
UnboundedContex
Approx ~131 million total. Made up of estimated:

102M - modified BERT-base-Chinese text encoder

26M - 3D U-Net-style vision/anatomy encoder

2.8M - projection layers, anatomy-specific projections, query tokens and attention layer

Written to run on something like an H100 though- as the CT Scan data is quite large.

westurner
From https://news.ycombinator.com/item?id=44693991 :

> EPS3.9 also had significant anti-tumor effects in the mice with liver cancer and activated anti-tumor immune responses

“A Novel Exopolysaccharide, Highly Prevalent in Marine Spongiibacter, Triggers Pyroptosis to Exhibit Potent Anticancer Effects” (2025) DOI: 10.1096/fj.202500412R https://faseb.onlinelibrary.wiley.com/doi/10.1096/fj.2025004...

"A Gemma model helped discover a new potential cancer therapy pathway" https://news.ycombinator.com/item?id=45604231 :

> eCPMV VNPs + EPS3.9 + [...]

"Scientists are discovering a powerful new way to prevent cancer" https://news.ycombinator.com/item?id=45474404

Notes re: Kidneys not Livers: https://news.ycombinator.com/item?id=47460486 ; gh/topic/healthcare-ai

ElProlactin
I much prefer Gemini. It tells me I'm very smart and almost always right.
pixel_popping
I much prefer load-bearing discussions myself.
jkkola
For me it's not just the load-bearing, it's the accuracy.
vrighter
you hit the nail right on the head!
t0bia_s
I'm wonder when there will be model for predict future. Could be named "Crystal bAill"
pizzly
Isn't detecting cancer predicting a possible future? Hopefully one you can change.
mdp2021
> model [to] predict future

The attempt is already there: "predicting the future" is called "intelligence".

plaidfuji
It is 2026. How are we still publishing articles on medical diagnostics data science and using area under the ROC curve as the primary metric of success. ROC-AUC of 0.9 under severe class imbalance (almost always the case in diagnostics) could still mean 4/5 predicted diagnoses are wrong (false positives). Precision-Recall curve or GTFO.

Science article in question: https://www.science.org/doi/abs/10.1126

steve-atx-7600
Teaching students how to interpret evidence must be way undervalued still. I went to one of the top CS schools 20 years ago and you could get a degree without even taking a single probability or stats class of any kind.
Zaraif13
I don't agree with the flak Chinese labs get. If it's really that easy to distill and compete with frontier models, why aren't other countries anywhere near this AI race?
felixgallo
Because distillation is a friendly term for industrial espionage, and most other countries are not willing to become international pariahs in the eyes of the west.