merkleforest
Re:Open-weight 27B hits 38% on Terminal-Bench 2.0 (Opus 4.1 hit 38% in...
on Tuesday April 28, 2026 @05:10PM (#47940829)
> 2. How local use feels in practice
Do we have stats on how does the models do on Mac M-series chips?
Re:Netflix's Metaflow: Reproducible machine learning pipelines
on Monday December 21, 2020 @03:43PM (#25499333)
It would be great if the infra layer can provide some help on automated resource scaling, especially for RAM. The ML solver/tooling layer has also been making progress on this front, for example Dask for limited-RAM pandas, h2o.ai has limited RAM solvers, xgboost has an external memory version, pytorch/tensorflow models are mostly trained on SGD and only needs to load data batch by batch. It's nice that Metaflow can integrate with any python code and thus benefit from all of the efforts made on the solver/tooling layer.
Re:Launch HN: Snark AI (YC S18) – Distributed Low-Cost GPUs for Deep ...
on Tuesday July 10, 2018 @05:12PM (#17502231)
Thanks for the suggestion! Snark AI will offer a pod type with all fast.ai course dependencies installed and easy jupyter notebook access.
Re:Launch HN: Snark AI (YC S18) – Distributed Low-Cost GPUs for Deep ...
on Tuesday July 10, 2018 @12:15AM (#17495418)
It's interesting that you're drawing the comparison with NiceHash. Snark AI will be a marketplace like NiceHash but targets mostly deep learning training and inference on the user end.
Re:Launch HN: Snark AI (YC S18) – Distributed Low-Cost GPUs for Deep ...
on Tuesday July 10, 2018 @12:11AM (#17495393)
Yeah exactly. Hopefully AI computation market will grow big in time so those crypto-miners can pivot into more profitable business of GPU cloud for AI instead of selling the hardware in crypto downfall. In the long term, Snark AI wants to create the marketplace where all the qualified GPU providers can bid for the best market price which will benefit everyone.