eric15342335
Re:Prospero: A new coding harness for a more civilized age
on Saturday October 31, 2026 @09:37AM (#50316076)
How does this compare with Zed though?
Re:Ask HN: What do you run on a $5 VPS that's worth keeping online 24/7?
on Friday October 09, 2026 @02:32PM (#50024824)
Xray-core
Re:I built a demo of what AI chat will look like when it's "free" and ...
on Sunday March 01, 2026 @11:34AM (#47208174)
just kidding: will someone make a ublock filter list for this website?
Re:Gemini 3.1 Pro
on Thursday February 19, 2026 @11:47AM (#47075798)
My first impression is that the model sounds slightly more human and a little more praising. Still comparing the ability.
Re:HackMyClaw
on Tuesday February 17, 2026 @12:46PM (#47050452)
Interesting. Have already sent 6 emails :)
Re:Understanding Neural Network, Visually
on Saturday February 07, 2026 @12:30PM (#46925662)
Correct me if I am wrong, I think this is related to the term "covariate shift" (change in model input distribution x) and "concept drift".
Re:Gemini 3 Pro Model Card [pdf]
on Tuesday November 18, 2025 @10:52AM (#45967884)
Update: it is available at https://aistudio.google.com now!
Re:Nobel Prize in Physics 2025
on Wednesday October 08, 2025 @01:58PM (#45518838)
correlation is not causation
Re:Show HN: Pyscn – Python code quality analyzer for vibe coders
on Sunday October 05, 2025 @12:37PM (#45482976)
What about Pylint? iirc pylint has code duplication check as well. is it the same thing?
Re:DeepSeek-v3.2-Exp
on Monday September 29, 2025 @02:20PM (#45417031)
Not sure if I get it correctly:
They trained a thing to learn mimicking the full attention distribution but only filtering the top-k (k=2048) most important attention tokens so that when the context window increases, the compute does not go up linearly but constantly for the attention->[query,key] process (it does grow up linearly in the graph because you still need to roughly scan the entire context window (which an "indexer" will do), but just very roughly here in order to speed up things, which is O(L) here).
Re:TokenFormer: Rethinking Transformer Scaling with Tokenized Model Pa...
on Saturday November 02, 2024 @10:55AM (#42026750)
I am a university year 2 student learning about basic mathematics and statistics related to neural networks. One thing that shocks me is that there isn't an "incremental" solution for building larger (more parameters) AI models (like GPT-4) despite having one in a smaller size e.g. GPT-3.5 (I saw the term "incremental (compiling)" nearly everywhere in the software engineering industry). I am curious how is this not possible theortically?