kamranjon

9 ms·

151.
by kamranjon 4mo ago
The hugging face models are already up and seem to be the original models with the speculative decoding module built in which is very cool: Flash: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-DSpark Pro: http
152.
by kamranjon 4mo ago
DeepSeek continues to not only push the boundaries but also publish these incredible papers explaining how they achieved their gains - something the American labs no longer do unfortunately. Chinese labs are doing the most interesting work
153.
by kamranjon 4mo ago
Have been thinking about this a lot lately.
154.
by kamranjon 4mo ago
I think most people running deepseek locally are using DS4: https://github.com/antirez/ds4 Which provides a 2-bit quant and a mixed 2-bit/4-bit quant - which range from 80gb to 97gb Deepseek is particularly well s
155.
by kamranjon 4mo ago
I think you’re confused - nobody running local models is concerned about SOTA - that’s just marketing hype from large providers - we are interested in data governance, security, control and freedom. You can’t compare hosted services to loca
156.
by kamranjon 4mo ago
I use it as my main coding agent - so its running DS4 server on my 128gb mbp and I run the pi coding agent on my other machine which calls out to it. Mostly Go and Typescript work. I also use it in local agent mode if im coding directly on
157.
by kamranjon 4mo ago
You’re just out of the loop, and that’s fine but it’s worth learning about. There is a pretty large and growing community of us using entirely local models for our agentic flows. From GLM 4.7 flash on 32gb machines with >60tok/s to
158.
by kamranjon 4mo ago
Oh interesting! Thanks for the context I had no idea that was a mechanic - also it seems like the mods merged it with another thread and now it’s back on the front page.
159.
by kamranjon 4mo ago
You’re out of the loop if you don’t think m series chips with unified memory aren’t one of the best platforms for running local inference
160.
by kamranjon 4mo ago
Gain some readers for… Wikipedia? I just learned about this and thought it was interesting given the current situation with RAM pricing. You’re free to draw your own conclusions.
161.
by kamranjon 4mo ago
How does something with 232 comments and 207 points over just 2 hours get pushed to the 3rd page in hacker news? I’m just really curious how it works, like why would something with so much engagement be push down so quickly?
162.
by kamranjon 4mo ago
I think one of the more ominous things to see in recent years was all of the tech execs at the presidential inauguration, after having collectively donated several million dollars to the inauguration fund. So if we go with that list, which
163.
by kamranjon 4mo ago
I really think this is a coordinated effort to restrict computing capacity for individuals and force adoption of centralized AI - I think there already is evidence of this from the moves OpenAI had made to lock up memory and gpu markets.
164.
by kamranjon 4mo ago
Damn I was considering an m5 max with 128gb just a few days ago and it was 5099 and now it’s 6699 - 1.6k increase - definitely a massive increase and has dissuaded me - this is pretty insane.
165.
by kamranjon 4mo ago
Seems possible it’s both this time: https://kotaku.com/valve-says-the-companies-making-ram-give-...
166.
DRAM Price Fixing Scandal(en.wikipedia.org)
33 points by kamranjon 4mo ago|8 comments
167.
by kamranjon 4mo ago
Yes apologies, Hackernews was just an example, you can do this with any website - it’s just a simple benchmark I like to use for testing vision models.
168.
by kamranjon 4mo ago
A fun thing I do with Qwen 3.5 0.8b is to take a screenshot of the Hackernews homepage and ask it to give me a JSON representation of the data and it does surprisingly well. With a well structured prompt I think it could be made to be pret
169.
by kamranjon 4mo ago
I have! I recently compared Gemma 1b to ModernBERT Large for a binary classification task and ModernBERT was the clear winner. It learned faster and performed the task better by a significant margin by the end of training. It seems the bidi
170.
by kamranjon 4mo ago
While you may be correct in some of these assumptions, the repo is open source, contains actual schematics and code, appears to have real community contributions, and also happens to exists now, which is something that can't be said f
171.
by kamranjon 4mo ago
thank you!
172.
by kamranjon 4mo ago
For those interested there is an open source radar based phased array project here: https://github.com/NawfalMotii79/PLFM_RADAR I may have even discovered it from hacker news, I forget now.
173.
by kamranjon 4mo ago
Can you tell me more about this?
174.
by kamranjon 4mo ago
Does anyone understand how Meta is able to spend so much money on AI with basically no AI product to speak of? Especially after sinking billions of dollars into a failed VR product? I just don't really understand why they are investing
175.
by kamranjon 4mo ago
a pretty fun and quick tests i do with vision models is to screenshot the hackernews homepage and ask the model to return a json representation of the screenshot - qwen 3.5 0.8b did surprisingly well at this.
176.
by kamranjon 4mo ago
To me this sounds like tailscale - does anyone have any insight into how what this is doing is similar or different?
177.
by kamranjon 4mo ago
I do quite a bit of 3d printing of functional parts and am trying to understand how this would fundamentally differ from printing at 100% infill? What type of part requirements are causing failures when something is just solid? Just curious
178.
by kamranjon 4mo ago
I was using the 8 bit quant and no reasoning - it’d make mistakes but then fix them at a speed that was impressive - it also was like incredibly tenacious and would honey badger its way around any issues it hit. My second best was Qwen 3 co
179.
by kamranjon 4mo ago
Crossing fingers for a 5.2 flash release - it’s been a while but I still feel like 4.7 flash is one of the strongest local coding models
180.
by kamranjon 4mo ago
I have been using deepseek v4 flash as my main model for everything ever since dwarf star came out. I run it on my M4 Max MacBook Pro with 128gb of memory. I run it usually as a server and connect to it over tailscale with my coding machine

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