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MediaSquirrel

3,021 karmajoined 17 năm trước
Founder/CEO at TalkTastic.com

Previously, I co-founded SpeakerText (speakertext.com), a interactive/social layer on top of online video, and Humanoid (gethumanoid.com), a crowdsourced virtual labor service that uses machine learning to track worker reputation on Mechanical Turk and ensure quality.

In previous lives, I fought forest fires in Montana & Alaska for the US Forest Service, worked as a freelance news reporter for the NY Times, and drove a 911 ambulance in Harlem and the South Bronx.

Submissions

Show HN: Local Motion – Use Cursor Agents and Chat with a Local LLM

github.com
1 points·by MediaSquirrel·18 giờ trước·0 comments

Show HN: Gist Discover – TikTok for ArXiv Summaries

gist.is
4 points·by MediaSquirrel·9 ngày trước·1 comments

Scalable GANs with Transformers

arxiv.org
3 points·by MediaSquirrel·11 ngày trước·0 comments

Cheaper Than Concrete: Robots and the New Stone Age

originals.is
4 points·by MediaSquirrel·11 ngày trước·0 comments

Lift4D: Harmonizing Single-View 3D Estimation for 4D Reconstruction In-the-Wild

arxiv.org
3 points·by MediaSquirrel·18 ngày trước·0 comments

Death Is an Engineering Problem

originals.is
3 points·by MediaSquirrel·18 ngày trước·1 comments

Non-frontal face recognition using GANs and memristor-based classifiers

arxiv.org
2 points·by MediaSquirrel·24 ngày trước·0 comments

MambAdapter: Lightweight Mamba-Based Adapters for Transfer Learning

arxiv.org
2 points·by MediaSquirrel·25 ngày trước·0 comments

Can I Buy Your KV Cache?

arxiv.org
36 points·by MediaSquirrel·29 ngày trước·28 comments

Before You Think: System 0, AI-Mediated Cognition and Cognitive Colonization

arxiv.org
1 points·by MediaSquirrel·29 ngày trước·0 comments

Reasoning as Pattern Matching: Shared Mechanisms in Human and LLM Reasoning

arxiv.org
1 points·by MediaSquirrel·29 ngày trước·0 comments

Superficial Beliefs in LLM Decision-Making

arxiv.org
3 points·by MediaSquirrel·30 ngày trước·0 comments

Show HN: Magenta Real-Time Music Generation Locally on iPhone, Without the GPU

github.com
9 points·by MediaSquirrel·tháng trước·0 comments

Feedback Alignment in Self-Distillation

arxiv.org
2 points·by MediaSquirrel·tháng trước·0 comments

WWDC 2026 – On-Device AI Deep Dive

gist.is
1 points·by MediaSquirrel·tháng trước·0 comments

Show HN: Gemma 4 Multimodal Fine-Tuner for Apple Silicon

github.com
235 points·by MediaSquirrel·3 tháng trước·28 comments

We Melted iPhones for Science – Generating Real-Time Video with On-Device AI

accelerateordie.com
1 points·by MediaSquirrel·10 tháng trước·0 comments

[untitled]

1 points·by MediaSquirrel·10 tháng trước·0 comments

We Melted iPhones for Science

accelerateordie.com
67 points·by MediaSquirrel·10 tháng trước·44 comments

comments

MediaSquirrel
·9 ngày trước·discuss
Ha, I built a version of the same thing as a Cursor plugin. Check it out:

https://open-vsx.org/extension/Transcendence/gist-discover https://gist.is/discover

We literally posted our Show HNs within minutes of each other: https://news.ycombinator.com/item?id=48768342

Great minds think alike.
MediaSquirrel
·11 ngày trước·discuss
[flagged]
MediaSquirrel
·18 ngày trước·discuss
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MediaSquirrel
·18 ngày trước·discuss
Dr. Alex Mathiasen, PhD wants to build a pause button for human biology – so that you can live forever. All he needs is enough GPUs to simulate quantum physics.
MediaSquirrel
·24 ngày trước·discuss
[flagged]
MediaSquirrel
·25 ngày trước·discuss
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MediaSquirrel
·29 ngày trước·discuss
[flagged]
MediaSquirrel
·29 ngày trước·discuss
[dead]
MediaSquirrel
·30 ngày trước·discuss
Do share.
MediaSquirrel
·30 ngày trước·discuss
[flagged]
MediaSquirrel
·tháng trước·discuss
[dead]
MediaSquirrel
·3 tháng trước·discuss
yeah, it came out after I stared on my project last year. Only issue is that you can't fine-tune it on Apple Silicon.
MediaSquirrel
·3 tháng trước·discuss
depends on the model!

If you run a smaller whisper-distil variant AND you optimize the decoder to run on Apple Neural Engine, you can get latency down to ~300ms without any backend infra.

The issue is that the smaller models tend to suck, which is why the fine-tuning is valuable.

My hypothesis is that you can distill a giant model like Gemini into a tiny distilled whisper model.

but it depends on the machina you are running, which is why local AI is a PITA.
MediaSquirrel
·3 tháng trước·discuss
Look inside here: https://github.com/mattmireles/gemma-tuner-multimodal/tree/m...

Here’s the trick: use Gemini Pro deep research to create “Advanced Hacker’s Field Guide for X” where X is the problem that you are trying to solve. Ask for all the known issues, common bugs, unintuitive patterns, etc. Get very detailed if you want.

Then feed that to Claude / Codex / Cursor. Basically, create a cheat sheet for your AI agents.

This will unlock a whole new level of capability.

I’m @mattmireles on Twitter — feel free to DM me.
MediaSquirrel
·3 tháng trước·discuss
More data -> better, faster on-device models

The actual plan was to distill Gemini 2.5 Pro into the best on-device voice dictation model.

Pretty sure it would have worked. Alas.
MediaSquirrel
·3 tháng trước·discuss
re: Whisper v3 -- how is this possible? Whisper has a 30s context window. You have to chunk it.
MediaSquirrel
·3 tháng trước·discuss
Great minds think alike!

Also, I had a huge head start, as I spent a month or two working on this in September 2025, shelved it and dusted it back off this weekend.
MediaSquirrel
·3 tháng trước·discuss
Haven’t tried yet. That’s on the do list. But good suggestion.
MediaSquirrel
·3 tháng trước·discuss
you are welcome! It was a fun side quest
MediaSquirrel
·3 tháng trước·discuss
Memory usage increases quadratically with sequence length. Therefore, using shorter sequences during fine-tuning can prevent memory explosions. On my 64GB RAM machine, I'm limited to input sequences of about 2,000 tokens, considering my average output for the fine-tuning task is around 1,000 tokens (~3k tokens total).