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ggcr

392 karma · joined January 8, 2023

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ggcr··on Ants: Who looks after the injured in a colony?
Fascinating. Hidden on the bottom of the article seems to be a video [1] showcasing how they track each ant out of the six colonies of 110 each.

I'd like to read the paper to skim over the methodology but it's not open-access :(

[1] https://www.uni-wuerzburg.de/fileadmin/uniwue/2026/0702Ameis...

ggcr··on OpenAI unveils its first custom chip, built by Broadcom
With Reinforcement Learning, inference is very present in post-training stages now too
ggcr··on Show HN: Lightweight C++23 S3 client with no extra deps (just curl and OpenSSL)
Fair point. Should've titled it "minimal dependencies" perhaps

Since C++ has no HTTP client in its std lib, I really had no other choice but to use curl. Same with OpenSSL. It'd be quite naïve of me to re-implement the whole HTTP stack and SHA256 from scratch =)

ggcr··on Show HN: Lightweight C++23 S3 client with no extra deps (just curl and OpenSSL)
Yep! I'd also like to explore C++26 reflection for the XML FSM parser I currently have

Everything so far is synchronous. In our toy benchmarks I've found out Go to be quite performant, perhaps it's using go-routines behind the scenes (?) Haven't explored their internals yet but I was surprised

ggcr··on MAI-Code-1-Flash
:(

I was hoping Microsoft would make it open weights, as they have done for years with the Phi models.

The era of big tech releasing models into the wild might be over, which IMO is counter-productive, as we are shifting from "the model is the product" to "the harness is the product"

ggcr··on MAI-Code-1-Flash
Meta recently launched Muse Spark [1] and they themselves compare against Claude Opus 4.6 Max.

Here Microsoft is comparing against Claude Haiku, the smallest and least capable model from Anthropic.

[1] https://ai.meta.com/blog/introducing-muse-spark-msl/

ggcr··on Qwen3.5: Towards Native Multimodal Agents
Thanks, I've totally missed that

It's basically the same as with the Qwen2.5 and 3 series but this time with 1M context and 200k native, yay :)

ggcr··on Qwen3.5: Towards Native Multimodal Agents
From the HuggingFace model card [1] they state:

> "In particular, Qwen3.5-Plus is the hosted version corresponding to Qwen3.5-397B-A17B with more production features, e.g., 1M context length by default, official built-in tools, and adaptive tool use."

Anyone knows more about this? The OSS version seems to have has 262144 context len, I guess for the 1M they'll ask u to use yarn?

[1] https://huggingface.co/Qwen/Qwen3.5-397B-A17B

ggcr··on The dired abstraction
alvaro's posts are must reads
ggcr··on Ask HN: Share your personal site
https://ggcr.es/
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