Hy4 preview - Hacker News

Posted by shenli3514 10 hours ago

Hy4 preview(www.tencent.com)

244 points | 141 commentspage 3

sezaidemirer 7 hours ago|

Congratulations, it turned out great!

zem 2 hours ago||

I was briefly impressed that https://hylang.org/ had released a 4.0 version!

petcat 8 hours ago|

> Tencent has released and open-sourced Tencent Hy4 preview, a next-generation large language model with 770B total parameters and 49B active parameters, and a context window exceeding 1M tokens.

There are no open source models, at least not useful ones (yet) [0]. Open weight is not the same as open source. The current "open weight" models are just opaque binary blobs you can run on your own computer instead of through a web API.

[0] https://allenai.org/

Imagine thinking that running a Photoshop binary on your own computer instead of through a SaaS web app means that it's "open source". Of course you think that's ridiculous.

mirekrusin 8 hours ago|

You can open source dataset without all the details how it was assembled.

Models are lossy compressed datasets you can pick up and amend (fine tune / continue training / alter) according to license they were released under.

Hy4 is released under OSI approved Apache License 2.0.

kennywinker 7 hours ago|||

Parent poster is technically right - open “source” implies the source used to make something is open. The model source is training data and code, not just weights.

But the reality is, the weights are a useful artifact that you can use to create derivative works. So, dismissing it as a photoshop binary is as technically wrong as calling it open source.

villish 6 hours ago||||

Countries that aren’t competitive need access to training datasets so that they may train their own similarly capable models and be sure of the inputs. Governments cannot blindly trust open weight models from China and the US.

LtWorf 7 hours ago|||

So windows is open source because the binaries are a lossy compression of the original source?

NitpickLawyer 1 hour ago||

Weights are not binary. A model is created at init time, with random values. After that, it is being modified using data. The key point is that the labs modify the models "as weights". That means that weights are the intended / preferred way of modifying a model. Which, coincidentally, matches the definition of source in Apache 2.0. There is no "higher level" place where editing takes place. It all happens in weight space. Through the license you get the same rights as the lab that created it: view, inspect, run, modify, re-release. That's it. That's the only thing a license can grant you.

The rest is semantics, misunderstandings, and FUD. A model released under an open source license is open source. Training data is lab knowhow / IP. Which, historically, has never been required for any open source release.