Microsoft Decision-1: 9B Qwen Model Launch Explained | Hacker News Reader

Microsoft Decision-1: 9B Qwen Model Launch Explained

shattered.io

72 pointsgmays32 comments

Reads like an ad for Microsoft and its model because it's an article about a decision model that doesn't mention Jev or other decision models at all.

Exactly my thought. I read the whole article, did Cmd +F for Jev - and felt uneasy on did the author did any research at all

And reads like AI generated text, to boot. But then that might just be because it’s marketing, and LLMs write in non stop marketing speak

This is really AI slop - so I don’t really know if it makes any sense for comments given that there is no real way to validate the crap that was put out.

It seems somebody bought the domain due to its rating. All the authors share the same type of image for their profile pics…

It’s sad that this content now come to the top of HN so often

Unlike the Internet, Microsoft did recognise the pivotal moment. But they made the wrong play… that and they’ve annoyed pretty much everybody with their products, I don’t think I’ve ever seen such a successful company with such little good will from their community.

They are a de facto monopoly for decades. They can afford annoying everyone.

No pelicans riding bicycles on this one, eh?

Pelicans are deciding.

Pelicans deciding if they are going to ride a bicycle.

Bikes with integrated decision models deciding which pelican needs a ride the most.

This made me realize it's been a long time since I did some brainstorming and how I missed it.

Put a decision model in my bike that decides when it is time to automatically shift up/down based on signals (FTP, Watt avg, HR, cadence, upcoming grade) and I will buy a subscription to your SaaS.

Instead the right app is hotdog / not hotdog

Could one reverse the test? Feed ai generated svgs into the model and ask it to decide which of 10 animals (dog, cat, pelican, crocodile, etc) doing which of 10 actions (moonwalking, paddleboarding, sitting, riding a bicycle, etc.).

AlexNet (2012) can do the first part :)

From an svg not rendered to pixels?

I haven't evaluated this one, but for what I have, it seem the pplx-decider-v1.2 (and its -flash variant) are pretty good. Anyone evaluated all these open-source decision models on their own tasks? (I evaluated on MonitoringBench).

I didn't look specifically at open-source but I evaluated as many decision models as I could on openrouter against how good are they at detecting phishing, which isn't the best use of these models but I was interested to see how they compared. https://emdashcyber.com/phishnchips-decision-models/

I had my first use case recently, and did some very non-systematic benchmarking of models on OpenRouter.

The only one that came close to Jev itself was the one from respan (respan/span-02), which is also open source and cheaper too.

Have you checked mammoth-1/elephant-1 models? They are benchmarking quite well compared and are currently free on openrouter. I currently use mammoth-1 for a small internal app and it works flawlessly for what I am doing.

https://huggingface.co/baselabs/mammoth-1

No. I will, and I will report here.

Did some ad hoc/small test. Unfortunately not very impressive. At least no on German short text, which is my use case.

Ah damn and also interesting. I am using it for classifying ads in podcasts. I am listening to a lot of English podcasts, but I am in Germany so often German segments are cut in. Mammoth-1 has had zero issues classifying those segments, but I guess my usecase might just be a lot simpler than yours.

You might also be interested in this index for decision models: https://huggingface.co/spaces/multimodalart/jev-decision-ind...

Mine deals with sentiments of news headlines.

Thanks for the index. I will try to navigate it. For now I cannot even find this respan/span-02 in it :/

Just fyi, i switched to span-02 on openrouter as well since it’s 10x cheaper than mammoth and it’s performing just as well for me, if not better because it’s noticably faster! So thanks for the recommendation.

> a model that refuses to write you a paragraph

AI slop reporting. Actual news: https://commandline.microsoft.com/microsoft-decision-1-model...

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