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by supriyo-biswas 9 days ago
It is surprising to me American companies completely absent from the open model space, even though we have historically seen companies doing open source.
7 comments

They aren't completely absent. Google keeps releasing Gemma models. Nvidia publishes Nemotron. Microsoft has their Phi series. IBM publishes Granite. Even OpenAI released a new open model (gpt-oss) less than a year ago.

https://deepmind.google/models/gemma/gemma-4/

https://developer.nvidia.com/ai-models#:~:text=NVIDIA%20Nemo...

https://www.microsoft.com/en-us/research/blog/phi-4-reasonin...

https://www.ibm.com/granite

https://openai.com/index/introducing-gpt-oss/

I was going to link all of these, some are better than others, but they're all reasonably capable. A lot of these have versions that can run on modest hardware too. Granite was the most surprising I learned about recently, wasn't too good with Zed though.
I think that models like Granite are less known because they aren't clear leaders in any particular area. This obscurity is also another sign of how fast models are developing. If current Granite models had been released 4 years ago, they would have been astonishing breakthroughs at the time.
The gpt-oss models are good but there's no evidence that OpenAI have ongoing development on open models.

I'm 99% sure it was one-and-done, box ticked, and now they can be mentioned in comments like this.

Perhaps, the issue is that the pace at which they release open models compared to their closed ones, shows that they are more committed on the closed ones and are not interested in advancing the state of the art of open models.
Should companies like Google and OpenAI be more interested in building open models than the ones they make money from?

Should they be interested in advancing state of the art open models?

I can't say what they should or should not be doing.

Generally, it is conspicuous how American companies are absent when it comes to state of the art open models. Meta tried for some time but it seems they've given up.

One of the main reasons why companies start new open source projects is because having a good open source option in a given category will usually push the market value of software in that category to $0, and this can be strategically valuable. For example, Google released Android as an open source operating system because they make their money from ads and data collection, not from selling operating system licenses. All the cell phone companies switched from Windows Mobile and Symbian to Android, which gave Google a ton of user data to sell.

For AI, the most profitable part of the value chain is selling inference. None of the big American companies want to release a leading edge model as open source because this would drive the price of inference to $0. Meanwhile, open source AI models are a huge strategic initiative for China. Having commodity Chinese models that are as good as the leading edge American models from 6 months ago forces the American companies to keep paying more and more money to train better and better models since the amount of time they can collect rent on a model they've previously trained is limited to 6 months.

In business strategy terms this is known as "commoditize your complements".

https://www.joelonsoftware.com/2002/06/12/strategy-letter-v/

Thank you for this article link! I had not seen it before. will be printing it off to read later.
The Chinese approach is reminiscent of the US spending so much on 'defense' in the 1980s that the USSR bankrupted itself trying to keep up.
> None of the big American companies want to release a leading edge model as open source because this would drive the price of inference to $0

Meta/Llama: "What am I, chopped liver?"

I thought the thing keeping inference above $0 was the hardware, and even if that were free there's still the tyranny of the Landauer Limit.

When was the last Llama release? Meta have abandoned it and reportedly they've had a shift in their AI strategy.
Meta Llama is free for many uses but it doesn't even remotely meet the definition of "open source".
They are useless and outdated by today standards.
Google had to release at least the core packages in Android regardless because it is based on top of Linux and the GPL license would require it.
But they open sourced much more than that, and under more permissive licenses.

The notable exception is of course the google play services, which is also strategic (they control the OEMs with this, among other things).

And the drivers, but that's mostly not them I think (they could possibly have required open source drivers though)

Embrace, Extend, Extinguish. Google did the Microsoft playbook. Look at email. Look at youtube we used to share videos via Kazaa and other p2p programs, zero censorship, all the same features (including chat!!) theres also XMPP which became Google Talk -> Chat -> Hangouts etc then the browser, how many random apps “Only works on Chrome” but you change the Firefox browser agent and it works there too!
No one open sources their core competencies, GitHub never open sourced their networked filesystem and Heroku never open sourced their dyno sandboxing code. They open source ancillary tools.
I'm curious, what would you say is DeepSeek's core competency?
Since it’s probably a state sponsored project, it is the open source ancillary tool to China’s core competencies
Distillation attacks. The weights are just a proof-of-work hash
Devaluing American companies, perhaps.
OpenAI & Anthropic are winning right now. I suspect if Chinese companies get ahead in the race the cards will reverse, OpenAI will restart farming goodwill with open models and then winning companies will be releasing closed models.
As what we say here in Brazil:

"The world doesn't go round. It flips over!"

American companies are interested in cashing in, not making a good product.
Llama?