#ai

Apple Partners with Alibaba for AI #

Apple partners with Alibaba for AI features in China

via Daring Fireball

This is an interesting partnership, since Alibaba’s relatively open model weights are much more akin to Meta compared to OpenAI, Apple’s main AI partner. I think the partnership is mainly for Alibaba’s cloud server infrastructure, since the Chinese giant’s Qwen models are a lot less consequential to Apple Intelligence compared to OpenAI’s previously industry-leading GPT models. However, if Apple did see a specific use for the Qwen suite of models, this would likely be the best way to integrate them, since companies with more than 100 million MAUs are subject to an additional clause in the Qwen License which requires requesting a special license from Alibaba. It’ll be interesting to see the comparisons between Apple Intelligence globally and in China, and I’m curious if a sudden innovation by Alibaba will propel the service to being better specifically in the country.

OpenAI Has Been on the Wrong Side of History #

Reddit comment from u/samaltman

via Simon Willison

Sam Altman, in response to a request to release model weights:

yes, we are discussing. i personally think we have been on the wrong side of history here and need to figure out a different open source strategy; not everyone at openai shares this view, and it’s also not our current highest priority.

I saw this comment on Slashdot yesterday, but didn’t realize that it came from Altman’s personal Reddit account. I previously assumed that Altman said this in a conversation with some politician, where absolutely nothing could be taken literally without considering OpenAI’s motives.

I still don’t think that this Reddit comment can be really considered as OpenAI going back to open source, especially since Altman has so much leverage in terms of the company’s plans and could have previously attempted to pivot to a more open company. This discrepancy is especially obvious even when comparing OpenAI to Anthropic, who doesn’t publish open model weights but at least attempts to make parts of their technology more accessible for usage without a $200/month subscription.

This comment is obviously catered towards the audience who thinks that OpenAI is going to implode because of DeepSeek, but there’s not really any advantage for OpenAI to open source their stack since the company is well established compared to the Chinese AI lab. I would guess that the main reasoning for this comment is just to give investors something to work with when considering OpenAI’s status compared to other AI companies (of course, primarily DeepSeek), so I wouldn’t derive any real meaning out of it.

DeepSeek-R1 is not Sputnik #

DeepSeek-R1’s lead is fundamentally different than what Sputnik’s was for many reasons, the primary one being the difference in access to powerful GPUs. DeepSeek did not design R1 to be trained on H800s just to see if it was possible—there were monetary and political incentives for them to create a powerful model on such limited hardware. In contrast, American AI companies have not felt any need to optimize model training, since they are much more focused on a different goal: fast, cheap inference. DeepSeek has been doing great work, but their work should not be any sort of scare for the American AI market, especially since R1 benchmarks extremely closely with o1.

As an analogy, I think of it as a student writing a compiler: it takes hard work for someone of their age, and fortells their ability to do much more complicated work as a future computer scientist. However, the same compiler could have just been created by a computer scientist who has specialized in compiler design for a decade. In this same way, DeepSeek is training impressive models on limited hardware, showing their architecture’s potential for training an even more powerful model if they had access to more powerful hardware. However, OpenAI already has access to the powerful hardware and is training their models using it, allowing them to easily train models with the same performance as R1, even with a worse model architecture. Therefore, even if DeepSeek is a student who—through a lot of hard effort—created a compiler, OpenAI is an experienced researcher who creates a similar result with much less effort.

Since American AI companies have access to the supplier of powerful GPUs (Nvidia) and now know a more performant training architecture through DeepSeek’s open research, there’s nothing stopping them from easily creating more powerful reasoning models than DeepSeek-R1. That’s the main difference compared to Sputnik—there shouldn’t be any perceived technical gap because DeepSeek’s innovation is unnecessary in the eyes of American AI companies (but it will still benefit these companies immensely).

Additionally, it’s not as if DeepSeek is using Chinese-made GPUs—if they were doing that, it would definitely should be a scare to American AI companies. But right now, DeepSeek and other Chinese AI companies still have a heavy reliance on Nvidia, allowing the United States to easily control the technological gap between it and China.

llama.vim #

ggml-org/llama.vim

via Hacker News

A nice AI completion plugin from Georgi Gerganov, the creator of llama.cpp. The completion seems pretty good, but it’s obviously either going to be slower or less accurate than something like Codeium. Of course, the main benefit of llama.vim is being able to generate completions locally, meaning that no private code is accidentally transferred to external servers. While there are already many Vim plugins available for local AI completion, llama.vim’s main advantage is its ease of use through directly integrating with llama.cpp—no configuration is required, and a single command is used to start the completion server. I also like the use of VimL over Lua, since a lot of new plugins are being written solely for Neovim instead of also supporting Vim.

AGI “for Humanity” #

Sam Altman is unreasonably good at convincing officials that his for-profit endeavours are actually net benefits for humanity. It’s pretty clear that he’s disillusioned himself to the true state of capitalism, where creating a larger OpenAI does not automatically translate into better conditions for the general public. He shows this way of thinking in posts like The Intelligence Age, which not-so-subtly converges to the necessity of additional funding (read: needing to creating a for-profit to raise said funding) to “make sure AI isn’t solely controlled by the rich”:

If we want to put AI into the hands of as many people as possible, we need to drive down the cost of compute and make it abundant (which requires lots of energy and chips). If we don’t build enough infrastructure, AI will be a very limited resource that wars get fought over and that becomes mostly a tool for rich people.

This was back in November, an eternity ago in the fast-paced AI scene (remember, AGI was only “a few thousand days” away!), and reaching AGI soon is still very much a speculation. Of course, Sam Altman is still interested in making more money, and still views OpenAI’s expansion as a universal benefit for the American people. Therefore, to him, AGI expansion is the only way forward: a technology that OpenAI will be perpetually close to creating, as the one in charge of defining what constitutes as AGI is Altman himself.

That’s the state in which the Stargate Project finds itself in, with the goal of reaching AGI eventually. But why should OpenAI and co. ever admit to actually creating AGI? The group currently has a nice $500B in funding, support from the U.S. government, and easily maintains the largest share of the AI market. None of this will disappear soon, especially as MGX and SoftBank can easily prioritize funding Altman’s pursuits on the off chance that AGI is actually achieved. And even if Stargate’s money sources somehow disappear, framing the project as a “net positive for all Americans” allows the U.S. government to easily support the endeavour (and grant OpenAI and Altman even more money).

Even if AGI is achieved through the Stargate Project, what would be the resolution? OpenAI claims that the project will create “hundreds of thousands” of American jobs. As pointed out by many Hacker News commenters, this cannot be predicted with any certainty and will likely result similarly to Foxconn’s $10B investment in Wisconsin (forecasted 13000 workers; actually ~1500), leading to the efforts solely benefitting OpenAI and the other private corporations. But even then, from Altman’s viewpoint, the endeavour is still a net positive for humanity: any increase to OpenAI’s valuation is just securing a future with more AI capabilities (which surely will be beneficial to all).

Note that this way of thinking isn’t limited to just Sam Altman: most “tech leaders” are figureheads for their respective companies and their political views and personal opinions should generally not be considered from a utopian point of view.