491–500 of 793 posts
Now there are not one, but two incredibly powerful open LLMs. I think this level of capability makes general prioritization / high level decision making doable with the right harness, and now everyone has hard-to-interrupt access to them (since these are open weights and someone in the world is going to run them). This world is going to get really weird soon, in both good and bad ways...
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Please don't conflate a volunteer effort with no expected economic gain with a very well funded company (or fleet of companies). With the CCP's highly successful track record with subsuming other markets, Occam's razor applies to why they're doing this.
There is clearly an anti-China bias here. Show me comments demonstrating the same level of distrust against Google for open-sourcing projects like Tensorflow, Kubernetes, Flutter, Chromium, etc.
So Google is not a great counter example.
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Same, you can think of China whatever you want but they're really good at giving big tech a reality check when it comes to AI. We now got a pretty wide range of open-weight models (from DeepSeek and MiMo over to Kimi K3, Qwen 3.8 & GLM-5.2) and I think it's most important that there's a variance not only between quality / intelligence and also cost. I mean even the cheapest option for Luna is still more expensive tha…
"China" isn't giving anything. These are Chinese companies leveraging their best competitive strategy at the moment: competing on price.
I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to bett…
Big conferences often come with a flurry of new releases and announcements.
I'm trying to move to local models as much as I can, and I'm finding that it's becoming more and more practical. Admittedly this is on a $6000 dollar laptop (M5 Max Macbook with the specs maxxed out), so the hardware is still a bit out of reach for most people (the AI industry isn't exactly helping here..), but I'm getting the impression that the future is going to be smaller models with more focused training running locally. The danger of giving all your data to these cloud providers just seems too big to me, and I think they're going to start charging insane amounts when they need to show a profit.
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It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.
> It's hard to say what their motivation is. Not for anyone who reads history. Back in the late 18th century, England was the world's top economy, in big part due to its textile industry. England had an export ban on the technology, but textile worker named Samuel Slater brought blueprints over (Supposedly in response to a bounty posted in a newspaper by the US government!). The technology diffused rapidly because th…
A mill in Rhode Island acquired a 32 spindle Arkwright and didn’t know how to operate or install it. I have no idea how they actually acquired a 32 spindle Arkwright since that technology could not be exported - but that’s one the biggest IP thefts in human history. Slater found some mechanics who could hand turn the iron needed for the frame, trained children to operate it and by 1791, the mill was in operation.
In 1794, Eli Whitney patented a 72 spindle cotton gin. That invention enabled the American textile industry because it opened up different kinds of cotton to the textile industry.
I’m into the history of the American Industrial Revolution and generally think history is a good guidebook to the future. But the evolution of the American textile industry was a lot more complicated and interesting than this. I really don’t see this connection once you dig into Slater.
Edit - This is kind of messed up to think through with modern sensibilities. But one of Slater’s biggest contributions to the American Industrial Revolution was a slightly different take on child labour. Children generally ran the textiles industry because their hands were small. But Slater came up with a form of apprenticeship in which he would indenture entire families and move them into villages surrounding the mills. Child labour was just great… but even better when you could indenture the entire family. As grisly as that sounds, it led to a very skilled workforce since when the kids hands would get too big, their parents would teach them mechanics.
There’s a joy of studying the Industrial Revolution. Everything sounds okay in comparison.
I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to bett…
It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.
Maybe because the industry isn't yet very sure as to what the use cases might be for these technologies they're hoping that by making it open source and accessible to everyone that someone could find interesting applications for it and even more so, perhaps, way to further the technologies themselves.
There are more Chinese than Americans, so statistically speaking, I'm guessing, there'd be a greater chance for one of Chinese engineers to make advancements than one of American. But that's pure speculation on my part, being neither, I'm just happy I can be a part of it and play with the tools as well~
Earlier quoted context omitted.
Please don't conflate a volunteer effort with no expected economic gain with a very well funded company (or fleet of companies). With the CCP's highly successful track record with subsuming other markets, Occam's razor applies to why they're doing this.
There is clearly an anti-China bias here. Show me comments demonstrating the same level of distrust against Google for open-sourcing projects like Tensorflow, Kubernetes, Flutter, Chromium, etc.
Earlier quoted context omitted.
Please don't conflate a volunteer effort with no expected economic gain with a very well funded company (or fleet of companies). With the CCP's highly successful track record with subsuming other markets, Occam's razor applies to why they're doing this.
There is clearly an anti-China bias here. Show me comments demonstrating the same level of distrust against Google for open-sourcing projects like Tensorflow, Kubernetes, Flutter, Chromium, etc.
Yes.
> Show me comments demonstrating the same level of distrust against Google for open-sourcing projects like Tensorflow, Kubernetes, Flutter, Chromium, etc.
There's a search bar at the bottom of the page. Most people, including me, detest google and think of them as a thoroughly dishonest and sleazy organization. Thanks for giving me the opportunity to not boost China for a moment in order to accuse you of dishonest rhetoric.
It's almost insane that you've posted "comments demonstrating the same level of distrust against Google for open-sourcing [...] Chromium[...]" as if that's not a hobby for thousands of people (including me.)
edit: this has got to be a submarine shill account: 226 karma in 10 years. If this is true, pleas stop. China is doing a good enough job that they don't need it.
Earlier quoted context omitted.
It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.
Anyone else think the AI environmental backlash is astroturfed? I keep looking at the numbers. The power use numbers are not that problematic. Ordering a burrito on DoorDash uses more power than a few days of heavy AI use. The water argument applies to some locations, and is mostly a local governance problem... if the data centers are using too much water, it means they are not being charged enough for that water. Ch…
Driven by people in the few roles that are soundly replaced by AI-- e.g. low tier media slop producers, who hate AI because it threatens their socially negative worthless jobs. The arguments are so paper thin because the environmental impact isn't their concern, it's just a target that sounds convincing to people who don't know better.