4 ms·
The way to develop in this space seems to be to give away free stuff, get your name out there, then make everything proprietary. I hope they still continue rele
by ninjahawk1 6mo ago
The way to develop in this space seems to be to give away free stuff, get your name out there, then make everything proprietary. I hope they still continue releasing open weights. The day no one releases open weights is a sad day for humanity. Normal people won’t own their own compute if that ever happens.
- testbjjl 6mo agoAny reason for them to do this other than altruism? I don’t think this can be regulated.
- Rohansi 6mo agoBake ads into them.
- visarga 6mo agoI think it is in the interest of chip makers to make sure we all get local models
- zozbot234 6mo agoDefinitely. Many big hardware firms are directly supporting HuggingFace for this very reason.
- ninjahawk1 6mo agoTrue, chip companies have the opposite mindset, Nvidia is making their own open weights I believe
- qalmakka 6mo agoI think they're in a win-win situation. Big AI companies would love to see local computing die in favour of the cloud because they are well aware the moment an open model that can run on non ludicrous consumer hardware appears, they're screwed. In this situation Nvidia, AMD and the like would be the only ones profiting from it - even though I'm not convinced they'd prefer going back to fighting for B2C while B2B Is so much simpler for them
- zozbot234 6mo agoIf you want to run AI models at scale and with reasonably quick response, there's not many alternatives to datacenter hardware. Consumer hardware is great for repurposing existing "free" compute (including gaming PCs, pro workstations etc. at the higher end) and for basic insurance against rug pulls from the big AI vendors, but increased scale will probably still bring very real benefits.
- qalmakka 6mo agoCurrently, yes. But I don't find it hard to imagine that in a while we could get reasonably light open models with a level of reasoning similar to current opus, for instance. In such a scenario how many people would opt to pay for a way more expensive cloud subscription? Especially since lots of people are already not that interested in paying for frontier models nowadays where it makes sense. Unless keep on getting a constant, never ending stream of improvements we're basically bound to get to a point where unless you really need it you are ok with the basic, cheaper local alternative you don't have to pay for monthly.
- zozbot234 6mo agoI think average users are already okay with the reasoning level they'd get with current open models. But the big AI firms have pivoted their frontier models towards the enterprise: coding and research, as opposed to general chat. And scale is quite important for these uses, ordinary pro hardware is not enough.
- twoodfin 6mo agoThis is really just a question of product design meeting the technology. Today, lots of integer compute happens on local devices for some purposes, and in the cloud for others. Same is already true for matmul, lots of FLOPS being spent locally on photo and video processing, speech to text, … No obvious reason you wouldn’t want to specialize LLM tasks similarly, especially as long-running agents increasingly take over from chatbots as the dominant interaction architecture.
- 6mo ago
- baq 6mo agoAlways has been, it’s literally saas; the slight difference is that the lowest tier subscriptions at the frontier labs are basically free trials nowadays, too
- CamperBob2 6mo agoI'm a little more optimistic than that. I suspect that the open-weight models we already have are going to be enough to support incremental development of new ones, using reasonably-accessible levels of compute. The idea that every new foundation model needs to be pretrained from scratch, using warehouses of GPUs to crunch the same 50 terabytes of data from the same original dumps of Common Crawl and various Russian pirate sites, is hard to justify on an intuitive basis. I think the hard work has already been done. We just don't know how to leverage it properly yet.
- thesz 6mo agoChange layer size and you have to retrain. Change number of layers and you have to retrain. Change tokenization and you have to retrain.
- altruios 6mo agoHopefully we will find a way to make it so that making minor changes don't require a full retrain. Training how to train, as a concept, comes to mind.
- dTal 6mo agoNone of that is true, at least in theory. You can trivially change layer size simply by adding extra columns initialized as 0, effectively embedding your smaller network in a larger network. You can add layers in a similar way, and in fact LLMs are surprisingly robust to having layers added and removed - you can sometimes actually improve performance simply by duplicating some middle layers[0]. Tokenization is probably the hardest but all the layers between the first and last just encode embeddings; it's probably not impossible to retrain those while preserving the middle parts. [0] https://news.ycombinator.com/item?id=47431671 https://news.ycombinator.com/item?id=47431671 https://news.ycombinator.com/item?id=47322887 https://news.ycombinator.com/item?id=47322887
- andriy_koval 6mo agothere is evidence it is useful in some cases, but obviously no evidence it is enough if you chase to beat SOTA.
- WarmWash 6mo agoThe Chinese state wants the world using their models. People think that Chinese AI labs are just super cool bros that love sharing for free. The don't understand it's just a state sponsored venture meant to further entrench China in global supply and logistics. China's VCs are Chinese banks and a sprinkle of "private" money. Private in quotes because technically it still belongs to the state anyway. China doesn't have companies and government like the US. It just has government, and a thin veil of "company" that readily fool westerners.
- grttsww 6mo agoSo what? I still prefer that over US total dominance. Let them fight it out.
- spwa4 6mo agoI'd get a bit informed about what exactly Chinese dominance entails. Ask a few Uyghurs, Cantonese Hong Kongers, or even Tibetans. Then decide ...
- joquarky 6mo agoAsk a few Native Americans about dominance. Or maybe families of African descent. Or maybe families of Japanese Americans who lived in the US during WWII. Or maybe people of Latin descent living in the US today.
- jazz9k 6mo agoThe US examples you just gave happened decades (and in some cases hundreds) of years ago. The difference is that it's happening in China right now, and nobody cares. You really don't see the difference?
- well_ackshually 6mo agoThe US is the biggest threat to the world right now, and is actively supporting a genocide in Palestine as well as war crimes in Lebanon. I'm perfectly happy to let the chinese get a piece of the pie and fight the US, no matter how bad they are right now.
- Zavora 6mo agoIts the new freeware model!
- elorant 6mo agoThis is obviously a strategic move at a national level. Keep publishing competing free models to erode the moat western companies could have with their proprietary models. As long as the narrative serves China there will be no turn to proprietary models.
- Barrin92 6mo ago>This is obviously a strategic move at a national level. no it isn't. That's the kind of thing people say who've never worked in the Chinese software ecosystem. It's how the Chinese internet has worked for 20+ years. The Chinese market is so large and competition is so rabid that every company basically throws as much free stuff at consumers as they can to gain users. Entrepreneurs don't think about "grand strategic moves at the national level" while they flip through their copies of the Art of War and Confucius lol
- elorant 6mo agoIf this was true then they’d build services around those models and provide those for free or vastly cheaper than western competition. But that’s not what they’re doing. Instead they’re giving away the entire model for free. And by the way, Qwen isn’t build from some random entrepreneur who’s trying to solve the cold start problem, but from Alibaba which is a fucking behemoth. And surprisingly of course none of these models answer uncomfortable questions about China’s past. Because sure enough, the first thing any entrepreneur would think is to protect their government and their history. Sure, happens all the time, no state interference here, move on.
- lossolo 6mo ago> And by the way, Qwen isn’t build from some random entrepreneur who’s trying to solve the cold start problem, but from Alibaba which is a fucking behemoth. DeepSeek, Kimi, GLM, etc. are not built by behemoths, and they are free. You do not understand China's culture and market. > And surprisingly of course none of these models answer uncomfortable questions about China’s past. Download the GLM 5.1 weights and ask about Tiananmen Square, it will tell you what happened. You are viewing China through a Western lens. I used to do the same many years ago, but after traveling to China many times, I realized that was a mistake.
- culi 6mo agoI think that's an overgeneralization. We've seen all the American models be closed and proprietary from the start. Meanwhile the non-American (especially the Chinese ones) have been open since the start. In fact they often go the opposite direction. Many Chinese models started off proprietary and then were later opened up (like many of the larger Qwen models)
- embedding-shape 6mo ago> We've seen all the American models be closed and proprietary from the start. Most*. OpenAI, contrary to popular belief, actually used to believe in open research and (more or less) open models. GPT1 and GPT2 both were model+code releases (although GPT2 was a "staged" release), GPT3 ended up API-only.
- zozbot234 6mo agoOpenAI has released their GPT-OSS series more recently.
- deleted 6mo ago[deleted]
- magicalhippo 6mo agoRecently, more like 20 years ago in LLM-years. It's a good model though, would be nice with a refresh.
- culi 6mo agoThat's fair but those days seem so long gone now. Also the Chinese models aren't following a typical American SaaS playbook which relies on free/cheap proprietary software for early growth. They are not just publishing their weights but also their code and often even publishing papers in Open Access journals to explicitly highlight what methods and advancements were made to accomplish their results
- zozbot234 6mo ago
- ai_fry_ur_brain 6mo ago[flagged]
- try-working 6mo agoExactly. Open source is a commercial strategy for Chinese labs. They have no other effective way of marketing their models and inference services: https://try.works/writing-1#why-chinese-ai-labs-went-open-and-will-remain-open https://try.works/writing-1#why-chinese-ai-labs-went-open-an...
- stingraycharles 6mo agoThat has been a viable commercial strategy for most modern, funded businesses. Capture market share at a loss, then once name is established turn on the profit.