Teaching an undergraduate class or even a graduate class is still teaching. The author does not say he won't do that anymore.
The problem is about the fresh talent pipeline for researchers (i.e. PhDs). In many ways, elementary school and a Master's degree are more alike than a Master's and a PhD in the sense that you're learning prior art with clearly defined exam/project assessments and no expectation of making something truly novel in both elementary school and the Master's, while a PhD is all about discovering something nobody uncovered before. So, calling this a problem of not wanting to teach isn't quite right.
IMO, the article is rather highlighting a different problem; the former problem in this area was that only a tiny sliver of the best engineering/CS undergrads wanted go into research given the far more lucrative industry careers, and now the supply part of that market is about to vanish too due to agentic AI. This will basically kill the concept of an academic career as we know it and the point of the article is that we need to find a different model of advancing and funding science.
>You can also cut yourself with a kitchen knife but nobody proposes banning kitchen knives.
oh nice, i love this game.
you cant carry a kitchen knife that is too long, you cant carry your kitchen knife into a school, you cant brandish your kitchen knife at police, you cant let a small child run around with a kitchen knife...
literally most of what "the state" does is be a "nanny"
(not agreeing or disagreeing with google here, i have no horse in this particular race. but this little knife quip is silly when you think about it for more than 5 seconds)
In this example we still don't require you to register with anyone to buy a knife, get the blessing of some institution to sell knives, or, as in this case, get a certification before you can start making knives.
its crazy that different things, like knives and app stores, have different rules. maybe thats why the quip about the knife sounded super cool but fell apart as an analogy for this scenario when thought about for more than 5 seconds?
the point of my comment was that the state does implement a lot of rules (read: "is a nanny"), despite the claim otherwise.
I think it's important to consider the intent of those laws, too. They are primarily or even exclusively to prevent you from hurting others with knives. They are not really intended to protect you from cutting yourself in your own home. So I think the parent's comment still holds weight.
sorry, should say "carry", not "buy". most states have a maximum length you can carry (4-5.5 inches is common).
although, i would imagine at some length, it becomes a "sword" (even if marketed as a knife) and falls under some other "nanny"-ing. i have not googled that.
As kevin_thibedeau points out elsewhere in the thread, he's not necessarily wrong. In many states and foreign countries it's illegal to carry a large knife in public without a reason and I'm sure purchases are restricted in some places as well. Most people are more or less OK with that, it seems, so there historically hasn't been a lot of pushback.
Claiming they have the unrestricted right to scrape whatever information they want off the internet but complaining about it when others do to you and bringing out the 'China bad' card, just ironic
Somebody’s nervous about the competition, so they’re running a PR campaign. To me, though, this campaign hurts Anthropic more than anyone else. How can I trust the output of a model they can modify at will for certain clients? And who are they, after scraping the entire web, to complain about theft?
Nobody cared about deep learning back in 2007, when CUDA released. It wasn't until the 2012 AlexNet milestone that deep neural nets start to become en vogue again.
I clearly remember Cuda being made for HPC and scientific applications. They added actual operations for neural nets years after it was already a boom. Both instances were reactions, people already used graphics shaders for scientific purposes and cuda for neural nets, in both cases Nvidia was like oh cool money to be made.
Parallel computing goes back to the 1960s (at least). I've been involved in it since the 1980s. Generally you don't create an architecture and associated tooling for some specific application. The people creating the architecture only have a sketchy understanding of application areas and their needs. What you do is have a bright idea/pet peeve. Then you get someone to fund building that thing you imagined. Then marketing people scratch their heads as to who they might sell it to. It's at that point you observed "this thing was made for HPC, etc" because the marketing folks put out stories and material that said so. But really it wasn't. And as you note, it wasn't made for ML or AI either. That said in the 1980s we had "neural networks" as a potential target market for parallel processing chips so it's aways there as a possibility.
That's a bit confusing. Do you believe LLMs coming out of non-chinese labs are censoring information about Israel and/or Palestine? Can you provide examples?
ChatGPT, Gemini and Claude are banned in China. Chinese model providers are getting absolutely massive amounts of very valuable user feedback from users in China.
Gemini 3 Flash ("Fast" in the web app) did not have trouble with this:
Since you presumably want the car to be clean, the answer depends entirely on how the car is getting washed.
The Breakdown
If it’s a Professional Car Wash: You’ll need to drive. Bringing the car to the wash is generally the prerequisite for them washing it. Plus, walking 50 meters just to ask them to come pick up a car that is visible from their front door might result in some very confused looks from the staff.
If it’s a Self-Service Pressure Washer: Again, drive. Dragging a 1,500kg vehicle 50 meters by hand is an incredible workout, but probably not the "quick chore" you had in mind.
If you are hiring a Mobile Detailer: Walk. Stroll over there, tell them where you're parked, and walk back home to watch TV while they do the work in your driveway.
What is truly amazing here is the fact that they trained this entirely on Huawei Ascend chips per reporting [1]. Hence we can conclude the semiconductor to model Chinese tech stack is only 3 months behind the US, considering Opus 4.5 released in November. (Excluding the lithography equipment here, as SMIC still uses older ASML DUV machines) This is huge especially since just a few months ago it was reported that Deepseek were not using Huawei chips due to technical issues [2].
US attempts to contain Chinese AI tech totally failed. Not only that, they cost Nvidia possibly trillions of dollars of exports over the next decade, as the Chinese govt called the American bluff and now actively disallow imports of Nvidia chips as a direct result of past sanctions [3]. At a time when Trump admin is trying to do whatever it can to reduce the US trade imbalance with China.
Where did you read that it was trained on Ascends?
I've only seen information suggesting that you can run inference with Ascends, which is obviously a very different thing. The source you link also just says: "The latest model was developed using domestically manufactured chips for inference, including Huawei's flagship Ascend chip and products from leading industry players such as Moore Threads, Cambricon and Kunlunxin, according to the statement."
I took the "for inference" bit from that sentence you quoted as a qualifier applied to the chips, as in the chips were originally developed for inference but were now used for training too.
Note that Z.ai also publically announced that they trained another model, GLM-Image, entirely on Huawei Ascend silicon a month ago [1].
Thanks. I'm like 95% sure that you're wrong, and that GLM-5 was trained on NVIDIA GPUs, or at least not on Huawei Ascends.
As I wrote in another comment, I think so for a few reasons:
1. The z.ai blog post says GML-5 is compatible with Ascends for inference, without mentioning training -- it says they support "deploying GLM-5 on non-NVIDIA chips, including Huawei Ascend, Moore Threads, Cambricon, Kunlun Chip, MetaX, Enflame, and Hygon" -- many different domestic chips. Note "deploying". https://z.ai/blog/glm-5
2. The SCMP piece you linked just says: "Huawei’s Ascend chips have proven effective at training smaller models like Zhipu’s GLM-Image, but their efficacy for training the company’s flagship series of large language models, such as the next-generation GLM-5, was still to be determined, according to a person familiar with the matter."
3. You're right that z.ai trained a small image model on Ascends. They made a big fuss about it too. If they had trained GLM-5 with Ascends, they likely would've shouted it from the rooftops. https://www.theregister.com/2026/01/15/zhipu_glm_image_huawe...
Exactly. The emperor has no clothes. The largest investments in US tech in history and yet there less than a year of moat. OpenAI or Anthropic will not be able to compete with Chinese server farms and so the US strategy is misplaced investments that will come home to roast.
US Secretary of State Bressent just publicly said that the US needs to get along and cooperate with China. His tone was so different than previously in the last year that I listened to the video clip twice.
Obviously for the average US tax payer getting along with China is in our interests - not so much our economic elites.
I use both Chinese and US models, and Mistral in Proton’s private chat. I think it makes sense for us to be flexible and not get locked in.
>His tone was so different than previously in the last year that I listened to the video clip twice.
US bluff got called. A year back it looked like US held all the cards and could squeeze others without negative consequences. i.e. have cake and eat it too
Since then: China has not backed down, Europe is talking de-dollarization, BRICS is starting to find a new gear on separate financial system, merciless mocking across the board, zero progress on ukraine, fed wobbled, focus on gold as alternate to US fiat, nato wobbled, endless scandals, reputation for TACO, weak employment, tariff chaos, calls for withdrawal of gold from US's safekeeping, chatter about dumping US bonds, multiple major countries being quite explicit about telling trump to get fucked
Not at all surprised there is a more modest tone...none of this is going the "without negative consequences" way
Who could have predicted that cooperation with decades old allies would be more fruitful than spitting in their faces and threatening them on a weekly basis both economically and militarily... really nobody /s
And yes, the consequence is strengthening the actual enemies of the USA, their AI progress is just one symptom of this disastrous US administration and the incompetence of Donald Trump. He really is the worst President of the USA ever, even if you were to just judge him on his leadership regarding technology... and I'm saying this while he is giving a speech about his "clean beautiful coal" right now in the White House.
To be fair, the US ban on Nvidia chip exports to China began under the Biden administration in 2022. By the time Trump took office, it was already too late.
> What is truly amazing here is the fact that they trained this entirely on Huawei Ascend chips
Has any of these outfits ever publicly stated they used Nvidia chips? As in the non-officially obtained 1s. No.
> US attempts to contain Chinese AI tech totally failed. Not only that, they cost Nvidia possibly trillions of dollars of exports over the next decade, as the Chinese govt called the American bluff and now actively disallow imports of Nvidia chips
Sort of. It's all a front. On both sides. China still ALWAYS had access to Nvidia chips - whether that's the "smuggled" 1s or they run it in another country. It's not costing Nvidia much. The opening of China sales for Nvidia likewise isn't as much of a boon. It's already included.
> At a time when Trump admin is trying to do whatever it can to reduce the US trade imbalance with China
Again, it's a front. It's about news and headlines. Just like when China banned lobsters from a certain country, the only thing that happened was that they went to Hong Kong or elsewhere, got rebadged and still went in.
> Has any of these outfits ever publicly stated they used Nvidia chips? As in the non-officially obtained 1s. No.
Uh yes? Deepseek explicitly said they used H800s [1]. Those were not banned btw, at the time. Then US banned them too. Then US was like 'uhh okay maybe you can have the H200', but then China said not interested.
The problem is about the fresh talent pipeline for researchers (i.e. PhDs). In many ways, elementary school and a Master's degree are more alike than a Master's and a PhD in the sense that you're learning prior art with clearly defined exam/project assessments and no expectation of making something truly novel in both elementary school and the Master's, while a PhD is all about discovering something nobody uncovered before. So, calling this a problem of not wanting to teach isn't quite right.
IMO, the article is rather highlighting a different problem; the former problem in this area was that only a tiny sliver of the best engineering/CS undergrads wanted go into research given the far more lucrative industry careers, and now the supply part of that market is about to vanish too due to agentic AI. This will basically kill the concept of an academic career as we know it and the point of the article is that we need to find a different model of advancing and funding science.
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