Starmer has been ramping up on domestic and European defence spending

In complete accordance with the USA’s orders? These were the USA’s orders to the UK. https://www.war.gov/News/Speeches/Speech/Article/4064113/opening-remarks-by-secretary-of-defense-pete-hegseth-at-ukraine-defense-contact/

Is anything Starmer has done in conflict with these orders? Has he done anything that makes it harder or impossible to follow these orders in the future that shows that he’s disregarding them? Otherwise, the specific examples you gave are in line with following the USA’s orders so far.

demands for interoperability with non-Apple products

the rules were not applied to Samsung

I wonder if Samsung owns a walled garden where their products aren’t interoperable with those from other manufacturers.

They did that without her consent!?

Okay so Donald Trump and Jeffrey Epstein were arrested, that’s big news, guess they resurrected him. Who are the other two?

Don’t you have that backwards? Without TSMC’s outstanding technology, the island’s value decreases, both for China and for the USA. Conventional wisdom is that reduced tensions also reduces the risk of war.

The public must be so terrorised in their homes, knowing the orphan crushing machines can’t come and save them when they need snap-orphan crushing.

300i https://www.bilibili.com/video/BV15NKJzVEuU/
M4 https://github.com/itsmostafa/inference-speed-tests
It’s comparable to an M4, maybe a single order of magnitude faster than a ~1000 euro 9960X, at most, not multiple. And if we’re considering the option of buying used, since this is a brand new product and less available in western markets, the CPU-only option with an EPYC and more RAM will probably be a better local LLM computer for the cost of 2 of these and a basic computer.

That’s still faster than your expensive RGB XMP gamer RAM DDR5 CPU-only system, and you can depending on what you’re running saturate the buses independently, doubling the speed and matching a 5060 or there about. I disagree that you can categorise the speed as negating the capacity, as they’re different axis. You can run bigger models on this. Smaller models will run faster on a cheaper Nvidia. You aren’t getting 5080 performance and 6x the RAM for the same price, but I don’t think that’s a realistic ask either.

I’m not saying you can deploy these in place of Nvidia cards where the tooling is built with Nvidia in mind. I’m saying that if you’re writing code you can do machine learning projects without CUDA, including training.

I agree with your conclusion, but these are LPDDR4X, not DDR4 SDRAM. It’s significantly faster. No fans should also be seen as a positive, since they’re assuming the cards aren’t going to melt. It costs them very little to add visible active cooling to a 1000+ euro product.

You can run llama.cpp on CPU. LLM inference doesn’t need any features only GPUs typically have, that’s why it’s possible to make even simpler NPUs that can still run the same models. GPUs just tend to be faster. If the GPU in question is not faster than an equally priced CPU, you should use the CPU (better OS support).

Edit: I looked at a bunch real-world prices and benchmarks, and read the manual from Huawei and my new conclusion is that this is the best product on the market if you want to run a model at modest speed that doesn’t fit in 32GB but does in 96GB. Running multiple in parallel seems to range from unsupported to working poorly, so you should only expect to use one.

Original rest of the comment, made with the assumption that this was slower than it is, but had better drivers:
The only benefit to this product over CPU is that you can slot multiple of them and they parallelise without needing to coordinate anything with the OS. It’s also a very linear cost increase as long as you have the PCIe lanes for it. For a home user with enough money for one or two of these, they would be much better served spending the money on a fast CPU and 256GB system RAM.

If not AI, then what use case do you think this serves better?

CUDA is not equivalent to AI training. Nvida offers useful developer tools for using their hardware, but you don’t have to use them. You can train on any GPU or even CPU. The projects you’ve looked at (?) just chose to use CUDA because it was the best fit for what hardware they had on hand, and were able to tolerate the vendor lock-in.

She was born in London and received citizenship at birth. It’s not her skin colour that inspired her politics.

Does it have any sort of on-board NPU to make it AI-oriented?

Unalive started being widely used 2020-2021.

Very good

Only because Google doesn’t index Chinese sites =P Deepseek had an access control bug when it first launched and Qwen is owned by Jack Ma.

The article talks about eighteen year olds that were hired “because they look very young”, playing children characters, with costumes and makeup meant to make them look younger.

GPUs being able to spy on you is a problem. Linux and OSs should work on ways to minimise this possibility. But specifically worrying about them ratting you out to the CPC is in my opinion much less serious than spying on you for commercial interests. Ultimately it’s possible to avoid visiting China if you aren’t Chinese. Including Chinese websites.

You could watch two YouTube films at once. (No but seriously 2Mb/s is too low even for just YouTube. YouTube recommends 20Mb/s. And that’s probably assuming 30hz. So you probably actually want at double or more. https://support.google.com/youtube/answer/78358)