A more textually oriented environment (like a normal Unix shell) is, in my experience, usually referred to as a CLI: Command Line Interface.

I did find an interesting hybrid in the Pi coding agent: it seems to leverage the normal terminal scrollback, while still enhancing it with things like transient input fields and status lines, so that it can display those without cluttering scrollback.

In fact, Intel also had Lunar Lake, which had on-package memory. However, it was still limited to 128-bit dual-channel, so there weren't really many performance benefits; it did however help with power efficiency.

First off, I believe that Intel has its memory far more "unified". AMD typically has a stricter VRAM/RAM 'tradeoff' setting that does not exist on Intel in the same way to my knowledge. (See how on Strix Halo systems, there is a thing about "allocating" 96 GB to the GPU, which seems to be needed sometimes but prevents the CPU from accessing that memory.)

Secondly, the Panther Lake board has LPDDR5X LPCAMM2 memory at 7467 MT/s, while the AMD boards are stuck with DDR5 SODIMMs at a meagre 5600 MT/s. In other words, the Intel board gets a third more memory bandwidth!

- It was the first card to enable real-time ray-traced effects. - Mesh shaders are a significant overhaul of the geometry pipeline that's only recently getting real traction. - Its tensor cores enabled a new generation of AI-driven upscaling/antialiasing. DLSS 2, FSR 4 and XeSS are all some variation of "TAA + neural networks", and these all rely on specialized matrix hardware to get optimal performance.

Obviously all of these features are supported across all vendors. Intel Arc Alchemist has all of these features as well, and AMD got RT and mesh shader support with RDNA2 along with slowly building up to tensor cores with RDNA3/4. But Turing clearly debuted these feature which have majorly changed the landscape of realtime 3D graphics.

So it's closer to half the speed than a tenth. Intel also seems to be positioning this card against the RTX PRO 4000 Blackwell, not the 5090, and that one gets more like 300 INT8 TOPS. It also has less memory but at a slightly higher bandwidth. The 5090 is much faster and IIRC priced similarly to the PRO 4000, but is also decidedly a consumer product which, especially for Nvidia, comes with limitations (e.g. no server-friendly form factor cards available, and there are or used to be driver license restrictions that prevented using a consumer card in a data center setup).

IIRC Granite Rapids is also not _that_ old, and either current or a single generation behind. (Has its successor landed yet? IIRC GNR is the same generation as Sierra Forest).

I'm guessing this isn't fully cycle-accurate, but is it at least somewhat "IPC-accurate"? I'm guessing yes? But much of that was also derived from Voodoo's (for the time) crazy high memory bandwidth AFAIK.

I found a Reddit comment claiming only 36 KiB per token. With that, half a million tokens fits in 18 GB, which is less than one GPU. And three GPUs fit the parameters with room to spare (64 out of 72 GB).

Again, though, if those work I assume they will be used for the slowrun. Surely a few hundred LoC to generate data would not be considered cheating :)

Intuitively, I would expect the synthetic data to mostly just "regurgitate" the existing data, and not add much. But I could be wrong of course, and perhaps doing reinforcement learning somewhere could solve that issue as well (though I don't know if there is much hidden in FineWeb that you could RL on; at best you can do self-verification probably?)

For example, let's say I want to add commit message generation (which I don't think is a great use of LLMs, but it is a practical example) to a repo. I would add the appropriate hook to /.git, but I would also want the agent with its instructions to live inside the repo (perhaps in an `axe` or `agents` directory).

Can Axe load agents from the current folder? Or can that be added?

Looking at the size, and its shared nature, it feels far more natural to compare with the L2 cache, which is also shared across the entire GPU and is in the same order of size (40MB on the listed A100).

The same trend is visible in GPUs: for example, my RTX 2070 (GDDR6) has the same memory bandwidth as a 3070 and only a little bit less than a 4070 (GDDR6X). However, a 5070 does get significantly more bandwidth due to the jump to GDDR7. Lower-end cards like the 4060 even stuck to GDDR6, which gave them a bandwidth deficit compared to a 3060 due to the narrower memory buses on the 40 series.

Huh? This comment sounds extremely America-centric to me. Porsche sells more cars into Europe than North America, despite taking a bigger there (-13-16% vs 0%)!

In general I don't think Porsche is representative of the car market as a whole, given their cars are all premium sports cars to at least some degree.

If you want more representative numbers look at more mass-market manufacturers. Notably, the Volkswagen group has a huge 20%+ market share in the EU, while it is below 5% in the USA. Renault is another example of a strong EU-centric brand and manufacturer with over 10% market share, even over 25% at home in France. Ford is a good example of the opposite, having 13% market share in the USA and only 2-3% here. Stellantis is strong in both markets, but has significant differentiation, even having different brands in both markets.

I believe the main holdup is a desire for Wayland to be usable with e.g. VR interfaces where there is no simple 2d grid.

Out of curiosity, how do you want the file manager to behave? And did you write your own or are you using an existing one that works that way?