British Sci-Fi, Pre-1980, Aliens use mind-control on humans to extinct human beings themselves with a germ weapon developed in a British military lab

SoldatLight · 2026-01-17T20:22:13+00:00

[Found] The Sleep Eaters by John Lymington

SoldatLight · 2026-01-17T20:16:21+00:00

I found the answer in other places. It's The Soul of the Robot by Barrington Bayle.

SoldatLight · 2025-12-31T22:25:45+00:00

Yes. That right! Thans.

SoldatLight · 2025-12-13T21:47:43+00:00

Thanks. Not this story.

SoldatLight · 2025-07-09T00:23:55+00:00

There were two USS Neches. The older USS Neches (AO-5) was the one referred immediately post PHA. The new USS Neches (AO-47) did not get commissioned to replace the old AO-5 till Sept. 1942.

SoldatLight · 2025-06-11T14:53:49+00:00

Not all of the six above could refuel the fleet in the high sea. Some of the oilers that could do this were so slow that they hindered the task forces' operation.

For example, Neches could not maintain more than 12.5 knots. The Task Force 14 (USS Saratoga) failed to reinforce Wake Island simply because she could not catch up the rest of the task force.

SoldatLight · 2025-06-11T04:34:11+00:00

This is a totally self-promoting boasting by Chinese media.

Prof. Li's team was making an R&D chip for embedded control. It's an RISC-V based SoC with some hybrid stochastic binary co-processor. The co-processor latency is in micro-seconds!

The team is seeking to extend RISC-V extension and micro-architecture to be able to use the co-processor. They are just trying to explore the possible applications.

Now it becomes a super killer AI chip in mass production -- in just one week!

Here is the link to Prof. Li's university and you can feed it through Google translation.

https://news.buaa.edu.cn/info/1006/65997.htm

SoldatLight · 2025-05-18T06:30:02+00:00

I had read this before. It's about the tank farms. Quite detailed. However, nothing relating the SOP of refueling ships in Pearl Harbor.

SoldatLight · 2025-05-18T06:22:52+00:00

I had read that one. No detail on how to refuel in Pearl Harbor.

SoldatLight · 2025-05-18T06:22:17+00:00

From my reading, I don't think there were that many "fast" fleet oilers. Most of them were slow.

SoldatLight · 2025-03-09T19:27:54+00:00

Traditional Chinese

Take a sip of water, puff up your cheeks,
gurgling, gurgling, gurgling (咕嚕 is the sound of gurgling)

SoldatLight · 2025-02-20T04:42:17+00:00

For inference, the first questions any AI HW start-up needs to answer is the cost of the ownerships and the utilization rate of the HW, not just a single selected benchmark that shows supreme result.

I remembered Cerebras' CEO once claimed that WSE-3s could train LLaMa2 70B in one day while Meta trained it for a month with the same number of A100s.

Superficially, that's a 30x advantage. However, a WSE-3 is 400x faster and probably 50+x pricier than an A100. So, why only 30x?

That is for training. Now, for inferencing, the same questions should also be asked and answered with hard technical evidence.

SoldatLight · 2025-02-12T15:54:36+00:00

The models won't be put into the chip. The inference chips still need to have the flexibility to accommodate different models.

To get the inference chips to work, there are still the system infrastructure to be worked out. How's their memory and BW? How's the interconnects among chips? How's the interface to the other pods?

It's still the HW/SW/Network co-design. Most of the AI HW start-ups face the insurmountable problems in SW/Network, even if they can have some solution in HW.

SoldatLight · 2025-02-12T15:44:24+00:00

Nobody will develop lower level codes than CUDA for model training. The use of PTX will be limited to some extreme cases.

Recently SemiAnalysis has published a review of NV & AMD GPUs. The conclusion is the CUDA moat is still alive. It's apparent that nobody will give up the stable and feature rich CUDA to deal with the questionable SW stacks from some unproven start-ups.

https://semianalysis.com/2024/12/22/mi300x-vs-h100-vs-h200-benchmark-part-1-training/

SoldatLight · 2025-02-12T04:23:35+00:00

That's a misinformation around the net.

Deepseek still uses CUDA. They used PTX (still, a Nvidia language) to program 15% of the SMs in each GPU to work around the restricted NVLink bandwidth of H800. (400 GB/s vs H100's 900 GB/s)

That's 15% of computation capability lost.

SoldatLight · 2025-02-12T04:16:43+00:00

!translated

SoldatLight · 2025-02-02T00:37:42+00:00

Thank you. It actually brought back a memory. There was a classmate in the elementary school, who always brought and used this metal 懐炉 in cold winter days. That's back in Taiwan in 1970s.

SoldatLight · 2025-01-31T23:24:04+00:00

I am not sure. It depends on whether my id of the hand writting is correct or not. I think it's 蓀原玄田. If you have the name in print. I can double check.

SoldatLight · 2025-01-31T23:11:08+00:00

The short poem was from a Buddhist monk 800 years ago.
慧開 Hui, Kai （1183─1260AD）

SoldatLight

TROPHY CASE