Spyke

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Where are the smart range token limits for various model sizes?

It depends on the model. For newer stuff, and Qwen3.8 27b specifically, its Qwen Sparse Attention/Gated DeltaNet architecture does much better than a lot of previous models.

The old rule of thumb was that the middle of the context window can get lost in old models, but Qwen3.8 27b and Qwen 3.8 Flash Next work fine, even when using most of the 262k native tokens of context… but this long context requires 8GiB of VRAM just for the context, and this is with FP8 KV quantization.

I still don’t trust much more than 128k though, and most harnesses automatically compact if a request would exceed a certain threshold (e.g., OpenCode is the higher of 15% of max or 16k tokens for its buffer).

For smaller models 16-32k is probably fine unless you’re using a model that is extremely old, like llama3 or phi 2.5. But you’re going to struggle to get anything other than a simple chatbot with very short conversation on a 4GB card. Maybe light translation or document work, but don’t expect anything useful in coding or agentic work.

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Thousands of Linux systems infected by stealthy malware since 2021

Shouldn’t be this hard to find out the attack vector.

Buried deep, deep in their writeup:

RocketMQ servers

  • CVE-2021-4043 (Polkit)
  • CVE-2023-33246

I’m sure if you’re running other insecure, public facing web servers with bad configs, the actor could exploit that too, but they didn’t provide any evidence of this happening in the wild (no threat group TTPs for initial access), so pure FUD to try to sell their security product.

Unfortunately, Ars mostly just restated verbatim what was provided by the security vendor Aqua Nautilus.

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GrapheneOS defends use of AI for coding

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The crux of that article is buying into Heidegger‘a definition of a tool, specifically, “thing that lets you do something you wouldn't otherwise have been able to.” If you disagree with that premise, the article doesn’t hold up.

Tools aren’t about letting you do something you would otherwise not have been able to do, they are simply a force multiplier for capability or efficiency. You still need knowledge and skills to do the thing.

I am not a carpenter. My knowledge and skills are near zero. This multiplied by any number is still damn near zero, and I have no idea about the culture, safety, or history of carpentry. I’m not stupid enough to jump right into using an lathe without a lot of research or someone to guide me, because I’m not a fucking moron.

People with programming knowledge and skills using AI will eventually figure out a workflow that works. Laypeople using AI to vibe code? They’re probably fucking morons. Sure, maybe even most of the time, it will be fine. But eventually, someone is going to be degloved.

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I'm sure people fall for this type of greenwashing all the time...

Explain your thought process here, how did you arrive at the larger bottle being 90% more detergent? It’s EXPLICITLY clear that the concentration is higher in the smaller bottle.

You could complain about the form factor or lack of precision in dosing loads using the higher concentration, but “detergent” is mostly water, which they clearly said they reduced by 75% (same solute, with less water/solvent = higher concentration).

Quick search and going by what it says on the label, the cost per load has not significantly changed, a little more than half a penny’s difference:

Ultra Concentrated (left) $15/60 loads = $0.25/load https://mrsmeyers.com/collections/laundry/products/ultra-concentrated-laundry-detergent-rain-water?variant=50673207640338

Standard (right) $18/74 loads = $0.2432/load https://mrsmeyers.com/collections/laundry/products/ultra-concentrated-laundry-detergent-rain-water?variant=50673207640338