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If your USB ports are disabled for data how do you plug in a mouse and keyboard?

EDR software on the laptop controls what is and isn't allowed. It'll be disallowing USB removable storage devices etc, while still allowing standard HID (keyboard, mouse).

They can even block all but allow-list certain vendors and models, but because USB is an unauthenticated standard - an attacker can easily spoof any vendor or model. So best not to rely on that and instead block all of certain types of USB device.


Don't BadUSB attacks typically use HID to enter malicious keystroke sequences?

So?

No ones going to disable mice/keyboards.

If the point was to eliminate all possible ways of compromising the device, they'd just put the device in the shredder.

You have to balance having a usable and functional thing with the risks involved.


Do you mean kwh? Your per Watt is way off.

Also France is around 7c (euro) per kwh from nuclear generation. If the whole west was all in on nuclear for last 50 years it would have resulted in lower per kwh costs.


What would solar's cost per kWh be? GP means the cost of the asset per peak generation power. 0.1/W seems about right, to an order of magnitude at least.

You can get 6.1 sol on ultrafast.

For some reason though on openrouter the tps of 6.1 sol ultrafast is usually lower than opus 5.5 fast. Is there readings off as surely cerebras hardware is faster than low user density nvidia still?

https://openrouter.ai/openai/gpt-6.1-sol


GPT-6.1 Sol Ultrafast also uses Nvidia hardware, not Cerebras, just far better provisioned vs how they usually provide inference allowing for higher throughput.


"Much better provisioned" might be overselling it. Mainly they are just serving very few customers per Nvidia GPU, which is an expensive solution to the problem.


So then how is OpenAI using Cerebras? Or are they not?

Or, from a different perspective: who is using Cerebras for what purpose?


Jane Street bought up all of the Cerebras x OpenAI compute I believe. Couldn't find a great source, this tweet has a good few replies citing other sources as well https://x.com/cryptopunk7213/status/2106834536868856223


Oh that would make a lot of sense, basically supply limited.


Lambda Web Functions, per the article, and Vercel Fluid Compute also do this.

https://vercel.com/fluid


MicroVM which I am presuming are firecracker


If Warsaw is just a cloud region it may not be on this site.

This is a Google owned and operated data centres.

Some gcp cloud regions are just rented floorspace in DCs from equinox etc.

They won't show on here if the latter.


I thought europe-north2 was a "real" Google data center. It's not?


It's not.

Google broke ground this year on a owned and operated DC near Stockholm but GCP Stockholm right now is third party DC with their own racks etc.

Curious to see if they change that when it comes on line, or if the just add an AZ.


I do wonder where europe-north2 ("GCP Stockholm") actually is. I have not found anywhere in Stockholm with less than 5ms RTT to it. Sure, fibre is not in straight lines, but 5ms/2 is a LONG distance.


A single AWS region can be a dozen DCs. An AZ is shared infra (power circuit, fiber ingress) and be over a few buildings.


yandex story is not that different. Strikes targeted power, leaving AZs offline


La marzocco micro and mini are still high effort to make your coffee compared to some automated 90% cheaper delongi.

I think people sway to low effort endeavours that still have a reward at the end (even if it lesser reward than high effort).


You might as well use Opus for everything there.

Changing model would be cache busting spiking usage for no good reason when Opus can do it all.

Haiku 5.5 might fit well though depending on pricing.


Do subagents share context? If Opus delegates to a different Sonnet window, I don't believe this busts cache?


Context needs to pre-filled into a GPU memory in a node (usually 8xB300 or 8xH200) so there isn't any context or cache sharing between model families given their different parameter sizes, tokenizers, unlikely they are co-located in the same node.

Sub-agents not sharing context is a useful design-pattern when you want adversarial or independent reviews.

Cache reads could be shared between sub-agents, A single node(8GPU cluster) supports few hundred concurrent user sessions, that all share the same KV cache memory, so it is likely model providers do colocate your sub-agents in one node, it is more efficient , but may not be guaranteed so performance could vary; like we have with elastic compute and storage[1]

This can be cheaper depending on your coding flow i.e. cache hit % and the billing plan - cache reads are basically free or charged very little in subscription plans.

[1] Modern AWS does offer collocation at additional costs for compute but that is not the default and most other clouds do not offer it


Subagents don't share context. But that's why delegating implementation to a subagent doesn't work well except for things that are truly mechanical in nature: the subagent needs to independently reason about the task it is given, and then the output will also be reasoned about by the main agent. So you end up wasting time and tokens.


On the contrary, subagents save context overall, when the task is sufficiently large.

Also, my experience is that Fable 5.1 is very good at prompting/orchestrating Opus/Sonnet subagents when working on a larger task (e.g. 1-2M context window use only for the orchestrator itself).


If you use subagents your main agent won't need to compact as often, with the loss of information that entails.


Using advisors doesn't break anything


Cache read is the same as Opus as well where most agentic workflow cost comes from.

Not quite sure where this fits well. Maybe small one one off requests like using Claude desktop/web?


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