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Their models are open weights, and they are supported in ollama. You can run locally if you have sufficient hardware.
https://hongkongfp.com/wp-content/uploads/2021/11/brave_udRs...
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Plus Volkswagen and Subaru in the last few weeks ...
Plus Volkswagen and Subaru in the last few weeks Both Volkswagen and Subaru have leaked his DNA in the last few weeks? Dude gets around.
open exposed clickhouse is this decade's open exposed elasticsearch so common in the past
This is probably an incredibly stupid, off-topic question, but why are their database schemas and logs in English? Like, when a DeepSeek dev uses these systems as intended, would they also be seeing the columns, keys, etc. in English? Is there usually a translation step involved? Or do devs around the world just have to bite the bullet and learn enough English to be able to use the majority of tools? I'm realizing no…
It might seem less credible to encounter English in a place where it’s less expected, but think of it this way: would a Yandex-developed ClickHouse database be adopted by Chinese devs if everything in it were written in Russian? There is some merit in asking your question, for there’s an unspoken rule (and a source of endless frustration) that business-/domain-related terms should remain in the language of their orig…
This is totally expected when you use AI to build your infrastructure.
Interesting to note: - Dev infra, observability database (open telemetry spans) - Logs of course contain chat data, because that's what happens with logging inevitably The startling rocket building prompt screenshot that was shared is meant to be shocking of course, but most probably was training data to prevent deepseek from completing such prompts, evidenced by the `"finish_reason":"stop"` included in the span attr…
> but most probably was training data to prevent deepseek from completing such prompts, evidenced by the `"finish_reason":"stop"` included in the span attributes As I understand, the finish reason being “stop” in API responses usually means the AI ended the output normally. In any case, I don't see how training data could end up in production logs, nor why they'd want to prevent such data (a prompt you'd expect to se…
https://platform.openai.com/docs/api-reference/introduction
Right there in the docs:
> Now that you've generated your first chat completion, let's break down the response object. We can see the finish_reason is stop which means the API returned the full chat completion generated by the model without running into any limits.
Regarding how training data ends up in logs, it's not that far fetched to create a trace span to see how long prompts + replies take, and as such it makes sense to record attributes like the finish_reason for observability purposes. However the message being incuded itself is just amateur, but common nonetheless.
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Hundreds of thousands. My employer alone probably has 1000.
No. I don’t think so. I think if you took many engineers and sat them at a computer and asked them to stand up a whole dev staging prod system they wouldn’t be able to do it. I certainly would not, or it would take me a significant amount of time to do properly. I have been a full stack dev for 10 years. Now take that one step further to someone whose only interaction with a development is numpy, pandas, julia, etc……
There are many in the software engineering field which could not satisfy a request of this nature, for any reasonable form of "asked them to".
