The problem here is people will beg for the opportunity and plead that they’ll take it seriously and it’ll be life changing and then ghost you at the first sign of actual work.
Finding a decent apprentice that won’t waste your time is a chore in and of itself
Do you consider yourself primarily an expert or a learner?
Genuinely asking, why is it important?
I have nothing to contribute; I’m scared of used drives. Interested to hear who folks have had good luck with though.
You actually have a lot of options in this space. You can take the prefill engine of just about any LLM and turn it’s transformer into a classifier by lobotomizing out the decoder. You can also use a diffusion model on single pass to surprisingly competent result.
If Jeff looks easy enough to deploy by all means start there, but don’t discount the idea if Jeff sucks; you have a lot of options.
You could (and probably should) use a system-one style inference system for spam classification. Much cheaper and the structured output means it’s impossible to go rogue and curl some malware or whatever. It can absolutely misclassify but its output is programmatically structured and just ranks a pre-selected set of output tokens.
In your case that’s
Spam
Not_spam
What’s remarkable is that they can extend the trace length without DDR5 timings shitting the bed lol. Can’t even put 4 sticks in most boards without spooky interposers.
MIT: I build my thing on top of your thing, it’s my thing now. I sell it, you have no rights.
GPL: I build my thing on top of your thing and your license forces me to distribute my thing under the GPL, including the source code.
There are legitimate arguments for both. Sometimes it sucks when proprietary things get built on top of MIT code but sometimes it takes money for innovation, and in the realm of code the world often benefits anyway by virtue of copycats or distillation.
+1 for pikvm. Expensive, but very powerful and very portable. My favorite part of them is their APL that lets me noninteractively, programmatically, interact with hardware buttons
Win 11 IOT enterprise LTSC already exists and doesn’t even require a TPM.
Unless this is a legitimate channel for regular users to get IOT enterprise LTSC, this is a non-story. The thing we want already exists, they just refuse to sell it.
I don’t understand what you’re proposing that nagios/chrck_mk doesn’t already do
You can absolutely train a nontrivial task model on a gaming gpu (image classifier, sound classifier, text model with a very structured input and output, etc). You can also post-train addon layers on top of existing open-weight models (LORA).
Ubuntu and bad updates
This is the only drama in your list I’m not familiar with already. What/when did they last break?
I would argue that Linux kernel scale basically doesn’t work. It is a huge barrier to would-be developers to get into. You might argue that’s a feature, but it’s pretty hard to argue that it doesn’t add a lot of friction to the process
Genuinely, pull requests being off platform without good integrated diff and merge conflict resolution tooling just doesn’t work at a certain scale.
Is this hopium or did they release a statement suggesting an 3.8 35b a3b was in development for release?
I’m not aware of any public frontier LLM provider that uses a static seed for inference. Meaning, even with an identical prompt and identical model you will not get the same output. Seeds should absolutely come back with the streaming metadata on requests imho, but they don’t in any api/harness I’m aware of.
my guess is something like this
https://330k.github.io/misc_tools/unicode_steganography.html
A model could hypothetically be trained to insert zero-width characters (I doubt any have though). But any other layer could also very trivially insert these codes. The inference engine could be designed to delay output streaming by however many tokens is required to embed their coding and ninja-insert them during the decode stream. A proxy between the inference engine could insert them. A harness could insert them. Hell, even the rendering javascript frontend in your browser could insert them.
Either the inference engine or proxy would be the prime target if they want to enable this on api responses as well as copy/paste from a chat interface. They could also do a combination of the above depending on final output mode.
You are definitely correct though that it’d be trivial to detect and strip by someone aware of it.
That’s only partially true.
Reddit is a/b testing api shutoffs that prevent up-to-date instances from working. There are forks that use logged in accounts or other methods to avoid detection but if reddit decides your private instance is a little too used (like mine) things are currently not working.
Imho the era of (not logged in) scraper-frontends is dead. They just haven’t given some of us the memo.