deoxykev

Seems like the root cause here was human error during EMudhra's key generation ceremony process.

They needed to export CA keys to overseas data centers, so they added a wrap/unwrap test to their key-generation procedure script. Somehow that generated a second set of weak (test?) keys from the CryptoServer Se-Series Gen2 HSM.

Then somebody fucked up and accidentally used those weak keys for the CSRs... then their root and Sectigo signed it. And it shipped.

That's why the private keys are literally one byte.

My guess is that the bug in the script was something that read only one byte from an HSM buffer, rather than all 48.

https://bugzilla.mozilla.org/show_bug.cgi?id=2083449#c11

Yes but only for detecting 5ghz WiFi cameras (actively streaming). If it’s 2.4ghz WiFi, or Ethernet wired, or it’s just recording to an sd card, it can’t be detected using the quadRF.

I live there in that city. There are hardly any homeless at all here. Not like other cities at least. I could see it being a major problem in other places.

How about LLM chat over DNS? https://github.com/accupham/llm-dns-proxy

And it typically works on captive portals too before payment.

Meta-commentary always leans nerdier.

Curious to hear what kind of work you do. Because there are definitely fields where productivity as 10x'd because of AI tools.

HTMX and shoelace is an awesome combo. Super fast to prototype things and tweak as needed. Being able to copy paste snippets and directly inject data in a straightforward way is a nice way of working. It limits cognitive overhead so you can focus on the domain logic rather than fight javascript dependencies.

Don't forget to finetune the reranker too if you end up doing the embedding model. That tends to have outsized effects on performance for out of distribution content.

Interesting, I had never heard about min-p until now. From what I understand, it's like a low-pass filter for the token sampling pool which boosts semantic coherence. Like removing static from the radio.

Do you have any benchmarks of min-p sampling with the new reasoning models, such as QwQ and R1?

Yeah, there is a clear bottleneck somewhere in llama.cpp. Even high end hardware is struggling to get good numbers. The theoretical limit should be higher, but it's not yet.

Benchmarks: https://github.com/ggerganov/llama.cpp/issues/11474#issuecom...

I don't think autoregressive models have a fundemental difference in terms of reasoning capability in latent space vs token space. Latent space enables abstract reasoning and pattern recognition, while token space acts as both the discrete interface for communication, and as a interaction medium to extend, refine and synthesize high order reasoning over latent space.

Intuively speaking, most people think of writing as a communication tool. But actually it's also a thinking tool that helps create deeper connections over discrete thoughts which can only occupy a fixed slice of our attention at any given time. Attentional capacity the primary limitation-- for humans and LLMs. So use the token space as extended working memory. Besides, even the Coconut paper got mediocre results. I don't think this is the way.

The fundemental challenge of using log probabilities to measure LLM certainty is the mismatch between how language models process information and how semantic meaning actually works. The current models analyze text token by token-- fragments that don't necessarily align with complete words, let alone complex concepts or ideas.

This creates a gap between the mechanical measurement of certainty and true understanding, much like mistaking the map for the territory or confusing the finger pointing at the moon with the moon itself.

I've done some work before in this space, trying to come up with different useful measures from the logprobs, such as measuring shannon entropy over a sliding window, or even bzip compression ratio as a proxy for information density. But I didn't find anything semantically useful or reliable to exploit.

The best approach I found was just multiple choice questions. "Does X entail Y? Please output [A] True or [B] False. Then measure the linprobs of the next token, which should be `[A` (90%) or `[B` (10%). Then we might make a statement like: The LLM thinks there is a 90% probability that X entails Y.

My take: the distills under 32B aren’t worth running. Quants seem to impact quality much more than other models. 32B and 70B unquantized are very good. 671B is SOTA.

8x 3090 will net you around 10-12tok/s

Have you hit any non-determinism errors keeping workflow state outside temporal?

Hey, I’m building agents on top of temporal as well. One of the main limitations is child workflows can not spawn other child workflows. Are you doing an activity for every prompt execution and passing those through other activities? Or something more framework-y?

Imhex is a really great frontend for Capstone. https://github.com/WerWolv/ImHex

Are you able to run 405B? 4Bit quant vram requirements are just shy of 192GB.

4 bit quants should require 85GB VRAM, so this will fit nicely on 4x 24G consumer GPUs, plus some leftover for KV cache optimization.

How does this compare to LayoutLMv3? Was it trained on forms at all?

Hi there, I would be interested in a chat about those back-office patterns and use cases. Could you send an email to a2V2aW4gQCBkZW94eSAuIG5ldA==

I use ansible to deploy and sync scripts, services, etc. I think it would work well for you use case as well.

Here is the list from the thread: --- 1. A Man Named Pearl

2. Once Upon a Time in Northern Ireland

3. Microcosmos

4. Crip Camp!

5. Keep The River On Your Right

6. All The Beauty And The Bloodshed

7. Harlan County USA

8. Stay on Board: The Leo Baker Story

9. Good Night Oppy

10. We Met in Virtual Reality

11. All That Breathes

12. Still

13. Can’t Be Stopped

14. The Amazing Jonathan Documentary

15. Searching for Sugarman

16. AKA Mr Chow

17. The Pigeon Tunnel

18. Little Richard: I Am Everything

19. I Know That Voice

20. Genghis Blues

21. Kings of Pastry

22. 20 Feet From Stardom

23. Stevie

24. Anvil: the Story of Anvil

25. Searching for Sugar Man

26. King of Kong

27. The Gleaners and I

28. Touching the Void

29. Cane Toads: An Unnatural History

30. 20 Days in Mariupol

31. Minding the Gap

32. How to Survive a Plague

33. Speciesism

34. Free Solo

35. Jim Allison: Breakthrough

36. Seven Up! series

37. Bowling for Columbine

38. The Fog of War

39. Rivers and Tides

40. Capturing the Friedmans

41. Spellbound

42. King of Kong

43. Crip Camp

44. Jesus Camp

45. Jiro Dreams of Sushi

46. Flee

47. Man on Wire

48. Queen of Versailles

49. The Thin Blue Line

50. Time Indefinite

51. The Gleaners and I

52. My Life as a Turkey

53. Happy People

54. Grizzly Man

A default key expiry of 3 days would be helpful here too, as it would mitigate the threat of someone compromising the endpoint and extracting secrets from browser history.

That’s a great idea, I think something like this would work very well as a installable PWA even.

This is cool. Do you mind me asking what videos you use it for?

Here’s a similar project, but for windows AD networks

https://github.com/byt3bl33d3r/DeathStar