There is news - from 2h ago - talking about Fortnite and EAC userspace coming to Linux soon. As someone not too knowledgeable on Linux kernel anti-cheat games, I wonder: is this big news or just a farce? I use CachyOS…
I’m curious too. We need to see 1b+ numbers or else it just seems like we’re leveraging compression here, which is great but it’s hard to understand why it’s novel and why it’s the best solution no contest.
Definitely publish it! I’ll be following closely! 100M seems a bit too low to turn heads, but cool project nevertheless. Always exciting to see open source observability tools pop up!
I currently manage 50m active series and it’s brain dead easy using Mimir (which can also easily do 100-200m). That being said, perhaps this Parseable project is much more efficient (RAM) in storing that 1b samples…
Use Tether!!
Yep I run `claude remote-control` as daemons (systemd/launchctl) on whatever paths/repos I wanna be able to create a session from on-to-go. Works really well and is a great use case for work laptops. Same shell, same…
notes/docs/wiki is a great use case
Sol 5.6 Ultra doesn't seem worth it because its long-horizon task scaling is not that good. Remove the one thing that differentiates these 2 SOTA models (long-horizon task scaling) and you're left with assessing the raw…
It's great, don't get me wrong, but so is Fable. I'm just comparing the long-horizon task performance between the two at the same or similar effort levels. Given the 50% discount on Sol and how smart it is, yeah it's…
*The "Max" I referred to was the plan tier, not the effort level btw For small tasks, you can just use something like low or medium effort and it can usually avoid mistakes; after all, the model will test the code…
Sol is way too eager to hone in on small details and ends up with massive over-engineering. Fable does it too - to be fair - but noticeably less. After extensively using both on Max 20x plans, I've concluded that Fable…
for example, models running at like 100-150 tokens/second (or faster!) vs 15 t/s (fable/sol are ~60 t/s, and OpenAI just announced their Cerebras partnership(?) for "ultrafast" mode of 750 t/s) models aren't able to run…
Apple is already doing this... they worked with Gemini to distill the model into a smaller one that fits on your phone. If you have iOS 27 Beta, you're already using this
There is news - from 2h ago - talking about Fortnite and EAC userspace coming to Linux soon. As someone not too knowledgeable on Linux kernel anti-cheat games, I wonder: is this big news or just a farce? I use CachyOS…
I’m curious too. We need to see 1b+ numbers or else it just seems like we’re leveraging compression here, which is great but it’s hard to understand why it’s novel and why it’s the best solution no contest.
Definitely publish it! I’ll be following closely! 100M seems a bit too low to turn heads, but cool project nevertheless. Always exciting to see open source observability tools pop up!
I currently manage 50m active series and it’s brain dead easy using Mimir (which can also easily do 100-200m). That being said, perhaps this Parseable project is much more efficient (RAM) in storing that 1b samples…
Use Tether!!
Yep I run `claude remote-control` as daemons (systemd/launchctl) on whatever paths/repos I wanna be able to create a session from on-to-go. Works really well and is a great use case for work laptops. Same shell, same…
notes/docs/wiki is a great use case
Sol 5.6 Ultra doesn't seem worth it because its long-horizon task scaling is not that good. Remove the one thing that differentiates these 2 SOTA models (long-horizon task scaling) and you're left with assessing the raw…
It's great, don't get me wrong, but so is Fable. I'm just comparing the long-horizon task performance between the two at the same or similar effort levels. Given the 50% discount on Sol and how smart it is, yeah it's…
*The "Max" I referred to was the plan tier, not the effort level btw For small tasks, you can just use something like low or medium effort and it can usually avoid mistakes; after all, the model will test the code…
Sol is way too eager to hone in on small details and ends up with massive over-engineering. Fable does it too - to be fair - but noticeably less. After extensively using both on Max 20x plans, I've concluded that Fable…
for example, models running at like 100-150 tokens/second (or faster!) vs 15 t/s (fable/sol are ~60 t/s, and OpenAI just announced their Cerebras partnership(?) for "ultrafast" mode of 750 t/s) models aren't able to run…
Apple is already doing this... they worked with Gemini to distill the model into a smaller one that fits on your phone. If you have iOS 27 Beta, you're already using this