AI consistently places animated objects behind a blur object which causes the browser to constantly repaint. Google's ai mode introduced one, some other websites clearly vibe codes included them too.
At first it confused me why my GPU usage spiked and fans started blowing harder, but now I see it is a common mistake that AI makes but no one tests properly. It is possible a human can make this mistake but I sheldom experienced this ever in my life until now.
I run 240hz monitors, and that meant the browser was trying to do 240 repaints per second. Blocking it with unlock origin is the only way. Ridiculous
I don't think it's going to be a disaster, doing nothing is not quite a disaster when the AAA games sector has been ticking over like this for the past 10 years or so.
The law is worded so that this does extremely little even if fully passed by CA's legal system due to the very broad exceptions. Exactly as lobbyists want it.
Makes great headlines for SKG while doing pretty much nothing material for them though.
When ctf organizers attempt to make a challenge "harder", I find they push the challenge into a more "guessy" state. Instead of proving skill, you basically need to guess some obscure or random step in the puzzle that the challenge is meant to give you. It is one of the most common problems with any puzzle based challenge system.
Yeah, but we have AI now, we don't need our blog posts to over explain or state what it all means to general audiences.
The author name-drops a bunch of CTF events hosted by a variety of independent organizations and name-drops well-known teams.
To help everyone, this Capture The Flag is specifically Cybersecurity adjacent, there is a Wikipedia article on it as the top Google search result for me when searching "CTF". This is why the acronym is used, because searching for the full will get you to the wrong "sport" vs the cybersecurity one.
I don't want to explain what a CTF is. look at the Wikipedia article. It is there for a good reason.
Just look at deepseek V4, this preview model uses only 8 GB for 1M token KV cache(the context). It's insanely efficient already. It's just that most models that are coming out are barely catching up with technical breakthroughs.
Deepseek are pioneers.
Unfortunately V4 is not trained for most real world usage, it is mainly for world general knowledge.
I tried over 20 variations of different system prompts.
Once I changed my tool to expect the colon, it also felt like it was running/calling tools faster, but I need to do a larger test to be sure.
I have a 1660ti and the cachyos + aur/llama.cpp-cuda package is working fine for me.
With about 5.3 GB of usable memory, I find that the 35B model is by far the most capable one that performs just as fast as the 4B model that fits entirely on my GPU.
I did try the 9B model and was surprisingly capable. However 35B still better in some of my own anecdotal test cases.
Very happy with the improvement. However, I notice that qwen 3.5 is about half the speed of qwen 3
I have personally seen a rise of LLMs being too lazy to investigate or do some level of figuring out things on their own and just jump to conclusions and hope you tell them extra information even if it is something they can do on their own.
At first it confused me why my GPU usage spiked and fans started blowing harder, but now I see it is a common mistake that AI makes but no one tests properly. It is possible a human can make this mistake but I sheldom experienced this ever in my life until now.
I run 240hz monitors, and that meant the browser was trying to do 240 repaints per second. Blocking it with unlock origin is the only way. Ridiculous
reply