aabdi
Joined 7 years ago
Joined 7 years ago
That's me for like 3-4 years or so b4 AI. Did i really build anything? IDK tbh.
Code was like max 20% of the time.
Same thing with Claude really.
There’s no reward for prosocial in llm rl as compared to other targets.
Humans have it since prosocial and others have evolutionary reward signals that do.
I've done this sort of with comfyui/same agent factory stuff, but the verification loop only works for models like fable as planner/writer, with gemini as verifier for like a very short movie. Sub 3-5 mins. After that you burn through million tokens.
Can't go too low fidelity audio/video or it craps out. Too long video and it loses consistency. Look at only snippets, it lacks global consistency, etc.
The people want better for themselves, similar to people here. Since this is speaking about people in Sulawesi, they don't really have any money or work there. It's largely jungle, mining, farms.
I'll just give an example with some of the people i spend time with whenever I'm in Indonesia.
Eko lives in his village. He largely has no real job or work. He catches fish sometimes. Different ways. Sometimes with rod. Sometimes he shimmies an air tank with an air pipe underwater and spears them. He might get bends and die of the pains of it. I told him he shouldn't fish like that, but he still does it.
You see, Eko does crazy things because wants his two kids to live better than him. He wants them to live more like those folks in Jakarta, with air conditioning and sanitary toilets. Eko thinks his life isn't great, but he makes do with it. He largely does not have a vehicle besides a weak scooter, he brings his kids together with. His hut is poor, and he built it himself with concrete and bamboo. No electrical. He defecates into a hole toilet he learned to build from his friend. Sometimes he defecates into the river.
Eko's father died recently. The father likely died of poor treatment. The hospital is about 2 hours away in the main city. The hospital is poorly run. Its red lights make you feel ill; there is barely any materials or equipment.
Sometimes he thinks he needs to bomb something to get more fish. It doesn't ever get him enough money because he needs a lot more than he does get from it. Even if his wife works on her tobacco farm, there is very little at the end of the month. Maybe his kids will die too in that same hospital. Some of my friend's kids died in similar fashion last year. Maybe an earthquake will happen again, and all the stuff that they've been doing will just be burnt away.
Poverty. It's uh, quite bleak.
Competitive with opus 4.8 but weaker than sol or fable. About 20x cheaper.
I think we experimented between 4096 and 8192 to measure p99 latency performance and that was the optimal as tradeoff.
Dagger was very nice for the newer services and the ones that used straight rx were like less hell
I agree with most of this except this. Think there’s some rose tinted glasses here or I’ve got bad luck over time.
Life before ai was bad as well. There wasn’t any one to explain to you anything! You had to figure it out yourself. The people either already left or was busy with something else.
No one wrote tests (to my standard). Most of the ops works was skipped. Docs were just not there. Nobody linted properly. Just bad mannnn
Go can.
There’s no equivalent competitor, it’s the best if u want to just write lots of undifferentiated code.
To caveat this if u want to run about 50 agents or so in parallel, all the typescript projects burn ur disk via node modules. The rust ones take forever to compile and burn too much compute
There’s no equivalent competitor, it’s the best if u want to just write lots of undifferentiated code.
What’s the problem then?
Use a cheap ds4 or Luna and do the second model net net per one shot best case you save couple dollars per?
There’s a measurable performance tradeoff versus gqa so there’s reluctance.
For the most part though the new deepseek v4 tech is hca and mhc and people are still catching on like with moe and rl. Wait for 6 12 months, minimum time for next pre train.