visarga

3 ms·

61.
by visarga 20d ago
They just released Astra, claimed it is AGI. The slowdown begins immediately after OpenAI's jump.
62.
by visarga 20d ago
Some people type 100x more words than the final article just digging into a topic and turning it on all sides. The final article being generated tells you nothing of the size of the effort going in.
63.
by visarga 22d ago
It's like finding random hornet nests.
64.
by visarga 23d ago
> can match or exceed human cognitive abilities across a wide range of tasks If you go by definition AGI is not general, just "smart ape" shaped.
65.
by visarga 23d ago
It's not measuring AGI at all, it starts from human "core knowledge" so it is parochial. It is made of tests that still fail so by definition next version will also start low. Moving goalpost.
66.
by visarga 23d ago
Their definition of AGI is "when we can't invent any more tests where it fails"
67.
by visarga 23d ago
I'm doing the opposite - prose. And specifically for Claude the 4s - "simple short synthetic style"
68.
by visarga 23d ago
I care more about the recursive loop between execution and cost. Anything that executes - be it biological or artificial - incurs some costs. Those costs in turn impact what execution can follow. The gains pay for action, action produces ga
69.
by visarga 24d ago
it's called `agy` now
70.
by visarga 24d ago
I am often asking it to write in sss-style - "synthetic, short and simple style"
71.
by visarga 24d ago
It's so bad I made my own chat client for Claude, so I can attach steering prompts in conversation. They are applied just at the end, before the last LLM response, then removed and response kept.
72.
by visarga 24d ago
> when you increase thinking-effort, that seemingly increases response-length I use the /sss writing style - synthetic, short and simple - and it helps a lot.
73.
by visarga 24d ago
You can engineer loops that have it, but it depends on a case by case basis. Does your loop have strong validation? if it's all vibes nothing can stop it from diverging.
74.
by visarga 24d ago
> Good software will be good-er. Bad software will be nightmare fuel. We are talking about a moving target here ... they get better every few months, so I expect the super-LLMs from 2035 will write amazing code even with sloppy prompting
75.
by visarga 24d ago
> Prompt Processing (PP) 66.3 tok/s I got 400 pp tps on a 10k token input. Your numbers seem suspiciously low, maybe the input was too short to measure properly? And this dense 27B is slow, the MoE A3B models get to 1000 tps.
76.
by visarga 24d ago
Local is never cheaper than cloud because they can do batch inference, and that means you load model weights once to produce 128 tokens on 128 sessions in parallel not 1 token on 1 session like local models. Local models rarely get to high
77.
by visarga 24d ago
If you buy the computer specifically for inference it is more expensive than cloud, but if you had it anyway it's free.
78.
by visarga 24d ago
I took this thread and summarized it with Qwen3.6-35B-A3B, it had 1400 tps prefix and 60 tps completion. Very good performance. Using oMLX on MacBook M5 Pro 64GB.
79.
by visarga 1mo ago
I think AI won't make anyone rich by what it can do, but by what it still can't.
80.
by visarga 1mo ago
Only AI code is holy, video is sinful.
81.
by visarga 1mo ago
The cheaper it is to produce, the more daring it can be. Which is a good thing.
82.
by visarga 1mo ago
> As in, what work or enjoyment does someone actually get from this? Why do we look at art, watch videos/movies? I like to generate songs from obscure poems
83.
by visarga 1mo ago
I agree 10K LOC is too little, I was saying "a few 10,000's of LOC"
84.
by visarga 1mo ago
A pluggable loop with events and hooks.
85.
by visarga 1mo ago
Yes, a 15 year old code base written by hand obviously, not by a coding agent from the start. At the same size I only heard of AI generated projects reimplementing compilers and browser engines which come with amazing tests written by hand
86.
by visarga 1mo ago
There is a limit, after a few 10,000's of LOC ai projects start disintegrating and becoming unmanageable.
87.
by visarga 1mo ago
Funny you mention Chinese Room and LLMs in the same response, I would say LLMs proved Searle wrong, agents now make cutting edge discoveries and meaningful problem solving. They not lookup tables though and you need to pay for inference, so
88.
by visarga 1mo ago
AliExpress and Temu would refund you if you complained about a delivery. Zero risk.
89.
by visarga 1mo ago
> If you want to follow a process or a checklist you probably shouldn't use an LLM I like to externalize tasks as markdown files with checklists, they are still planned by agents but I can pass the plan around to judge agents and fi
90.
by visarga 1mo ago
I can't get an answer from Fable on "How does digestion work?" Used to straight out bail to Opus on this, now it's "Honing" and "Pondering" for 10 minutes on it. Then I get a bunch of "This respo

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