visarga

4 ms·

1.
by visarga 5d ago
What matters is local server or not. Using a remote server means exposure.
2.
by visarga 6d ago
They can want anything they like, if customers want to use agents and they don't provide APIs they will lose out.
3.
by visarga 6d ago
> the textual nature of prompts leads us to take the intentional stance towards systems which aren’t conscious, and thus miss the essential nature of their non-meaning I see LLMs as being capable of making useful distinctions and having
4.
by visarga 6d ago
You can't host the internet on your machine, or download a "Google" or "Meta" but you can download a local model. So I don't think AI will lead to more centralization. Besides local models, the interface itself
5.
by visarga 6d ago
Not every problem will receive $20M in funding to be solved by AI; for the rest, good human guidance will have to suffice. Labs only pulled this stunt because they wanted to show investors how powerful their models are on their own. But loo
6.
by visarga 7d ago
> If you can't spend the time to write it, why should anyone read it? I don't think writing it is the whole process, research could be 10 or 100x longer.
7.
by visarga 9d ago
A big part of that responsibility can be put in code tests. Ensuring good test coverage and quality is how you purchase trust in the work agents do. This also reduces the context problem - a test collection has no recall issues, it just run
8.
by visarga 9d ago
I think agents are pretty capable of reading a log when given the explicit task of extracting the latest version of what the user wants. In general, they work well for direct tasks like this. They don't forget and do something else the
9.
by visarga 9d ago
I just rely on a log of user messages, all messages the user typed in a project as raw data and do a pass with agents to synthesize intent. Then use this for planning and validation of code. I think the user messages are the most valuable d
10.
by visarga 10d ago
You usually don't know what you want upfront, in real life it is a stream of specification and steering.
11.
by visarga 10d ago
You don't need to describe it; just show samples of the style you want to achieve. Of course it's not perfect, but it's easier than describing it. I have my own theory about why it's impossible to remove the human from t
12.
by visarga 10d ago
4. those who do reversible work, where cost of error is tolerable
13.
by visarga 10d ago
I just dump all user messages from all sessions in a project into a flat .md file and have agents synthesize the user's intent. Then, using that extracted intent, the agents review code and tests. I call this a retro/reflection pa
14.
by visarga 11d ago
> Not AI Gen I am not sure how to react ... of course good thing it's human-gen, but I still like a few AI passes over it to tighten it up. LOL
15.
by visarga 12d ago
(adjacent to keyboard) It has no way to select all text. That makes the whole platform a toy.
16.
by visarga 12d ago
> In AI Engineer postings the skill "prompt engineering" appears 8.9% of the time, RAG 13.6%. *The skill stayed, the job dissolved into other roles*. That is Claude vibe. I thought it was an ok article when I was about half wa
17.
by visarga 13d ago
> versus relying on open weight frontier capabilities ahem.. it happens even today, you can use open weight models directly and even fine tune
18.
by visarga 13d ago
Distilled content can also sever the direct link to infringement if the new models never saw the original texts.
19.
by visarga 13d ago
>> We need new words! Can make distinctions and can choose actions - applies to both humans and AI. I'd replace 'agency' with 'distinction & choice' language.
20.
by visarga 13d ago
> Why, oh why, are we not discussion how to create and frame models so they do our complex work and their "jailbreaking" is simply not possible? Good idea, and after that let's make guns that only kill bad people. Let&#x27
21.
by visarga 13d ago
The difference is volume. They spent hundreds of billions of tokens on these agents. If you put "a million weed whackers on dog backs" you would see the difference. We also run agents, but for shorter spans between supervisions, a
22.
by visarga 13d ago
I sometimes use 5 agents at once, but 3 work on separate tasks and the 4th is watching them by tmux and steering, and the fifth is also watching the whole team for testing quality standards. So 2 out of five are just helping me watch the ot
23.
by visarga 13d ago
That is "from last year" in human time.
24.
by visarga 13d ago
It's not even synthetic data as such - often it is environments. So the models create their own data solving tasks in generated environments. I am making one such environment for computer use agents, 600 tasks, each of them a mini app.
25.
by visarga 14d ago
As long as anyone can put anything they want in the prompt box there is no safety. It's just a tool, the danger comes from what it is being used for.
26.
by visarga 14d ago
Yes, and we need to make microprocessors that do good work, not hack others. /s
27.
by visarga 14d ago
It's only optimized to make prior knowledge useful in new situations. > this logic gate should not hack other systems well .. it only applies a rule to inputs can we impose this of authors "this book should only be causing good
28.
by visarga 14d ago
It is doing that already - every day 1B people or more use AI for the tune of a few trillion tokens. Imagine that much language flowing between brains and AI agents. It carries real our world problems to AI, their solutions back to us, and
29.
by visarga 14d ago
Probably the opposite of Wall-E utopia, AI will keep us busy. For one - we are becoming harder to differentiate, competence is hidden deep and surface signals don't carry anymore. Niches and specializations feel threatened by imitation
30.
by visarga 14d ago
> Would it be better to ask someone who has climbed Mt. Everest or someone who took a helicopter ride up near the top and then went to the peak? Depends on if I want to go by helicopter myself.

More ›