visarga

43 ms·

691.
by visarga 1y ago
Oh the web was full of slop long before LLMs arrived. Nothing new. If anything, AI slop is higher quality than was SEO crap. And of course we can't uninvent AI just like we can't unborn a human.
692.
by visarga 1y ago
Yes, we have the context - our unique lived experience, and are ultimately accountable for our actions. LLMs have no skin. They have no desires, and cannot be punished in any way. No matter how smart they get, we are providing their opportu
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by visarga 1y ago
When I see comments like yours I can't help but decry how bad was the "stochastic parrots" framing. A parrot does not hallucinate a better API.
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by visarga 1y ago
I like this approach. It's not that intelligence is in the brain or the model, and it should not be a noun. It is a process, a search process based on exploration and learning. Think of a river - the water carves the banks, the banks c
695.
by visarga 1y ago
I think intelligence is search. Search is exploration + learning. So intelligence is not in the model or in the environment, but in their mutual dance. A river is not the banks, nor the water, but their relation. ARC is just a frozen snapsh
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by visarga 1y ago
I think intelligence is search. Search is exploration and learning. So intelligence is not in the model, or in the environment, but in their mutual dance. A river is not the banks, nor the water, but their relation.
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by visarga 1y ago
> Managers and execs are workers, too--so if the AI really is so good, surely they should recuse themselves and go live a peaceful life One thing that doesn't get mentioned is AI capability for being held accountable. AI is fundamen
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by visarga 1y ago
The good thing about it is that being part of such a community feeds creative impulses towards doing projects with AI. It keeps AI forefront in our mind. Happens with all other specialized communities, like r/classicalmusic
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by visarga 1y ago
The way I see it is to use hindsight, not to come with predefined criteria. The criteria is usefulness of one LLM response in the interactions that follow it down the line. For example, the model might propose "try doing X", and I
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by visarga 1y ago
It's not about achieving AGI as a final product, it's about building a perpetual learning machine fueled by real-time human interaction. I call it the human-AI experience flywheel. People bring problems to the LLM, the LLM produce
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by visarga 1y ago
> everything we do online has, until this point, been free training to make OpenAI, Anthropic, etc. richer while cutting humans--the ones who produced the value--out of the loop I think on the contrary, who sets the prompts stands to get
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by visarga 1y ago
I built a graph memory MCP tool as well. I don't use triplets, instead I generate nodes. The node is composed of (id, title, text) and text can contain links inlined, like @45, referencing past nodes. So it can create both a node and i
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by visarga 1y ago
I foreseen this a couple years ago. We already have web search tools in LLMs, and they are amazing when they chain multiple searches. But Spegel is a completely different take. I think the ad blocker of the future will be a local LLM, small
704.
by visarga 1y ago
Results are modest, maybe 20-30% fewer training steps to reach target performance. This won't solve the problem of organic data exhaustion. We need 100x more data. They didn't test against actual language model pretraining, only t
705.
by visarga 1y ago
> AI is not good at forgetting. There is also a related feeling of fatigue with our own digital archives - photos, old writings. We like to save them but not to look at them. They evoke powerful and somewhat uncomfortable feelings. And o
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by visarga 1y ago
> By the medium directly engaging with the person and > Even though there's no person in the loop contradict each other. There is always a person in the loop, and the LLM is actually reacting to their messages, however wrong it t
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by visarga 1y ago
The main benefit is not that it made interoperability fashionable, or that it make things easy to interconnect. It is the LLM itself, if it knows how to wield tools. It's like you build a backend and the front-end is not your job anymo
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by visarga 1y ago
That has nothing to do with promoting progress and creativity, and all to do with privacy. Remember that photographs of people already have copyright protection. Why did they lump a privacy law into copyright? It's already dysfunctiona
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by visarga 1y ago
I would exercise a new vocabulary by generating many different phrases based on a limited number of known words, like the Pimsleur method. This teaches words in context, not isolated.
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by visarga 1y ago
Maybe not, I think they trained the model to be especially capable of MCP tool use, and generated data this way. Other formats and systems might be slightly worse, and the whole model would probably not handle such a diversity of tools if a
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by visarga 1y ago
Simple - you use MCP agents to update your MCP servers. I made 2 MCPs both 100% vibe coded. Keep the constraints - docs+tests - and you can regenerate the code as needed.
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by visarga 1y ago
MCP is really a great leap because LLMs orchestrate across a collection of tools instead of running a scripted flow. The most obvious example is deep research, where the LLM sends initial queries, reads, then generates new queries and loops
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by visarga 1y ago
One use case I see is to analyze codebases not just by reading the code, but by tracing the call graph and values that flow between function calls. Basically what I'd do if I wanted to know what a function does - put a break point and
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by visarga 1y ago
What I'd like - a coding agent with debugging capabilities. Walk the stack, inspect local variables and arguments, basically seeing what is really happening as opposed to debugging by prints and asserts.
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by visarga 1y ago
The advantage of MCP over fixed flows controlled from backend is that the LLM does the orchestration itself, for example when doing web searches it can rephrase the query as needed and retry until it finds the desired information. When solv
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by visarga 1y ago
> We don't need to know what a cone is The counter argument is that you can't zoom in and fix a specific bug in this mode of operation. Everything is mashed together in the same neural net process. They needed to ensure safety,
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by visarga 1y ago
The piece is from 2017, it was a time before LLMs, when AI was much more modest
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by visarga 1y ago
'patent guy Einstein
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by visarga 1y ago
LLMs don't care you have to maintain the code, they don't get any benefit or loss from their work and are unaccountable when they fuck up. They have no skin in the game. They don't know the office politics, or go on coffee br
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by visarga 1y ago
Computer use over screen and keyboard comes to the rescue

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