visarga

13 ms·

271.
by visarga 7mo ago
> No amount of platforming will fix this. The problem with social media is precisely the platform, it ranks what keeps people addicted, seeing more ads. Creators conform to the Algorithm and produce slop to capture some of that scarce at
272.
by visarga 7mo ago
> the input data is usually pretty terrible. It's based on either similarity I found luck just using a LLM to chat about my tastes, what I like, what kinds of songs I want to discover ... it does a good job and is able to also give
273.
by visarga 7mo ago
> I build with Claude Code daily and the context decay is real by the end of a long session it starts forgetting decisions we made earlier I generate task.md files before working on anything, some are short, others are super long and wit
274.
by visarga 7mo ago
I like you can ask Grok to search the social graph and comments. Hacker news also has one semantic search engine ( https://hackersearch.net/ ), reddit has none and it's a pity.
275.
by visarga 7mo ago
> Though it’ll be interesting to see what happens to ChatGPT and the like once the amount of quality content for them to consume slows to a trickle. Creative loop moves inside the agentic chat room, where we do learning, work, art, resea
276.
by visarga 7mo ago
Yes pretty much my workflow. I also keep all my task.md files around as part of the repo, and they get filled up with work details as the agent closes the gates. At the end of each one I update the project memory file, this ensures I can al
277.
by visarga 7mo ago
I built something like this in 1993, it was used to design layouts for DOS apps and headers for printed listings. Imitating the BorlandPascal and Novel TUIs of the day
278.
by visarga 7mo ago
It helps but a LLM could still code a destructive command (like inlined python -c scripts) you can't parse by rules and regex, or a gatekeeper LLM be able to understand its implication reliably. My solution is sandbox + git, where the
279.
by visarga 7mo ago
> My only caution is that good writers and LLMs look very similar, because LLMs were trained on a corpus of good writers. People moving to careless writing for authenticity while good writing will be considered AI? funny. We want authent
280.
by visarga 7mo ago
Luck. RNNs can do it just as good, Mamba, S4, etc - for a given budget of compute and data. The larger the model the less architecture makes a difference. It will learn in any of the 10,000 variations that have been tried, and come about 10
281.
by visarga 7mo ago
> Whenever I see claims about AGI being reachable through large language models, it reminds me of the miasma theory of disease. Whenever I see people think the model architecture matters much, I think they have a magical view of AI. Prog
282.
by visarga 7mo ago
I did something similar - I put 18 years of comments on reddit, HN, slashdot, and 3 years of LLM chats in the system. I ended with a similar conclusion - it was less useful than I expected. My intent was to do RAG over my corpus, have a LLM
283.
by visarga 7mo ago
I thought it was at most a monetary fine, do people go to jail for copyright infringement? But you seem to want to own all the air around your work, the ground beneath it too. Nothing can exist around it, so a creative person would do bette
284.
by visarga 7mo ago
Your project, while interesting as an approach, is orders of magnitude more complex than the proposition here - which is to rely on agents skills with file systems, bash, python, sed, grep and other cli tools to find and organize data, but
285.
by visarga 7mo ago
AI work creates surplus, we eat that away by specializing and becoming more dependent. Work doesn't stop, it becomes higher stakes, we depend on each other and AI now.
286.
by visarga 7mo ago
> I've spent decades building up and accumulating expert knowledge and now that has been massively devalued. Any idiot can now prompt their way to the same software. Do you like the craft of programming more than the outcomes? Now
287.
by visarga 7mo ago
If you got access to a working prototype of a software, you can use it for differential testing. So you got unlimited tests for free.
288.
by visarga 7mo ago
> It is there to reduce our agency, to make it easier to fire us, to put us in even more precarious position, to suck even more wealth from those that have little to those that have a lot. You could say this is the story of society, it m
289.
by visarga 7mo ago
Stochastic Parrots hits back! another author thinks LLMs only reproduce. If that were so we could have used `cp` for free
290.
by visarga 7mo ago
> In that situation, they give the (wrong) answer that sounds the most plausible. Not if you use web search or deep report, you should not use LLMs as knowledge bases, they are language models - they learn language not information, and a
291.
by visarga 7mo ago
> because it has nothing to pull from? Chat rooms produce trillions of tokens per day now, interactive tokens, where AI can poke and prod at us, and have its ideas tested in the real world (by us).
292.
by visarga 7mo ago
> It's crazy to me that you'd trust the output of an LLM for that. It's something where if you do it wrong it could cause major damage, With critical tasks you need to cross reference multiple AI, start by running 4 deep r
293.
by visarga 7mo ago
> These news sites run ads that are borderline gore, disturbing images promoting snake oil weight loss or skin care treatments And that doesn't raise an eye brow, but well worded AI articles based on sources is described as slop
294.
by visarga 7mo ago
Looks like another bullet machine, the cheapest way to present a response.
295.
by visarga 7mo ago
You have 2 paths - code tests and AI review which is just vibe test of LGTM kind, should be using both in tandem, code testing is cheap to run and you can build more complex systems if you apply it well. But ultimately it is the user or usa
296.
by visarga 8mo ago
It's for unstructured inputs, text and images, where you need to extract specific features such as education level, experience with various technologies and tasks. The trick is to choose those features that actually matter for your com
297.
by visarga 8mo ago
> In 2030, how is Anthropic going to keep Claude "up-to-date" I think the majority of research, design and learning goes through LLMs and coding agents today, considering the large user base and usage it must be trillions of to
298.
by visarga 8mo ago
An unqualified statement, the user has copyright over the elements they provide. In an image if they make manual edits for example, those are protected. In a modern agentic codebase the code itself is least valuable, what counts more are th
299.
by visarga 8mo ago
A nice way to use traditional ML models today is to do feature extraction with a LLM and classification on top with trad ML model. Why? because this way you can tune your own decision boundary, and piggy back on features from a generic LLM
300.
by visarga 8mo ago
Yes, it should remain part of the commit, and the work plan too, including judgements/reviews done with other agents. The chat log encodes user intent in raw form, which justifies tasks which in turn justify the code and its tests. Bot

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