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Nanobot: Ultra-Lightweight Alternative to OpenClaw

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Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#91

Post by [deleted] »

gdhkgdhkvff wrote: post #83
yberreby wrote: post #49

Watching the OpenClaw/Molbot craze has been entertaining. I wouldn't use it - too much code, changing too quickly, with too little regard for security - but it has inspired me. I often have ideas while cleaning around, cooking, etc. Claude Code (with Opus 4.5) is very capable. I've long wanted to get Claude Code working hands-free. So I took an afternoon and rolled my own STT-TTS voice stack for Claude Code. The voic…

On one hand, I think this project is super cool and something I would use and/or would have loved to build myself for my own use. On the other hand, it makes me wonder if we’re just heading for a future where everyone is just always working, at all times, even while doing other things. “Wow look at our daughter taking her first steps! She’s doing so… wait hold on… No, Claude. I said to name the class “potatoes”, not…

[deleted]

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#92

Post by zophi »

plingamp wrote: post #53
m00dy wrote: post #21

Earlier quoted context omitted.

RAG is broken when you have too much data.

Specifically when the document number reaches around 10k+, a phenomenon called "Semantic Collapse" occurs. https://dho.stanford.edu/wp-content/uploads/Legal_RAG_Halluc...

> Specifically when the document number reaches around 10k+

Where are you getting this? just read the paper and not seeing it -- interested to learn more

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#93

Post by Jommi »

yberreby wrote: post #49

Watching the OpenClaw/Molbot craze has been entertaining. I wouldn't use it - too much code, changing too quickly, with too little regard for security - but it has inspired me. I often have ideas while cleaning around, cooking, etc. Claude Code (with Opus 4.5) is very capable. I've long wanted to get Claude Code working hands-free. So I took an afternoon and rolled my own STT-TTS voice stack for Claude Code. The voic…

repo?

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#94

Post by lxgr »

Aurornis wrote: post #71
lxgr wrote: post #51

Earlier quoted context omitted.

No, RAG is definitely preferable once your memory size grows above a few hundred lines of text (which you can just dump into the context for most current models), since you're no longer fighting context limits and needle-in-a-haystack LLM retrieval performance problems.

> once your memory size grows above a few hundred lines of text (which you can just dump into the context for most current models) A few hundred lines of text is nothing for current LLMs. You can dump the entire contents of The Great Gatsby into any of the frontier LLMs and it’s only around 70K tokens. This is less than 1/3 of common context window sizes. That’s even true for models I run locally on modest hardware n…

Yes, but how good will the recall performance be? Just because your prompt fits into context doesn't mean that the model won't be overwhelmed by it.

When I last tried this with some Gemini models, they couldn't reliably identify specific scenes in a 50K word novel unless I trimmed down the context to a few thousands of words.

> Having LLMs use simpler tools like grep based on an array of similar search terms and then evaluating what comes up is faster in many cases

Sure, but then you're dependent on (you or the model) picking the right phrases to search for. With embeddings, you get much better search performance.

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#95

Post by somebehemoth »

threethirtytwo wrote: post #64
jamespo wrote: post #38

Earlier quoted context omitted.

There's people saying AI isn't living up its hype / valuation, I don't see many saying "utterly useless". And there's plenty who worship at the altar of Claude.

>There's people saying AI isn't living up its hype / valuation, I don't see many saying "utterly useless". There's more people saying AI doesn't live up to the hype. The people who are saying it's utterly useless is still quite large on HN. It's just that most of them are midway through changing their story because reality is smashing them in the face. >And there's plenty who worship at the altar of Claude. I mean wh…

> There's more people saying AI doesn't live up to the hype.

It is possible they are correct and nothing you have written suggests otherwise.

> The people who are saying it's utterly useless is still quite large on HN.

Are these people's opinions less valid than your own? Are you angry your opinion might be a minority on this one website?

> It's just that most of them are midway through changing their story because reality is smashing them in the face.

You made this up.

> But if you're not using it you're behind.

Yeah, well, you know, that’s just, like, your opinion, man

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#96

Post by Aurornis »

lxgr wrote: post #94
Aurornis wrote: post #71

Earlier quoted context omitted.

> once your memory size grows above a few hundred lines of text (which you can just dump into the context for most current models) A few hundred lines of text is nothing for current LLMs. You can dump the entire contents of The Great Gatsby into any of the frontier LLMs and it’s only around 70K tokens. This is less than 1/3 of common context window sizes. That’s even true for models I run locally on modest hardware n…

Yes, but how good will the recall performance be? Just because your prompt fits into context doesn't mean that the model won't be overwhelmed by it. When I last tried this with some Gemini models, they couldn't reliably identify specific scenes in a 50K word novel unless I trimmed down the context to a few thousands of words. > Having LLMs use simpler tools like grep based on an array of similar search terms and then…

> Yes, but how good will the recall performance be? Just because your prompt fits into context doesn't mean that the model won't be overwhelmed by it.

With current models it's very good.

Anthropic used a needle-in-haystack example with The Great Gatsby to demonstrate the performance of their large context windows all the way back in 2023: https://www.anthropic.com/news/100k-context-windows

Everything has become even better in the nearly 3 years since then.

> Sure, but then you're dependent on (you or the model) picking the right phrases to search for. With embeddings, you get much better search performance.

How do are those embeddings generated?

You're dependent on the embedding model to generate embeddings the way you expect.

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#97

Post by lxgr »

Aurornis wrote: post #96
lxgr wrote: post #94

Earlier quoted context omitted.

Yes, but how good will the recall performance be? Just because your prompt fits into context doesn't mean that the model won't be overwhelmed by it. When I last tried this with some Gemini models, they couldn't reliably identify specific scenes in a 50K word novel unless I trimmed down the context to a few thousands of words. > Having LLMs use simpler tools like grep based on an array of similar search terms and then…

> Yes, but how good will the recall performance be? Just because your prompt fits into context doesn't mean that the model won't be overwhelmed by it. With current models it's very good. Anthropic used a needle-in-haystack example with The Great Gatsby to demonstrate the performance of their large context windows all the way back in 2023: https://www.anthropic.com/news/100k-context-windows Everything has become even…

That doesn’t match my experience, both in test and actual usage scenarios.

Gemini 3 Pro fails to satisfy pretty straightforward semantic content lookup requests for PDFs longer than a hundred pages for me, for example.

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#98

Post by visarga »

visarga wrote: post #75
simonw wrote: post #70

Earlier quoted context omitted.

Yeah, vector embeddings based RAG has fallen out of fashion somewhat. It was great when LLMs had 4,000 or 8,000 token context windows and the biggest challenge was efficiently figuring out the most likely chunks of text to feed into that window to answer a question. These days LLMS all have 100,000+ context windows, which means you don't have to be nearly as selective. They're also exceptionally good at running searc…

The fundamental problem wit RAG is that it extracts only surface level features, "31+24" won't embed close to "55", while "not happy" will be close to "happy". Another issue is that embedding similarity does not indicate logical dependency, you won't retrieve the callers of a function with RAG, you need a LLM or code for that. Third issue is chunking, to embed you need to chunk, but if you chunk you exclude informati…

Ok 2 hours later here is the release: https://github.com/horiacristescu/nub

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#99

Post by mpolichette »

gdhkgdhkvff wrote: post #83
yberreby wrote: post #49

Watching the OpenClaw/Molbot craze has been entertaining. I wouldn't use it - too much code, changing too quickly, with too little regard for security - but it has inspired me. I often have ideas while cleaning around, cooking, etc. Claude Code (with Opus 4.5) is very capable. I've long wanted to get Claude Code working hands-free. So I took an afternoon and rolled my own STT-TTS voice stack for Claude Code. The voic…

On one hand, I think this project is super cool and something I would use and/or would have loved to build myself for my own use. On the other hand, it makes me wonder if we’re just heading for a future where everyone is just always working, at all times, even while doing other things. “Wow look at our daughter taking her first steps! She’s doing so… wait hold on… No, Claude. I said to name the class “potatoes”, not…

I don't disagree, but I think there is the otherside of that same coin... What if we could do other stuff while remaining productive.

Rather than the example of missing first steps, what if we had, "Ok Claude, prepare a few slides for my presentation, I'm going to watch my childs mid-day recital..." maybe you get a success/failure ping and maybe even need to step out for part of the event, but in another world you couldn't have gone at all.

Re: Nanobot: Ultra-Lightweight Alternative to OpenClaw

#100

Post by Aurornis »

lxgr wrote: post #97
Aurornis wrote: post #96

Earlier quoted context omitted.

> Yes, but how good will the recall performance be? Just because your prompt fits into context doesn't mean that the model won't be overwhelmed by it. With current models it's very good. Anthropic used a needle-in-haystack example with The Great Gatsby to demonstrate the performance of their large context windows all the way back in 2023: https://www.anthropic.com/news/100k-context-windows Everything has become even…

That doesn’t match my experience, both in test and actual usage scenarios. Gemini 3 Pro fails to satisfy pretty straightforward semantic content lookup requests for PDFs longer than a hundred pages for me, for example.

> for PDFs longer than a hundred pages for me

Your original comment that I responded to said a "few hundred lines of text", not hundred page PDFs.

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