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Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

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Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#71

Post by Imustaskforhelp »

dang wrote: post #67
Imustaskforhelp wrote: post #34

Earlier quoted context omitted.

Thanks dang but can you please explain there being two accounts who wrote something very small comment and one account being completely new and the other being 7 months old only being invoked in this case. Clearly I am not the only one here as john_strinlai here seems to have had somewhat of the same conclusion as me. Dang I know you care about this community so can you please talk more what you think about this in p…

I'm happy to answer as best I can! but I'm having trouble understanding what you're specifically asking. If https://news.ycombinator.com/item?id=47327129 and https://news.ycombinator.com/item?id=47328465 don't answer your questions, can you maybe try picking the most important question and making it as specific as you can? Then I can take a crack at that and we can go from there.

Sure let me better explain what I'd like if possible.

https://news.social-protocols.org/stats?id=47326101

I'd like to have some information within 1) time frame of this from 0-80 upvotes which feels the most upward of this curve and 2) time frame of the whole article and I would like three datapoints in all of this:

So imagine we take every people who upvoted this thread and then we find three data points and average (median not mean for better representation) them together for anonymity purposes:

1. The date of the accounts

2. The karma of the accounts

3. The words written by those accounts (optional) [But I have done some work on that and I have found this to be a good factor on if someone is truly a bot or not]

Because, Although you mention that the upvotes are fine. I'd still really appreciate it if we can find any form of data backing that statement up and hopefully knowing that nothing fishy is going on as you may understand that this company has done a lot of fishy stuff in its past and all the fishy stuff which I have talked about in this thread too makes me feel like just a minor bit more deeper look into it/transparency would personally be really appreciated and the community would like it too!

Have a nice day dang and looking forward to your next comment!

Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#72

Post by coder543 »

CamJN wrote: post #68
coder543 wrote: post #60

Earlier quoted context omitted.

Terrible relative to everything else that exists today. I have a neutral American accent. Maybe you just don’t know what you’re missing? Google’s default speech to text is still bad compared to Whisper and Parakeet, but even Google’s is markedly better than Apple’s. I cannot think of a single speech to text system that I’ve run into in the past 5 years that is less accurate than the one Apple ships. Sure, Apple’s spe…

As someone who tried every TTS in existance a few years ago for some product work, Apple’s is so consistantly better that we wound up getting a bunch of apple stuff just for the TTS.

“A few years ago” sounds like it could be before the modern era of STT, as defined by when Whisper was released.

Your comment says TTS, which is different from what I’m discussing, though, so there might be some confusion.

Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#74

Post by dang »

Imustaskforhelp wrote: post #71
dang wrote: post #67

Earlier quoted context omitted.

I'm happy to answer as best I can! but I'm having trouble understanding what you're specifically asking. If https://news.ycombinator.com/item?id=47327129 and https://news.ycombinator.com/item?id=47328465 don't answer your questions, can you maybe try picking the most important question and making it as specific as you can? Then I can take a crack at that and we can go from there.

Sure let me better explain what I'd like if possible. https://news.social-protocols.org/stats?id=47326101 I'd like to have some information within 1) time frame of this from 0-80 upvotes which feels the most upward of this curve and 2) time frame of the whole article and I would like three datapoints in all of this: So imagine we take every people who upvoted this thread and then we find three data points and average…

Sorry, but this is much too complicated for me to follow, and I believe I've already answered the main points: what happened to the thread and what was going on with the upvotes and comments.

Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#75

Post by blks »

vessenes wrote: post #7

Just tried it. really cool, and a fun tech demo with rcli. I filed a bug report; not everything is loading properly when installed via homebrew. Quick request: unsloth quants; bit per bit usually better. Or more generally UI for huggingface model selections. I understand you won't be able to serve everything, but I want to mix and match! Also - grounding: "open safari" (safari opens, voice says: "I opened safari") "n…

> "open safari" (safari opens, voice says: "I opened safari") "navigate to google.com in safari" (nothing happens, voice says: "I navigated to google.com")

So you’re describing a core broken feature. Application breaking at easiest test.

Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#76

Post by shubham2802 »

stingraycharles wrote: post #4

I’m a bit confused by what you’re offering. Is it a voice assistant / AI as described on your GitHub? Or is it more general purpose / LLM ? How does the RAG fit in, a voice-to-RAG seems a bit random as a feature? I don’t mean to come across as dismissive, I’m genuinely confused as to what you’re offering.

RunAnywhere builds software that makes AI models run fast locally on devices instead of sending requests to the cloud.

Right now, our focus is Apple Silicon.

Today there are two parts:

MetalRT - our proprietary inference engine for Apple Silicon. It speeds up local LLM, speech-to-text, and text-to-speech workloads. We’re expanding model coverage over time, with more modalities and broader support coming next.

RCLI - our open-source CLI that shows this in practice. You can talk to your Mac, query local docs, and trigger actions, all fully on-device.

So the simplest way to think about us is: we’re building the runtime / infrastructure layer for on-device AI, and RCLI is one example of what that enables.

Longer term, we want to bring the same approach to more chips and device types, not just Apple Silicon.

For people asking whether the speedups are real, we’ve published our benchmark methodology and results here: LLM: https://www.runanywhere.ai/blog/metalrt-fastest-llm-decode-e... Speech: https://www.runanywhere.ai/blog/metalrt-speech-fastest-stt-t...

Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#77

Post by harvenstar »

shubham2802 wrote: post #55
RationPhantoms wrote: post #49

This doesn't work on any of the methods I've tried.

Please open the issue - if it's not working ? I believe you should be able to install it via : curl -fsSL https://raw.githubusercontent.com/RunanywhereAI/RCLI/main/in... | bash

Cool project — been looking for something like this. Just opened a PR with a couple of new macOS actions (empty_trash + toggle_do_not_disturb). Happy to contribute more and quick chat if you're open to it.

Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#78

Post by Imustaskforhelp »

dang wrote: post #74
Imustaskforhelp wrote: post #71

Earlier quoted context omitted.

Sure let me better explain what I'd like if possible. https://news.social-protocols.org/stats?id=47326101 I'd like to have some information within 1) time frame of this from 0-80 upvotes which feels the most upward of this curve and 2) time frame of the whole article and I would like three datapoints in all of this: So imagine we take every people who upvoted this thread and then we find three data points and average…

Sorry, but this is much too complicated for me to follow, and I believe I've already answered the main points: what happened to the thread and what was going on with the upvotes and comments.

That's fair dang. Sorry if it got too complicated. I trust ya in that case that the comments are fine from your one of comments to me here. Any case of botting must have been spotted by you guys if there was a case.

It was just that they raised quite a large number of red alerts for me personally with the whole thing.

Just to be on the same page, Is there anything suspicious about the upvotes in this page in sense of being upvoted by bot accounts in general from your observation especially during the start of this thread?

Can you please just talk more about this as in confirmation because I still have some disbelief about it given its shady history and the whole way this thread unfolded. I feel as if there feels some likelihood to me that this post got (bot-upvoted?) at some point or the other.

Or did all of the upvotes came from genuine account and it was just that this got to front page due to hackernews preferential treatment? Can you just talk more about it because if anything, I might still learn something new either way.

Dang, Has there ever been any YC startup which employed in shady practice like using bots to upvote their HN posts or use bot accounts which got caught in the history of this website?

Re: Launch HN: RunAnywhere (YC W26) – Faster AI Inference on Apple Silicon

#80

Post by shubham2802 »

shekhar101 wrote: post #79

Tried this and really liking it so far. Question - is there a diarization support in the tui app or any of the models MetalRt supports? Any plans to add it if not already supported?

Yes, we do have plans to support it.
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