Rabbit R1 AI box revealed to just be an Android app
Rabbit R1 AI box revealed to just be an Android app
It sounds like the company is now blocking access from "bootleg" APKs.
- Rabbit R1 AI box is actually an Android app in a limited $200 box, running on AOSP without Google Play.
- Rabbit Inc. is unhappy about details of its tech stack being public, threatening action against unauthorized emulators.
- AOSP is a logical choice for mobile hardware as it provides essential functionalities without the need for Google Play.
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Why are there AI boxes popping up everywhere? They are useless. How many times do we need to repeat that LLMs are trained to give convincing answers but not correct ones. I've gained nothing from asking this glorified e-waste something, pulling out my phone and verifying it.
What I don't get is why anyone would like to buy a new gadget for some AI features. Just develop a nice app and let people run it on their phones.
That's why though. Because they can monetize hardware. They can't monetize something a free app does.
Plenty of free apps get monetized just fine. They just have to offer something people want to use that they can slather ads all over. The AI doo-dads haven't shown they're useful. I'm guessing the dedicated hardware strategy got them more upfront funding from stupid venture capital than an app would have, but they still haven't answered why anybody should buy these. Just postponing the inevitable.
I just used ChatGPT to write a 500-line Python application that syncs IP addresses from asset management tools to our vulnerability management stack. This took about 4 hours using AutoGen Studio. The code just passed QA and is moving into production next week.
https://github.com/blainemartin/R7_Shodan_Cloudflare_IP_Sync_Tool
Tell me again how LLMs are useless?
To be honest… that doesn’t sound like a heavy lift at all.
Dream of tech bosses everywhere. Pay an intermediate dev for average level senior output.
Intermediate? Nah, junior. They're cheaper after all.
But senior devs do a lot more than output code. Sometimes - like Bill Atkinson's famous -2000 line change to Quickdraw - their jobs involve a lot of complex logic and very little actual code output.
It's a shortcut for experience, but you lose a lot of the tools you get with experience. If I were early in my career I'd be very hesitant relying on it as its a fragile ecosystem right now that might disappear, in the same way that you want to avoid tying your skills to a single companies product. In my workflow it slows me down because the answers I get are often average or wrong, it's never "I'd never thought of doing it that way!" levels of amazing.
You used the right tool for the job, saved you from hours of work. General AI is still a very long ways off and people expecting the current models to behave like one are foolish.
Are they useless? For writing code, no. Most other tasks yes, or worse as they will be confiently wrong about what you ask them.
I think the reason they're useful for writing code is that there's a third party - the parser or compiler - that checks their work. I've used LLMs to write code as well, and it didn't always get me something that worked but I was easily able to catch the error.
Are they useless?
Only if you believe most Lemmy commenters. They are convinced you can only use them to write highly shitty and broken code and nothing else.
This is my expirence with LLMs, I have gotten it to write me code that can at best be used as a scaffold. I personally do not find much use for them as you functionally have to proofread everything they do. All it does change the work load from a creative process to a review process.
I don't agree. Just a couple of days ago I went to write a function to do something sort of confusing to think about. By the name of the function, copilot suggested the entire contents of the function and it worked fine. I consider this removing a bit of drudgery from my day, as this function was a small part of the problem I needed to solve. It actually allowed me to stay more focused on the bigger picture, which I consider the creative part. If I were a painter and my brush suddenly did certain techniques better, I'd feel more able to be creative, not less.
But we never have proofs that it gives good code, that's convenient...
So you want me to go into one of my codebases, remember what came from copilot and then paste it here? Lol no
Of course you can't.
Just a couple of days ago
You already forgot, that's convenient, again.
Yeah you post your employer first, dumbass
All you want is something to belittle
You say it's magical but never post proof. That's all I need to think it's shit. No need to debate about it for hours. Come back when you entice us with something instead of the billion REST APIs that are useless but seem to give a hard on to all the AI bros out there.
It's no sense trying to explain to people like this. Their eyes glaze over when they hear Autogen, agents, Crew ai, RAG, Opus... To them, generative AI is nothing more than the free version of chatgpt from a year ago, they've not kept up with the advancements, so they argue from a point in the distant past. The future will be hitting them upside the head soon enough and they will be the ones complaining that nobody told them what was comming.
They aren't trying to have a conversation, they're trying to convince themselves that the things they don't understand are bad and they're making the right choice by not using it. They'll be the boomers that needed millennials to send emails for them. Been through that so I just pretend I don't understand AI. I feel bad for the zoomers and genas that will be running AI and futilely trying to explain how easy it is. Its been a solid 150 years of extremely rapid invention and innovation of disruptive technology. But THIS is the one that actually won't be disruptive.
Please show me good code done with AI. I'm waiting.
Wonderfully said, this is a very good point.
Who's going to tell them that "QA" just ran the code through the same AI model and it came back "Looks Good".
:-)
I don't think LLMs are useless, but I do think little SoC boxes running a single application that will vaguely improve your life with loosely defined AI features are useless.
Because money, both from tech hungry but not very savvy consumers, and the inevitable advertisers that will pay for the opportunity for their names to be ejected from these boxes as part of a perfectly natural conversation.
I think it's a delayed development reaction to Amazon Alexa from 4 years ago. Alexa came out, voice assistants were everywhere. Someone wanted to cash in on the hype but consumer product development takes a really long time.
So product is finally finished (mobile Alexa) and they label it AI to hype it as well as make it work without the hard work of parsing wikipedia for good answers.
Alexa is a fundamentally different architecture from the LLMs of today. There is no way that anyone with even a basic understanding of modern computing would say something like this.
Alexa is a fundamentally different architecture from the LLMs of today.
Which is why I explicitly said they used AI (LLM) instead of the harder to implement but more accurate Alexa method.
Maybe actually read the entire post before being an ass.
Alexa and Google home came out nearly a decade ago
I have now heard of my first "ai box". I'm on Lemmy most days. Not sure how it's an epidemic...
I haven't seen much of them here, but I use other media too. E.g, not long ago there was a lot of coverage about the "Humane AI Pin", which was utter garbage and even more expensive.
There is s fuck ton on money laundering coming from China nowadays and they invest millions in any tech-bro stupid idea to dump their illegal cash.
I just started diving into the space from a localized point yesterday. And I can say that there are definitely problems with garbage spewing, but some of these models are getting really really good at really specific things.
A biomedical model I saw seemed lauded for it's consistency in pulling relevant data from medical notes for the sake of patient care instructions, important risk factors, fall risk level etc.
So although I agree they're still giving well phrased garbage for big general cases (and GPT4 seems to be much more 'savvy'), the specific use cases are getting much better and I'm stoked to see how that continues.