Will we now finally get autocorrect that isn’t complete garbage?
That’s all I really want for Christmas.
Gemma 3n preview: Mobile-first AI
131–140 of 179 posts
Re: Gemma 3n preview: Mobile-first AI
#132Earlier quoted context omitted.
It's understanding.
LLMs neither understand nor reason, that has been shown multiple times.
The bar for this excludes humans xor includes LLMs. I guess you're opting for the former?
If you don't believe me, here is a fun mental exercise: define "understand" and "reason" in a measurable way, that includes humans but excludes LLMs.
Re: Gemma 3n preview: Mobile-first AI
#133Earlier quoted context omitted.
Seems like some don’t like that LLMs aren’t really intelligent. https://neurosciencenews.com/llm-ai-logic-27987/
We're at the peak of the hype cycle right now. Ask these questions again in two years when the next winter happens.
Or, ignore the hype, look at what we know about how these models work and about the structures their weights represent, and base your answers on that today.
Re: Gemma 3n preview: Mobile-first AI
#134You can try it on Android right now: Download the Edge Gallery apk from github: https://github.com/google-ai-edge/gallery/releases/tag/1.0.0 Download one of the .task files from huggingface: https://huggingface.co/collections/google/gemma-3n-preview-6... Import the .task file in Edge Gallery with the + bottom right. You can take pictures right from the app. The model is indeed pretty fast.
I assume that "pretty fast" depends on the phone. My old Pixel 4a ran Gemma-3n-E2B-it-int4 without problems. Still, it took over 10 minutes to finish answering "What can you see?" when given an image from my recent photos. Final stats: 15.9 seconds to first token 16.4 tokens/second prefill speed 0.33 tokens/second decode speed 662 seconds to complete the answer
Pixel 9 Pro XL
("What can you see?"; photo of small monitor displaying stats in my home office)
1st token: 7.48s
Prefill speed: 35.02 tokens/s
Decode speed: 5.72 tokens/s
Latency: 86.88s
It did a pretty good job, the photo had lots of glare and was at a bad angle and a distance, with small text; it picked out weather, outdoor temperature, CO2/ppm, temp/C, pm2.5/ug/m^3 in the office; Misread "Homelab" as "Household" but got the UPS load and power correctly, Misread "Homelab" again (smaller text this time) as "Hereford" but got the power in W, and misread "Wed May 21" on the weather map as "World May 21".
Overall very good considering how poor the input image was.
Edit: E4B
Re: Gemma 3n preview: Mobile-first AI
#135Earlier quoted context omitted.
LLMs neither understand nor reason, that has been shown multiple times.
The bar for this excludes humans xor includes LLMs. I guess you're opting for the former? If you don't believe me, here is a fun mental exercise: define "understand" and "reason" in a measurable way, that includes humans but excludes LLMs.
It's pretty easy to craft a prompt that will force the LLM to reply with something like
> The `foobar` is also incorrect. It should be a valid frobozz, but it currently points to `ABC`, which is not a valid frobozz format. It should be something like `ABC`.
Where the two `ABC`s are the exact same string of tokens.
Obviously nonsense to any human, but a valid LLM output for any LLM.
This is just one example. Once you start using LLMs as tools instead of virtual pets you'll find lots more similar.
Re: Gemma 3n preview: Mobile-first AI
#136Earlier quoted context omitted.
The bar for this excludes humans xor includes LLMs. I guess you're opting for the former? If you don't believe me, here is a fun mental exercise: define "understand" and "reason" in a measurable way, that includes humans but excludes LLMs.
It's pretty easy to craft a prompt that will force the LLM to reply with something like > The `foobar` is also incorrect. It should be a valid frobozz, but it currently points to `ABC`, which is not a valid frobozz format. It should be something like `ABC`. Where the two `ABC`s are the exact same string of tokens. Obviously nonsense to any human, but a valid LLM output for any LLM. This is just one example. Once you…
People say nonsense all the time. LLMs also don't have this issue all the time. They are also often right instead of saying things like this. If this reply was meant to be a demonstration of LLMs not having human level understanding and reasoning, I'm not convinced.
Re: Gemma 3n preview: Mobile-first AI
#137Earlier quoted context omitted.
It seems straightforward to me: Apps take up storage, and the only way to get more of that is to pay Apple's markups, as iOS devices don't support upgradable storage. On top of the already hefty markup, they don't even take storage capacity into consideration for trade-ins.
I am not aware of any phone allowing storage upgrades.
microSD. Of course, never supported in any iPhone.
Re: Gemma 3n preview: Mobile-first AI
#138Earlier quoted context omitted.
Imagine a model smarter than most humans that fits on your phone. edit: I seem to be the only one excited by the possibilities of such small yet powerful models. This is an iPhone moment: a computer that fits in your pocket, except this time it's smart.
I can't speak for anyone else, but these models only seem about as smart as google search, with enormous variability. I can't say I've ever had an interaction with a chatbot that's anything redolent of interaction with intelligence. Now would I take AI as a trivia partner? Absolutely. But that's not really the same as what I look for in "smart" humans.
>anything redolent of interaction with intelligence
compared to what you are used to right?
I know it's elitist but most people My circle of people I talk with during the day has changed since I took on more charity which consists of fixing up old laptops and installing Ubuntu on them; I get them for free from everyone and I give them to people who cannot afford, including some lessons and remote support (which is easy as I can just ssh in via tailscale). Many of them believe in chemtrails, vaccinations are a gov ploy etc and multiple have told me they read that these AI chatbots are nigerian or indian (or so) farms trying to fraud them out of 'things' (they usually don't have anything to fraud otherwise I would not be there). This is about half of humanity; Gemma is gonna be smarter than all of them, even though I don't register any LLM as intelligence and with the current models, it won't happen either. Maybe a breakthrough in models will be made that changes it, but it has not much chance yet.
Re: Gemma 3n preview: Mobile-first AI
#139Earlier quoted context omitted.
We're at the peak of the hype cycle right now. Ask these questions again in two years when the next winter happens.
Or, ignore the hype, look at what we know about how these models work and about the structures their weights represent, and base your answers on that today.
That’s what my link is for
Re: Gemma 3n preview: Mobile-first AI
#140Earlier quoted context omitted.
It's pretty easy to craft a prompt that will force the LLM to reply with something like > The `foobar` is also incorrect. It should be a valid frobozz, but it currently points to `ABC`, which is not a valid frobozz format. It should be something like `ABC`. Where the two `ABC`s are the exact same string of tokens. Obviously nonsense to any human, but a valid LLM output for any LLM. This is just one example. Once you…
People say nonsense all the time. LLMs also don't have this issue all the time. They are also often right instead of saying things like this. If this reply was meant to be a demonstration of LLMs not having human level understanding and reasoning, I'm not convinced.
Not people, some people.
But a LLM is sometimes the genius and sometimes the idiot.
That doesn’t happen often if you always talk to the same person