Maybe you gave up before Google released Gemini Advanced? This viewpoint seemed more accurate before it was related, but Gemini Advanced is the third best LLM as rated here [1]. In fact, had second place until a few days ago when Claude 3.5 came out.

[1]: https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboar...

Isn't Gemini Advanced Gemini Pro attached to some sort of an internet search program? If it has that advantage over other models it isn't a sign of AI chops.

Can't speak to Gemma, but I found 1.5 superior to Claude and ChatGPT 4 when it came out. The trend seems to be each taking the lead when it comes out, being king of the hill for a couple weeks, and then being surpassed by the next.

Claude's reign has begun, and I'd say it has a solid enough lead for at least another two weeks of dominance before it's dethroned.

I wonder if Google is making Deepmind people switch from their cool original research to doing LLMs like everybody else. Having their scale in money and data, I would hire new teams of engineers who want to do LLMs and leave the Deepmind researchers do their thing. Not killing the goose that lays golden eggs.

Google is in a fight for their lives, I've fully moved over to paid services and haven't used google in about a month now.

If this were a common sentiment or rooted in reality I would imagine their stock would not be at an all time high...

I'm an early adopter. The rest of you will catch up in the next five years.

Ironically I was just thinking earlier today how the most valuable Google products to me are YouTube and Android... and that's it.

I gave up on Chrome a decade ago, going back to Firefox. I don't use Google for search anymore, I do use Gmail but I also got Protonmail so could easily migrate the Gmail traffic there.

A lot of non-techies I know have complained for some time how Google search sucks, and while a lot use Chrome it seems to be mainly inertia.

Not saying Google is dying, but it seems vulnerable for disruption.

Is it really possible to even disrupt Youtube? It's been a constant in our lives for the past 20 years and is basically a historical record by now. By a rough estimate, they have to keep buying over 1% of the total world production of HDD drives just to stay on top of the new data being uploaded. Google has completely destroyed it, placing more ads than videos on it, making it unusable without an adblocker and people still use it, it's that core to everyone's lives. It's like a public utility.

I've been thinking about it. AI generated videos. It could be generating a DSL or IR for some sort of multimedia VM so there's only a tiny fraction of data. Just common textures and shapes in a CDN. Could be fully interactive.

I wouldn't be surprised if most of it was already tried in some form.

And the training samples are overly tied to Vertex

>long time ago

This is an incredible statement to make about a field that no one was talking about 24 months ago, a family of SOTA models that didn't exist until 8 months ago, and a family of small local models that didn't exist 6 months ago. But sure, give up hope after the first generation of a model family doesn't impress you.

People seem to forget how incredibly early we are in this whole thing. The fact that so much progress has been made in such a short amount of time should make everyone super excited!

To be fair, LLMs (especially Google LLMs) aren't merely 24 months old. This is part of a long line of models that draw their heritage from BERT and t5-flan. Google has been at this longer than most, particularly in the field of edge-compute models. This isn't even close to a first-generation model family.

That's not to say this is an insignificant contribution. New models are great, especially when released for free, and it's important for big firms to keep the ball rolling for tech to progress. Though there is also legitimate concern that all LLMs aren't improving as fast as they used to improve, and we may have hit the proverbial bathtub curve of AI progress.

I think there is valid criticism of google for inventing a cool technology only to have the rest of the industry discover its usefulness before them. But to say Gemini 1.0 or OG Gemma aren't first generation models because BERT and flan existed before is like saying the iPad wasn't a first generation device because Apple made the Newton. Like sure, they're the same in that they're transformers trained on language and text, but these are new families of models. The training mechanisms are different, their architectures are different, the data sets are different, the intended purpose of the models are completely different, etc. At some point I guess it's a semantic difference, maybe.