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Gemini 2.0: our new AI model for the agentic era

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Re: Gemini 2.0: our new AI model for the agentic era

#221

Post by tbarbugli »

crazygringo wrote: post #177
crowcroft wrote: post #15

Big companies can be slow to pivot, and Google has been famously bad at getting people aligned and driving in one direction. But, once they do get moving in the right direction the can achieve things that smaller companies can't. Google has an insane amount of talent in this space, and seems to be getting the right results from that now. Remains to be seen how well they will be able to productize and market, but hard…

> and Google has been famously bad at getting people aligned and driving in one direction. To be fair, it's not that they're bad at it -- it's that they generally have an explicit philosophy against it. It's a choice. Google management doesn't want to "pick winners". It prefers to let multiple products (like messaging apps, famously) compete and let the market decide. According to this way of thinking, you come out a…

Google is not winning on cloud, AWS is winning and MS gaining ground.

Re: Gemini 2.0: our new AI model for the agentic era

#222

Post by aerhardt »

iamdelirium wrote: post #196
krona wrote: post #161

Earlier quoted context omitted.

> all of our products — including all 7 of them All the products including all the products?

Why did you specifically ignore the remainder of the sentence? "...all of our products — including all 7 of them with 2 billion users..." It tells people that 7 of their products have 2b users.

That phrasing still sucks, I am neither a native speaker nor a wordsmith but I've worked with professional English writers who could make that look and sound infinitely better.

Re: Gemini 2.0: our new AI model for the agentic era

#223

Post by jay_kyburz »

iamdelirium wrote: post #196
krona wrote: post #161

Earlier quoted context omitted.

> all of our products — including all 7 of them All the products including all the products?

Why did you specifically ignore the remainder of the sentence? "...all of our products — including all 7 of them with 2 billion users..." It tells people that 7 of their products have 2b users.

all of our products, 7 of which have over 2 billion users..

Re: Gemini 2.0: our new AI model for the agentic era

#224

Post by dandiep »

kwindla wrote: post #111
dandiep wrote: post #95

Gemini multimodal live docs here: https://cloud.google.com/vertex-ai/generative-ai/docs/model-... A little thin... Also no pricing is live yet. OpenAI's audio inputs/outputs are too expensive to really put in production, so hopefully Gemini will be cheaper. (Not to mention, OAI's doesn't follow instructions very well.)

The Multimodal Live API is free while the model/API is in preview. My guess is that they will be pretty aggressive with pricing when it's in GA, given the 1.5 Flash multimodal pricing. If you're interested in this stuff, here's a full chat app for the new Gemini 2 API's with text, audio, image, camera video and screen video. This shows how to use both the WebSocket API and to route through WebRTC infrastructure. http…

Thanks, this is great!

Re: Gemini 2.0: our new AI model for the agentic era

#225

Post by SimianSci »

maeil wrote: post #72
whimsicalism wrote: post #20

Earlier quoted context omitted.

i don’t think they need to win the on device market. we need to separate inference and training - the real winners are those who have the training compute. you can always have other companies help with inference

> i don’t think they need to win the on device market. The second Apple comes out with strong on-device AI - and it very much looks like they will - Google will have to respond on Android. They can't just sit and pray that e.g. Samsung makes a competitive chip for this purpose.

I think Apple is uniquely disadvantaged in the AI race to a point people dont realize. They have less training data to use, having famously been focused on privacy for its users and thus having no particular advantage in this space due to not having customer data to train on. They have little to no cloud business, and while they operate a couple of services for their users, they do not have the infrastructure scale to compete with hyperscaler cloud vendors such as Google and Microsoft. Most of what they would need to spend on training new models would require that they hand over lots of money to the very companies that already have their own models, supercharging their competition.

While there is a chance that Apple might come out with a very sophisticate on-device model. The problem here is that they would only be able to compete with other on-device models. The magnitude of compute needed to keep pace with SOA models is not achievable on a single device. It will take many generations of Apple silicon in order to compete with the compute of existing datacenters.

Google also already has competitive silicon in this space with the Tensor series processors, which are being fabbed at Samsung plants today. There is no sitting and praying necessary on their part as they already compete.

Apple is a very distant competitor in the space of AI, and I see no reason to assume this will change, they are uniquely disadvantaged by several of the choices they made on their way to mobile supremacy. The only thing they currently have going for them is the development of their own ARM silicon which may give them the ability to compete with Google's TPU chips, but there is far more needed to be competitive here than the ability to avoid the Nvidia tax.

Re: Gemini 2.0: our new AI model for the agentic era

#226

Post by caeril »

manishsharan wrote: post #31
crowcroft wrote: post #15

Big companies can be slow to pivot, and Google has been famously bad at getting people aligned and driving in one direction. But, once they do get moving in the right direction the can achieve things that smaller companies can't. Google has an insane amount of talent in this space, and seems to be getting the right results from that now. Remains to be seen how well they will be able to productize and market, but hard…

>> hard to deny that their LLM models aren't really, really good though. The context window of Gemini 1.5 pro is incredibly large and it retains the memory of things in the middle of the window well. It is quite a game changer for RAG applications.

Bear in mind that a "1 million token" context window isn't actually that. You're being sold a sparse attention model, which is guaranteed to drop critical context. Google TPUs aren't running inference on a TERABYTE of fp8 query-key inputs, let alone TWO of fp16.

Google's marketing wins again, I guess.

Re: Gemini 2.0: our new AI model for the agentic era

#227

Post by WA »

jncfhnb wrote: post #16

Am I alone in thinking the word “agentic” is dumb as shit? Most of these things seem to just be a system prompt and a tool that get invoked as part of a pipeline. They’re hardly “agents”. They’re modules.

Gemini, too, for the sole reason that non-native speakers have no clue how to pronounce it.

Re: Gemini 2.0: our new AI model for the agentic era

#228

Post by jacooper »

pelorat wrote: post #57
crowcroft wrote: post #15

Big companies can be slow to pivot, and Google has been famously bad at getting people aligned and driving in one direction. But, once they do get moving in the right direction the can achieve things that smaller companies can't. Google has an insane amount of talent in this space, and seems to be getting the right results from that now. Remains to be seen how well they will be able to productize and market, but hard…

Well, compared to github copilot (paid), I think Gemini Free is actually better at writing non-archaic code.

Gemini is coming to copilot soon anyway.

Re: Gemini 2.0: our new AI model for the agentic era

#229

Post by dotancohen »

StableAlkyne wrote: post #152
crowcroft wrote: post #15

Big companies can be slow to pivot, and Google has been famously bad at getting people aligned and driving in one direction. But, once they do get moving in the right direction the can achieve things that smaller companies can't. Google has an insane amount of talent in this space, and seems to be getting the right results from that now. Remains to be seen how well they will be able to productize and market, but hard…

> Remains to be seen how well they will be able to productize and market The challenge is trust. Google is one of the leaders in AI and are home to incredibly talented developers. But they also have an incredibly bad track record of supporting their products. It's hard to justify committing developers and money to a product when there's a good chance you'll just have to pivot again once they get bored. Say what you w…

  > Google is one of the leaders in AI and are home to incredibly talented developers. But they also have an incredibly bad track record of supporting their products.
This is why we've stayed with Anthropic. Every single person I work with on my current project is sore at Google for discontinuing one product or another - and not a single one of them mentioned Reader.

We do run some non-customer facing assets in Google Cloud. But the website and API are on AWS.

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