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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

#161

Post by krona »

utopcell wrote: post #157
smallerfish wrote: post #154

Was this written by an LLM? It's pretty bad copy. Maybe they laid off their copywriting team...? > "Now millions of developers are building with Gemini. And it’s helping us reimagine all of our products — including all 7 of them with 2 billion users — and to create new ones" and > "We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading…

Sorry, what's wrong with these phrases?

> all of our products — including all 7 of them

All the products including all the products?

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

#164

Post by thelastbender12 »

nightski wrote: post #114
ramoz wrote: post #105

Earlier quoted context omitted.

These models take an instruction, along with any contextual information, and are trained to produce valid output. That production of output is a form of reasoning via _some_ type of logical processing. No? Maybe better to say computational reasoning. That’s a mouthful.

Static computation is not reasoning (these models are not building up an argument from premises, they are merely finding statistically likely completions). Computational thinking/reasoning would be breaking down a problem into an algorithmic steps. The model is doing neither. I wouldn't confuse the fact that it can break it into steps if you ask it, because again that is just regurgitation. It's not going through tha…

I kinda agree with you but I can also see why it isn't that far from "reasoning" in the sense humans do it.

To wit, if I am doing a high school geometry proof, I come up with a sequence of steps. If the proof is correct, each step follows logically from the one before it.

However, when I go from step 2 to step 3, there are multiple options for step-3 I could have chose. Is it so different from a "most-likely-prediction" an LLM makes? I suppose the difference is humans can filter out logically-incorrect steps, or prune chains-of-steps that won't lead to the actual theorem quicker. But an LLM predictor coupled with a verifier doesn't feel that different from it.

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

#165

Post by closewith »

talldayo wrote: post #77
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…

BERT and Gemma 2B were both some of the highest-performing edge models of their time. Google does really well - in terms of pushing efficiency in the community they're second to none. They also don't need to rely on inordinate amounts of compute because Google's differentiating factor is the products they own and how they integrate it. OpenAI is API-minded, Google is laser-focused on the big-picture experience. For e…

> Google is laser-focused on the big-picture experience.

This doesn't match my experience of any Google product.

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

#166

Post by rowanG077 »

whimsicalism wrote: post #90
dagmx wrote: post #58

Earlier quoted context omitted.

At what point does the on device stuff eat into their market share though? As on device gets better, who will pay for cloud compute? Other than enterprise use. I’m not saying on device will ever truly compete at quality, but I believe it’ll be good enough that most people don’t care to pay for cloud services.

You're still focused about inference :) inference basically does not matter, it is a commodity

That makes no sense. Inference cost dwarf training cost if you have a succesfull product pretty quickly. Afaik there is no commodity hardware that can run state of the art models like chatgpt-o1.

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

#167

Post by coder543 »

summerlight wrote: post #83

It is interesting to see that they keep focusing on the cheapest model instead of the frontier model. Probably because of their primary (internal?) customer's need?

It's cheaper and faster to train a small model, which is better for a research team to iterate on, right? If Google decides that a particular small model is really good, why wouldn't they go ahead and release it while they work on scaling up that work to train the larger versions of the model?

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

#168

Post by TIPSIO »

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…

Yes. Imagine Google banning your entire Google account / Gmail because you violated their gray area AI terms ([1] or [2]). Or, one of your users did via an app you made using an API key and their models.

With that being said, I am extremely bullish on Google AI for a long time. I imagine they land at being the best and cheapest for the foreseeable future.

[1] https://policies.google.com/terms/generative-ai

[2] https://policies.google.com/terms/generative-ai/use-policy

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

#169

Post by JeremyNT »

bradhilton wrote: post #6

Beats Gemini 1.5 Pro at all but two of the listed benchmarks. Google DeepMind is starting to get their bearings in the LLM era. These are the minds behind AlphaGo/Zero/Fold. They control their own hardware destiny with TPUs. Bullish.

Yeah they've been slow to release end-user facing stuff but it's obvious that they're just grinding away internally.

They've ceded the fast mover advantage, but with a massive installed base of Android devices, a team of experts who basically created the entire field, a huge hardware presence (that THEY own), massive legal expertise, existing content deals, and a suite of vertically integrated services, I feel like the game is theirs to lose at this point.

The only caution is regulation / anti-trust action, but with a Trump administration that seems far less likely.

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

#170

Post by CSMastermind »

> We're also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It's available in Gemini Advanced today.

Anyone seeing this? I don't have an option in my dropdown.

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