Gemini Decisions API

iamdelirium

Looks like Google announced their own Jev inspired API and model

waximabbax

Its bit more expensive than other other Decision Models in the same lane. However, it can accept Audio and Video as input as well and for those specific cases it can be extremely useful.

florkbork

Meanwhile, they are suffocating Jules today ( https://killedbygoogle.com/ ) with a metaphorical pillow to the face and no migration path mapped out for casual users apart from "use antigravity" in a 1 line high banner; after about a year of existence. It seems unlikely this will be around in 6 months at this rate.

IncreasePosts

It took OpenAI 2 weeks after Jev to release a decision end point, and now google does it 2 months later. Why such a difference? Bureaucracy? Quality control?

eminence32

I'm sort of surprised it took Jev for everyone to realize "oh yeah, this is a useful thing that we should have in our product portfolio". But maybe this is one of those things that's only obvious in retrospect? I'm sure people were trying something similar years ago with grammar-constrained outputs (for example to only output a simple json structure), but you can't get probabilities out of the model that way. Which makes me wonder: how do these models calculate probabilities?

kaycebasques

API docs: https://aistudio.google.com/docs/decisions-api

pratzc07

So is it over for Jev now that the big boys are in the game

abhikul0

There’s also this guide by google to use embedding gemma 2 as a decision maker. Wonder how these compare. https://developers.google.com/edge/mediapipe/solutions/decis...

vesterde

Anyone hear anything around when it might land in Vertex? As far as I can tell it's just in AI Studio for now.

claiir

Why’s the probability type called “noul”?

londons_explore

Presuming this started when Jev was released... If so, thats pretty quick time to release for Google.

theanonymousone

The best decision model I have used (besides Jev itself) is respan/span-02, which is based on (finetuned from?) Gemma4 26A4. That makes me optimistic for this release, despite the high cost.

holografix

Google ensuring “share of wallet” from their existing customer base with a solid but not great “we do it too” product, priced to capitalise on risk and change aversion. Standard practice by the big G.

wasabi991011

Surprised how close all these models are on the benchmarks

5555watch

I still don't really understand where and why these decisions or Jev is useful or interesting? Is there a clear demonstration or tldr anywhere?

kodoman

I have still not used a decision model, How are people using them at the moment? is any one using them in a coding harness like Pi?

nico

For anyone wanting something local, private, faster, which can also run and train on CPU, checkout https:// http://jeffyclassify.com/ It comes with a bunch of pre trained classifiers, and you can use the tooling to train your own There are also integrations with workflow tools like n8n

2001zhaozhao

We're about at the point where the AI is now pretty insanely cheap. Passing 100K tokens of context then asking hundreds of questions of 100 tokens each would cost about as much as a single Google search API call. Out of the hundreds of questions, most of them could even be different variations of the same question to capture more nuance than what is normally possible in a single multiple-choice.

low_tech_punk

Google shipped a "Decision Maker" API a while ago, see https://developers.google.com/edge/mediapipe/solutions/decis... Apparently the two teams aren't talking to each other.

perching_aix

I still have no idea why this is useful. Models are atrocious without reasoning, for classification and otherwise, and this doesn't even just eschew reasoning afaik, but parts of the models as well for lower latency and cost. I genuinely do not see the point. What differentiates this from training a classifier model? That it comes pretrained with general knowledge?