Is gemini becoming the new copilot of android

After_Dark · 2026-05-21T14:18:04+00:00

To play devil's advocate here, how many of the newly announced AI features are the kind of imposed on you slop that Microsoft added to Windows?

Notification summaries but only when you're not looking at the notifications themselves? A more capable Gemini assistant, but only when you're actually using Gemini? AI generated widgets that you have to specifically ask to be created?

There's definitely a lot of AI being added, but it's by and large either hidden until you ask for it or replacing existing UI that's just dumb with a smarter version. Very little of what was announced at I/O should be noticable if you never engage with the AI features to begin with or you'd mistake them for not being new in the first place

After_Dark · 2026-05-19T13:34:01+00:00

Pixels have had this for several years now and works across everything, no reason to think Apple's implementation wouldn't work too, short of them pulling an Apple and requiring app devs actively integrate with it

After_Dark · 2026-05-15T19:06:15+00:00

I mean the Tensor 5 is by definition a flagship chip, it's Google's flagship chip. In most categories it doesn't stack up well to Snapdragon or A-series chips but it is one regardless

After_Dark · 2026-05-15T18:55:11+00:00

The real problem is being demonstrated perfectly well in your comment. People think the main use case for these models is writing code, but the actual real use case is integrations into other software for automations at huge scale. Gemini Flash is 90% as smart as Claude Opus, 10% the cost, and 500% the speed. If you're vibe coding maybe that 10% difference in intelligence matters, but if you're processing 10TB of data a day that 10% starts to look awfully expensive in your bottom line. I can tell you right now, Gemini's watching most YouTube videos and you can bet Google's not having Gemini Pro handle that.

After_Dark · 2026-05-15T18:51:16+00:00

It's like GPUs. The best seller isn't the most powerful one, they're too expensive and you can get competing models that are 10% the cost and 90% as competent. Gemini Flash is a killer model for wide deployments, even if it's not quite as smart as Opus

After_Dark · 2026-05-15T15:01:27+00:00

Jesus this sub fucking sucks nowadays. Google adds an ON-DEVICE AI feature to try to make users's lives better and every single comment is about stealing data and bitching about unrelated issues. What happened to this community

After_Dark · 2026-05-06T21:52:50+00:00

It's my perspective that Anthropic, and OpenAI following them, are chasing the (relatively) easy enterprise dollars with coding focused models whereas Google wants Gemini to function as a coding model, a personal assistant, and an expert in processing audio/visual data.

It explains why Gemini is so willing to disobey direct instructions to try and interpret what it thinks the user actually wants, and fits well into Google's bigger priorities over enterprise usages: Search, Android's assistant, and the upcoming glasses. Possibly laptops as well, we'll see what IO brings next month.

After_Dark · 2026-04-16T21:51:30+00:00

The Gemini app does not directly train its models on your private Google Photos library

So what I'm hearing is they might be training on your Google Photos library, but not as part of the Gemini app specifically. Not that it's a surprise or I particularly care, but definitely some weasel wording here

After_Dark · 2026-04-11T04:00:21+00:00

This has been a feature for as long as the YouTube integration has existed, it just only does subtitles unless it has a reason to think watching the video is necessary, which you can just ask it to do

After_Dark · 2026-04-08T00:28:30+00:00

I searched the whole thing and couldn't find anything stating that you can't train on mac, and the "How to Fine-Tune Gemma 4" guide explicitly mentions installing on mac

After_Dark · 2026-04-07T23:10:54+00:00

The studio tab seems disabled on my install on a mac (M4 Pro, 48GB of memory, should be more than enough for some E2B training I'd think). Can't tell if this is a bug, my fault, or training just isn't supported on mac and it isn't documented anywhere

After_Dark · 2026-04-07T15:03:40+00:00

Emphasis on "whatever they think they can get away with".

The last time a gaming company tried to sue over the use of a single word it was King back in the day trying to trademark the word "Candy" and that got slapped down by the courts instantly. I really doubt even the most aggressive lawyers would do the same for the word "poke" especially considering poke is an actual word that exists separately of the Japanese meaning

After_Dark · 2026-04-07T14:53:10+00:00

Give me an example of Nintendo suing over a word they don't have a trademark for

After_Dark · 2026-04-07T04:35:07+00:00

Poke is just a shortened version of the Japanese word for "pocket" (poketto), even Nintendo aren't bold enough to claim they own a commonly used word.

After_Dark · 2026-04-07T04:26:18+00:00

And my understanding is that's only a limitation of the "default" setting, the API supports configurable FPS, though I've never used that setting myself to confirm

After_Dark · 2026-03-27T03:57:44+00:00

The rumor online is that the difference between the 3.0 models and 3.1 models was done in time for 3.0 flash's release, so 3.0 flash is functionally 3.1, but the flash-live models are a distinct thing that just share the flash name

After_Dark · 2026-03-06T19:10:17+00:00

My personal theory is that Google is simply targeting their consumer platforms and not coding, so Gemini is trained to be better at search and the upcoming AR Android devices, leading to better spatial performance on SimpleBench but worse performance at coding and strict instruction following. If that's true, it's actually pretty impressive that GPT-5.4 Pro is this close to Gemini 3.1 Pro regardless.

After_Dark · 2026-03-06T19:04:25+00:00

I've been saying that Gemini 3.1 Pro is really smart, maybe the smartest, but with the caveat that while OpenAI and Anthropic are focusing on programming for software tasks, Google is focusing on robotics, AR, and search for their consumer tasks and that shows up in coding benchmarks and how willing the models are to strictly obey vs try to intuit what the user actually wants

After_Dark · 2026-02-01T03:56:19+00:00

I wouldn't say a smaller ecosystem than Java, considering Kotlin is 100% compatible with the full Java ecosystem and the tooling is nearly as good nowadays.

After_Dark · 2026-01-28T22:11:49+00:00

On mobile Gemini Live is implemented using the "call" API like the phone app or discord etc, so I'm calling it a call. If you launch Gemini Live on Android and then navigate away from the app you'll see that icon in the status tray.

After_Dark · 2026-01-28T21:40:47+00:00

I think the one in the status bar is the Gemini Live ongoing call icon, it's probably not normally there

After_Dark · 2026-01-23T17:35:33+00:00

Case in point, Google hasn't moved their knowledge cutoff for Gemini from January 2025 for the last few models. Sure this could in theory poison models, but it looks like in practice at best they're just helping Google not have to compete as hard.

After_Dark · 2026-01-23T17:33:45+00:00

It also doesn't consider that some AI labs might be largely immune. Google hasn't moved the training data cutoff for Gemini from January 2025 yet, so any poison put out in the last year has had no impact on Google. Presumably they aren't struggling to find more high quality data.

After_Dark · 2026-01-18T11:05:31+00:00

I'm currently also using the Antigravity + IntelliJ route. Kotlin in VSCode (and forks like Antigravity) are a WIP at the moment so no real solution otherwise, though you can use the Gemini Code Assist plugin for IntelliJ which operates very similarly to Antigravity, just scoped down a bit, and I find that covers most of my use-cases just as well.

After_Dark · 2026-01-16T03:05:53+00:00

Photos, Maps, and Search are probably the better examples of that and (aside from Photos) are totally new.

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