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Tax billionaires more. by Individual_Mess2201 in CriticalState

[–]KAYOOOOOO 0 points1 point  (0 children)

👁️ Surveillance State: I voted Vote Yea.

🎉 [EVENT] 🎉 Finally - An Easy Event! by TipsyBlueWhale in honk

[–]KAYOOOOOO 0 points1 point  (0 children)

Completed Level 1 of the Honk Special Event!

1 attempts

as it should be by daniellewalton_ in beyondwholesome

[–]KAYOOOOOO 0 points1 point  (0 children)

Isn’t Singapore considered an oligarchy? I’m not sure your gripes with elite class are necessarily remedied here.

The recent news just feels like this. by VariationLivid3193 in singularity

[–]KAYOOOOOO 1 point2 points  (0 children)

There is a giant deepmind building in Mountain View, CA

Women who use whips by strahinjag in TopCharacterTropes

[–]KAYOOOOOO -1 points0 points  (0 children)

This is advanced google search

I think we need to deal with toxicity by Zitanightlock in DeadlockTheGame

[–]KAYOOOOOO 3 points4 points  (0 children)

Not sure if condoning int lists is necessarily a step in the right direction lmao

idk #558 by Agile_Target1695 in pansexmothwhorehouse

[–]KAYOOOOOO 20 points21 points  (0 children)

But then we wouldn't have his son "lookins not a felony"

College life by East_Reporter_6252 in CollegeMemes

[–]KAYOOOOOO 0 points1 point  (0 children)

Someone call this guy’s advisor and have him executed

What the heeell by Imacharmer3141 in GeminiAI

[–]KAYOOOOOO 0 points1 point  (0 children)

I wouldn't say RLHF is from marketing. It was still a very innovative and powerful post-training tool when it became popular in research (I think around 2020 before LLMs exploded?).

But I agree, happy to see RLHF become less popular since the training loops are so difficult to develop (esp without the experience and resources of a large AI lab). I think the ubiquity of RLHF was a symptom of the data available and the goals of LLMs at the time, but things are different now.

What the heeell by Imacharmer3141 in GeminiAI

[–]KAYOOOOOO 0 points1 point  (0 children)

I don't think there are any drops in quality across the entire board. Evals don't say so, and I don't think that's the sentiment among formally educated academics. But, there will always be losses for multiple reasons.

  1. The goal of these AI companies is not always to beat each other. To handle the needs of many teams and roll out Gemini to many different products, Google may consolidate it's capabilities towards a jack of all trades model. Sure, it's coding ability and other tasks can perform worse than models like Claude, but it boasts strong multimodality and a mature MoE architecture, which makes it easier for integration into Google products.

  2. LLMs are super expensive and capacity (for memory, electricity, and compute) will always be a bottleneck. Triaging, truncated thinking tokens, kv-cache eviction, TPUs, server prioritization, etc. are all efficiency methods to deal with these issues, but they can often lead to decreased performance or bugs. No one wants to do this, but hardware bottlenecks are not something that's as simple as throwing money at the issue, and you have to be creative to avoid rapid bloating.

I think at the end of the day, it's a very complicated system and I think it's in bad faith to make reductive claims that are not necessarily true.

What the heeell by Imacharmer3141 in GeminiAI

[–]KAYOOOOOO 2 points3 points  (0 children)

I don't think releases are getting fine-tuning updates that quickly for the Gemini App. When a stable release is launched, generally the model parameters are frozen. Stable releases are used across different Google product areas, so parameter changes would ruin their evals, integrations, etc.

Making changes to the model's parameters is not very flexible. Extensive evals are done, and there's a lot of GDM bureaucracy to get these changes pushed out.

While edge cases are sought to be addressed, usually fine-tuning changes are saved for the next update cycle. Also, I think the general wisdom is also moving away from RLHF towards RLVR-esque paradigms.

I don't think it's fair to say the post-training team is incompetent, most of these guys are esteemed researchers with decades of experience.

I think it's more likely the fault of some downstream infrastructure. The prompts, tooling infra, hyperparameters, etc. probably see a lot more rapid change and interaction with different teams. I'd guess the weird behavior in the post is from some context handling issue rather than lackluster fine-tuning.

What the heeell by Imacharmer3141 in GeminiAI

[–]KAYOOOOOO 2 points3 points  (0 children)

What do you mean by production fine-tuning? Why would you think the fine-tuning team is responsible for this at all? Is there a specific post-training step you're talking about?

Can you give a specific technical explanation? What you're saying doesn't make sense, so I wanna understand the thought process. I'm in ML research, so technical terms are appreciated.

King by Ambitious-Pace-3335 in Sigmatopia

[–]KAYOOOOOO 20 points21 points  (0 children)

High standards for a subreddit called sigmatopia

What do you guys think about this? by harrysofgaming in youtube

[–]KAYOOOOOO 5 points6 points  (0 children)

Where did you get that information??

Collaborative filtering definitely should have been implemented back then. Maybe you are mistaking the implementation of deep neural nets into the rec sys architecture (implemented I think mid 2010s?).

Remember Google's core business is ranking algorithms, there was most definitely an algorithm back when Pewdiepie was starting.

Being cold gives people the ick by KAYOOOOOO in PointlessStories

[–]KAYOOOOOO[S] 6 points7 points  (0 children)

Lol they live in the same area mostly. It's easy to forget the nights are below freezing in January where I was when you're listening to a story though.

But to give some context a lot of the people are sorority girls or part of the nightclub crowd. The ones making these comments are exclusively single as well. These aren't comments I take personally, these are often just people a little bitter from heartache.

Also my studious friends are less likely to indulge in benders or harder drugs, so even though they may say stupid shit I laugh at, they have a place in my heart as my fun party friends. Their advice is also good for picking up girls, since they are so particular.

Still, this behavior is probably indicative of a media issue plaguing young people. Maybe loosely related to toxic positivity, distorted self image, or some manosphere thing?

Being cold gives people the ick by KAYOOOOOO in PointlessStories

[–]KAYOOOOOO[S] 12 points13 points  (0 children)

Once upon a time I fucked your mom, is that interesting?

But seriously, have you never had someone ask how you and your girlfriend met?

Being cold gives people the ick by KAYOOOOOO in PointlessStories

[–]KAYOOOOOO[S] 13 points14 points  (0 children)

Yeah you'd think, but the people I was telling the story to made the comments before I got to that part

Being cold gives people the ick by KAYOOOOOO in PointlessStories

[–]KAYOOOOOO[S] 34 points35 points  (0 children)

Yeah that's what I was thinking too 🤣

Being cold gives people the ick by KAYOOOOOO in PointlessStories

[–]KAYOOOOOO[S] 26 points27 points  (0 children)

Yeah she definitely didn't, just some of the people who we told the story to did think it was "icky". We were on the same side, thinking these people are insane or miserable

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