johnb231

They blacklisted games that feature incest. Good riddance. This trash should never have been allowed on Steam.

Of course I can discern that. I think it sounds stupid and childish, and makes someone appear less intelligent. Overused and misused word. But this is now derailing the thread.

The site does not request any personal information, therefore no privacy policy is required.

Devs finish the work 30% faster and take the rest of the day off. That's what I would do. Working remotely.

Dude in 1972 looking at Atari Pong: “computer graphics will never achieve realism”

Meaningless comparison. If xAI or Google accepts the contract, they intend to deliver within the budget. You can't say whether it's too much or too little without knowing all of the details, which you don't.

The process involves running the original model. You can rent these big GPUs for ~$10 per hour, so that is ~$160 per hour for as long as it takes

These are all "too big to host at home". I don't think that is the issue here.

https://github.com/MoonshotAI/Kimi-K2/blob/main/docs/deploy_...

"The smallest deployment unit for Kimi-K2 FP8 weights with 128k seqlen on mainstream H200 or H20 platform is a cluster with 16 GPUs with either Tensor Parallel (TP) or "data parallel + expert parallel" (DP+EP)."

16 GPUs costing ~$30k each. No one is running a ~$500k server at home.

Written by ChatGPT. The second paragraph is obviously AI slop.

This sentence is 100% AI generated: "It’s a symbiotic cycle: retro inspires, modern sustains. Commodore isn’t returning. It’s evolving, with purpose."

That is for professional or commercial use, not casual home users.

You are doing it wrong. That's where you should downvote, not flag.

Frivolous flagging - as you are doing - could eventually get your account privileges removed.

Elon Musk cofounded and funded OpenAI.

I use Grok, ChatGPT, and Gemini. They are all excellent, state of the art, and have their unique strengths and weaknesses.

https://cloud.google.com/terms/service-terms

"b. Disclaimer. PRE-GA OFFERINGS ARE PROVIDED “AS IS” WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES OR REPRESENTATIONS OF ANY KIND. Pre-GA Offerings (i) may be changed, suspended or discontinued at any time without prior notice to Customer and (ii) are not covered by any SLA or Google indemnity. Except as otherwise expressly indicated in a written notice or Google documentation, (A) Pre-GA Offerings are not covered by TSS, and (B) the Data Location Section above will not apply to Pre-GA Offerings."

How is this so hard to understand? It's a preview service for testing only, not intended for production.

I am done with this thread. We are going around in circles.

The users aren't random "human beings" in this case. They are professional software developers who are expected to understand the basics. Deploying that model into production shows a lack of basic competence. It is clearly marked "preview" and is for test only.

This case was simply a matter of people not understanding the terms of service. There is nothing more to be said. It's that simple. The "engineers" should know that before deploying to prod. Basic competence.

And I mean I genuinely do not understand what you are trying to say. Couldn't parse it.

I honestly have no idea what you are trying to say.

It's a preview model - for testing only, not for production. Really not that complicated.

The model is labelled as Preview. There are no guarantees of stability or availability for Preview models. Not intended for production workloads.

https://cloud.google.com/products?hl=en#product-launch-stage...

"At Preview, products or features are ready for testing by customers. Preview offerings are often publicly announced, but are not necessarily feature-complete, and no SLAs or technical support commitments are provided for these. Unless stated otherwise by Google, Preview offerings are intended for use in test environments only. The average Preview stage lasts about six months."

That is a preview / beta model with no expectation of stability. Google did nothing wrong there. No one should be using a preview model in production.

[flagged]

I understood they were referring to the search bar in Windows 11 which I use every day at work. I am saying that feature is redundant since everyone has internet search in the browser. In Linux we have also have DE widgets that provide the same internet search functionality in the taskbar or a popup triggered with a keyboard combo. The Plasma Search plugin framework for KDE is way more powerful and configurable than Windows 11 search.

The Plasma web search plugin includes ~100 search engines / services OOTB.

No, all of the major Linux distros have practically 100% feature parity with each other. The differences are mainly in the default packages and settings, package management tools, release schedule, release QA process, enterprise support contracts, etc.

We’ve had “internet search bars” (aka web browsers) in Linux since the early 90s. The web started on NeXT/Unix, not Windows.

In terms of desktop environment features there is no comparison. The variety of options and widgets in Linux DE’s extends far beyond the basic shit available in Windows.

It took Windows several decades to get virtual desktops (Windows 11). Linux had that in 1993.

You are missing the point. The person I replied to is complaining about the lack of empirical analysis. There is no empirical analysis in the article. Subjective blog articles are not scientific studies.

For this article he took the time explain how it makes him more productive. What more do you expect? Why are you entitled to any more than that?

Developers who are productive with these tools are not going to waste time on that.

They are busy doing their work and prefer their competitors (other developers) to not use these tools.

I suppose it is implemented much like predictive text

Those predictive text systems are usually Markov models. LLMs are fundamentally different. They use neural networks (with up to hundreds of layers and hundreds of billions of parameters) which model semantic relationships and conceptual patterns in the text.

The point is not made clear in the first few sentences. Ironically you could have used AI to make the post readable. Copy/paste AI slop.

It's not pointless. This is research.

Here's something interesting from the conclusion of the paper:

"An interesting and promising direction for future work that leverages the inherent differentiability, would be to apply RenderFormer to inverse rendering applications."

That means generate a 3D scene from 2D images.

Correct and it wasn’t fixed with more parameters. Reasoning models question their own output, and all of the current models can verify their sources online before replying. They are not perfect, but they are much better than they used to be, and it is practically not an issue most of the time. I have seen the reasoning models correct their own output while it is being generated. Gemini 2.5 Pro, GPT-o3, Grok 3.